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  • richardmitnick 9:48 am on September 20, 2021 Permalink | Reply
    Tags: "Taking on the stormy seas", Mathematics, ,   

    From The Massachusetts Institute of Technology (US) : “Taking on the stormy seas” 

    MIT News

    From The Massachusetts Institute of Technology (US)

    September 19, 2021
    Michaela Jarvis

    1
    Themistoklis Sapsis, an associate professor of mechanical engineering at MIT, uses analytical and computational methods to try to predict behavior — such as that of ocean waves or instability inside a gas turbine — amid uncertain and occasionally extreme dynamics. Credit: M. Scott Brauer.

    On his first day of classes at the Technical University of Athens’ School of Naval Architecture and Marine Engineering, Themistoklis Sapsis had a very satisfying realization.

    “I realized that ships and other maritime structures are the only ones that operate at the interface of two different media: air and water,” says Sapsis. “This property alone creates so many challenges in terms of mathematical and computational modeling. And, of course, these media are not calm at all — they are random and often surprisingly unpredictable.”

    In other words, Sapsis did not have to choose between his two great passions: huge, ocean-going ships and structures on the one hand, and mathematics on the other. Today, Sapsis, an associate professor of mechanical engineering at MIT, uses analytical and computational methods to try to predict behavior — such as that of ocean waves or instability inside a gas turbine — amid uncertain and occasionally extreme dynamics. His goal is to create designs for structures that are robust and safe even in a broad range of conditions. For example, he may study the loads acting on a ship during a storm, or the flow separation and lift reduction around a helicopter rotor blade during a difficult maneuver.

    “These events are real — they often lead to big catastrophes and casualties,” Sapsis says. “My goal is to predict them and develop algorithms that can simulate them quickly. If we achieve this goal, then we could start talking about optimization and design of these systems with consideration of these extreme, rare, but possibly catastrophic events.”

    Growing up in Athens, where great seafaring and mathematical traditions date back to ancient times, Sapsis’ house was “full of machine elements, spare engines, and engineering blueprints,” the tools of his father’s trade as a superintendent engineer in the maritime industry.

    His father traveled internationally to oversee major ship repairs, and Sapsis often went along.

    “I think what made the biggest impression on me as a child was the size of these vessels and especially the engines. You had to climb five or six flights of stairs to see the whole thing,” he recalls.

    Also in the Sapsis home were math and engineering books — “lots of them,” he says. His father insisted that he study math closely, at the same time that the young Sapsis was conducting physics experiments in the basement.

    “This back-and-forth transition between dynamical systems — more generally mathematics — and naval architecture” was frequently on his mind, Sapsis says.

    In college, Sapsis ended up taking every math class that was offered. He says he had the good fortune to get in touch early on with the most mathematically inclined professor in the School of Naval Architecture and Marine Engineering, who then mentored Sapsis for three years. In his spare time, Sapsis even attended classes in the university’s School of Applied Mathematics.

    His undergraduate thesis was on probabilistic description of dynamical systems subjected to random excitations, a topic important to the understanding of the motions of large ships and loads. One of Sapsis’ most memorable research breakthroughs occurred while he was working on that thesis.

    “I was given a nice problem by my thesis advisor,” Sapsis says. “He warned me that most likely I would not be able to get something new, as this was an old problem and many had tried in the past decades without success.”

    Over the next six months, Sapsis went over every step of the methods that were in the academic literature, “again and again,” he says, trying to understand why various approaches failed. He started to discern a path toward deriving a new set of equations that could achieve his goal, but there were technical obstacles.

    “Without a lot of hope, as I knew that his was an old problem, but with a lot of curiosity, I began working on the different steps,” Sapsis says. “After a few weeks of work, I realized that the steps were complete, and I had a new set of equations!”

    “It was certainly one of my most enthusiastic moments,” Sapsis says, “when I heard my advisor saying, ‘Yes, this is new and it is important!’”

    Since that early success, the engineering and architecture problems associated with building for the extreme and unpredictable ocean environment have provided Sapsis with plenty of research problems to solve.

    “Naval architecture is one of the oldest professions, with many open problems remaining and many more new ones coming,” he says. “The theoretical tools should not be more complex than the problem itself. However, in this case there are some really challenging physical problems that require the development of fundamentally new mathematics and computational methods. I am always trying to begin with the fundamentals and build the right theoretical and computational tools to, hopefully, come closer to the modeling of certain complex phenomena.”

    Sapsis, who joined the MIT faculty in 2013 and was tenured in 2019, says he loves the energy and pace of the Institute, where “there are so many things happening here that you can never feel you have achieved enough — but in a healthy way.”

    “I always feel humbled by the amazing achievements of my colleagues and our students and postdocs,” he says. “It is a place filled with pure passion and talent, blended together for a good cause, to solve the world’s hardest problems.”

    These days, Sapsis says it is his students who experience the pure excitement of finding solutions to problems in the field.

    “My students and postdocs are now the ones who have the pleasure to be the first to find out when a new idea works,” Sapsis says. “I have to admit, however, that I save some problems for myself.”

    In fact, Sapsis says he relaxes by “thinking about a nice problem: a high-risk and low-expectations one. I think of a strategy to go about it but know that most likely it will not work. This is something I don’t consider work.”

    See the full article here .


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    Please help promote STEM in your local schools.

    Stem Education Coalition

    MIT Seal

    USPS “Forever” postage stamps celebrating Innovation at MIT.

    MIT Campus

    The Massachusetts Institute of Technology (US) is a private land-grant research university in Cambridge, Massachusetts. The institute has an urban campus that extends more than a mile (1.6 km) alongside the Charles River. The institute also encompasses a number of major off-campus facilities such as the The MIT Lincoln Laboratory (US), The MIT Bates Research and Engineering Center (US), and The Haystack Observatory (US), as well as affiliated laboratories such as The Broad Institute of MIT and Harvard(US) and The Whitehead Institute (US).

    Founded in 1861 in response to the increasing industrialization of the United States, The Massachusetts Institute of Technology adopted a European polytechnic university model and stressed laboratory instruction in applied science and engineering. It has since played a key role in the development of many aspects of modern science, engineering, mathematics, and technology, and is widely known for its innovation and academic strength. It is frequently regarded as one of the most prestigious universities in the world.

    As of December 2020, 97 Nobel laureates, 26 Turing Award winners, and 8 Fields Medalists have been affiliated with MIT as alumni, faculty members, or researchers. In addition, 58 National Medal of Science recipients, 29 National Medals of Technology and Innovation recipients, 50 MacArthur Fellows, 80 Marshall Scholars, 3 Mitchell Scholars, 22 Schwarzman Scholars, 41 astronauts, and 16 Chief Scientists of the U.S. Air Force have been affiliated with Massachusetts Institute of Technology (US) . The university also has a strong entrepreneurial culture and MIT alumni have founded or co-founded many notable companies. The Massachusetts Institute of Technology is a member of the Association of American Universities (AAU).

    Foundation and vision

    In 1859, a proposal was submitted to the Massachusetts General Court to use newly filled lands in Back Bay, Boston for a “Conservatory of Art and Science”, but the proposal failed. A charter for the incorporation of the Massachusetts Institute of Technology, proposed by William Barton Rogers, was signed by John Albion Andrew, the governor of Massachusetts, on April 10, 1861.

    Rogers, a professor from the University of Virginia (US), wanted to establish an institution to address rapid scientific and technological advances. He did not wish to found a professional school, but a combination with elements of both professional and liberal education, proposing that:

    “The true and only practicable object of a polytechnic school is, as I conceive, the teaching, not of the minute details and manipulations of the arts, which can be done only in the workshop, but the inculcation of those scientific principles which form the basis and explanation of them, and along with this, a full and methodical review of all their leading processes and operations in connection with physical laws.”

    The Rogers Plan reflected the German research university model, emphasizing an independent faculty engaged in research, as well as instruction oriented around seminars and laboratories.

    Early developments

    Two days after The Massachusetts Institute of Technology was chartered, the first battle of the Civil War broke out. After a long delay through the war years, MIT’s first classes were held in the Mercantile Building in Boston in 1865. The new institute was founded as part of the Morrill Land-Grant Colleges Act to fund institutions “to promote the liberal and practical education of the industrial classes” and was a land-grant school. In 1863 under the same act, the Commonwealth of Massachusetts founded the Massachusetts Agricultural College, which developed as The University of Massachusetts-Amherst (US). In 1866, the proceeds from land sales went toward new buildings in the Back Bay.

    The Massachusetts Institute of Technology was informally called “Boston Tech”. The institute adopted the European polytechnic university model and emphasized laboratory instruction from an early date. Despite chronic financial problems, the institute saw growth in the last two decades of the 19th century under President Francis Amasa Walker. Programs in electrical, chemical, marine, and sanitary engineering were introduced, new buildings were built, and the size of the student body increased to more than one thousand.

    The curriculum drifted to a vocational emphasis, with less focus on theoretical science. The fledgling school still suffered from chronic financial shortages which diverted the attention of the MIT leadership. During these “Boston Tech” years, The Massachusetts Institute of Technology faculty and alumni rebuffed Harvard University (US) president (and former MIT faculty) Charles W. Eliot’s repeated attempts to merge MIT with Harvard College’s Lawrence Scientific School. There would be at least six attempts to absorb MIT into Harvard. In its cramped Back Bay location, MIT could not afford to expand its overcrowded facilities, driving a desperate search for a new campus and funding. Eventually, the MIT Corporation approved a formal agreement to merge with Harvard, over the vehement objections of MIT faculty, students, and alumni. However, a 1917 decision by the Massachusetts Supreme Judicial Court effectively put an end to the merger scheme.

    In 1916, The Massachusetts Institute of Technology administration and the MIT charter crossed the Charles River on the ceremonial barge Bucentaur built for the occasion, to signify MIT’s move to a spacious new campus largely consisting of filled land on a one-mile-long (1.6 km) tract along the Cambridge side of the Charles River. The neoclassical “New Technology” campus was designed by William W. Bosworth and had been funded largely by anonymous donations from a mysterious “Mr. Smith”, starting in 1912. In January 1920, the donor was revealed to be the industrialist George Eastman of Rochester, New York, who had invented methods of film production and processing, and founded Eastman Kodak. Between 1912 and 1920, Eastman donated $20 million ($236.6 million in 2015 dollars) in cash and Kodak stock to MIT.

    Curricular reforms

    In the 1930s, President Karl Taylor Compton and Vice-President (effectively Provost) Vannevar Bush emphasized the importance of pure sciences like physics and chemistry and reduced the vocational practice required in shops and drafting studios. The Compton reforms “renewed confidence in the ability of the Institute to develop leadership in science as well as in engineering”. Unlike Ivy League schools, The Massachusetts Institute of Technology catered more to middle-class families, and depended more on tuition than on endowments or grants for its funding. The school was elected to the Association of American Universities (US)in 1934.

    Still, as late as 1949, the Lewis Committee lamented in its report on the state of education at The Massachusetts Institute of Technology that “the Institute is widely conceived as basically a vocational school”, a “partly unjustified” perception the committee sought to change. The report comprehensively reviewed the undergraduate curriculum, recommended offering a broader education, and warned against letting engineering and government-sponsored research detract from the sciences and humanities. The School of Humanities, Arts, and Social Sciences and The MIT Sloan School of Management were formed in 1950 to compete with the powerful Schools of Science and Engineering. Previously marginalized faculties in the areas of economics, management, political science, and linguistics emerged into cohesive and assertive departments by attracting respected professors and launching competitive graduate programs. The School of Humanities, Arts, and Social Sciences continued to develop under the successive terms of the more humanistically oriented presidents Howard W. Johnson and Jerome Wiesner between 1966 and 1980.

    The Massachusetts Institute of Technology‘s involvement in military science surged during World War II. In 1941, Vannevar Bush was appointed head of the federal Office of Scientific Research and Development and directed funding to only a select group of universities, including MIT. Engineers and scientists from across the country gathered at The Massachusetts Institute of Technology’s Radiation Laboratory, established in 1940 to assist the British military in developing microwave radar. The work done there significantly affected both the war and subsequent research in the area. Other defense projects included gyroscope-based and other complex control systems for gunsight, bombsight, and inertial navigation under Charles Stark Draper’s Instrumentation Laboratory; the development of a digital computer for flight simulations under Project Whirlwind; and high-speed and high-altitude photography under Harold Edgerton. By the end of the war, The Massachusetts Institute of Technology became the nation’s largest wartime R&D contractor (attracting some criticism of Bush), employing nearly 4000 in the Radiation Laboratory alone and receiving in excess of $100 million ($1.2 billion in 2015 dollars) before 1946. Work on defense projects continued even after then. Post-war government-sponsored research at MIT included SAGE and guidance systems for ballistic missiles and Project Apollo.

    These activities affected The Massachusetts Institute of Technology profoundly. A 1949 report noted the lack of “any great slackening in the pace of life at the Institute” to match the return to peacetime, remembering the “academic tranquility of the prewar years”, though acknowledging the significant contributions of military research to the increased emphasis on graduate education and rapid growth of personnel and facilities. The faculty doubled and the graduate student body quintupled during the terms of Karl Taylor Compton, president of The Massachusetts Institute of Technology between 1930 and 1948; James Rhyne Killian, president from 1948 to 1957; and Julius Adams Stratton, chancellor from 1952 to 1957, whose institution-building strategies shaped the expanding university. By the 1950s, The Massachusetts Institute of Technology no longer simply benefited the industries with which it had worked for three decades, and it had developed closer working relationships with new patrons, philanthropic foundations and the federal government.

    In late 1960s and early 1970s, student and faculty activists protested against the Vietnam War and The Massachusetts Institute of Technology’s defense research. In this period The Massachusetts Institute of Technology’s various departments were researching helicopters, smart bombs and counterinsurgency techniques for the war in Vietnam as well as guidance systems for nuclear missiles. The Union of Concerned Scientists was founded on March 4, 1969 during a meeting of faculty members and students seeking to shift the emphasis on military research toward environmental and social problems. The Massachusetts Institute of Technology ultimately divested itself from the Instrumentation Laboratory and moved all classified research off-campus to the The MIT Lincoln Laboratory facility in 1973 in response to protests. The student body, faculty, and administration remained comparatively unpolarized during what was a tumultuous time for many other universities. Johnson was seen to be highly successful in leading his institution to “greater strength and unity” after these times of turmoil. However six Massachusetts Institute of Technology students were sentenced to prison terms at this time and some former student leaders, such as Michael Albert and George Katsiaficas, are still indignant about MIT’s role in military research and its suppression of these protests. (Richard Leacock’s film, November Actions, records some of these tumultuous events.)

    In the 1980s, there was more controversy at The Massachusetts Institute of Technology over its involvement in SDI (space weaponry) and CBW (chemical and biological warfare) research. More recently, The Massachusetts Institute of Technology’s research for the military has included work on robots, drones and ‘battle suits’.

    Recent history

    The Massachusetts Institute of Technology has kept pace with and helped to advance the digital age. In addition to developing the predecessors to modern computing and networking technologies, students, staff, and faculty members at Project MAC, The Artificial Intelligence Laboratory, and The Tech Model Railroad Club wrote some of the earliest interactive computer video games like Spacewar! and created much of modern hacker slang and culture. Several major computer-related organizations have originated at MIT since the 1980s: Richard Stallman’s GNU Project and the subsequent Free Software Foundation were founded in the mid-1980s at the AI Lab; The MIT Media Lab was founded in 1985 by Nicholas Negroponte and Jerome Wiesner to promote research into novel uses of computer technology; the World Wide Web Consortium standards organization was founded at The Laboratory for Computer Science in 1994 by Tim Berners-Lee; The MIT OpenCourseWare project has made course materials for over 2,000 Massachusetts Institute of Technology classes available online free of charge since 2002; and The One Laptop per Child initiative to expand computer education and connectivity to children worldwide was launched in 2005.

    The Massachusetts Institute of Technology was named a sea-grant college in 1976 to support its programs in oceanography and marine sciences and was named a space-grant college in 1989 to support its aeronautics and astronautics programs. Despite diminishing government financial support over the past quarter century, MIT launched several successful development campaigns to significantly expand the campus: new dormitories and athletics buildings on west campus; The Tang Center for Management Education; several buildings in the northeast corner of campus supporting research into biology, brain and cognitive sciences, genomics, biotechnology, and cancer research; and a number of new “backlot” buildings on Vassar Street including The Stata Center. Construction on campus in the 2000s included expansions of the Media Lab, the Sloan School’s eastern campus, and graduate residences in the northwest. In 2006, President Hockfield launched The MIT Energy Research Council to investigate the interdisciplinary challenges posed by increasing global energy consumption.

    In 2001, inspired by the open source and open access movements, The Massachusetts Institute of Technology launched OpenCourseWare to make the lecture notes, problem sets, syllabi, exams, and lectures from the great majority of its courses available online for no charge, though without any formal accreditation for coursework completed. While the cost of supporting and hosting the project is high, OCW expanded in 2005 to include other universities as a part of the OpenCourseWare Consortium, which currently includes more than 250 academic institutions with content available in at least six languages. In 2011, The Massachusetts Institute of Technology announced it would offer formal certification (but not credits or degrees) to online participants completing coursework in its “MITx” program, for a modest fee. The “edX” online platform supporting MITx was initially developed in partnership with Harvard and its analogous “Harvardx” initiative. The courseware platform is open source, and other universities have already joined and added their own course content. In March 2009 The Massachusetts Institute of Technology faculty adopted an open-access policy to make its scholarship publicly accessible online.

    The Massachusetts Institute of Technology has its own police force. Three days after the Boston Marathon bombing of April 2013, MIT Police patrol officer Sean Collier was fatally shot by the suspects Dzhokhar and Tamerlan Tsarnaev, setting off a violent manhunt that shut down the campus and much of the Boston metropolitan area for a day. One week later, Collier’s memorial service was attended by more than 10,000 people, in a ceremony hosted by The Massachusetts Institute of Technology (US) community with thousands of police officers from the New England region and Canada. On November 25, 2013, The Massachusetts Institute of Technology announced the creation of The Collier Medal, to be awarded annually to “an individual or group that embodies the character and qualities that Officer Collier exhibited as a member of The Massachusetts Institute of Technology community and in all aspects of his life”. The announcement further stated that “Future recipients of the award will include those whose contributions exceed the boundaries of their profession, those who have contributed to building bridges across the community, and those who consistently and selflessly perform acts of kindness”.

    In September 2017, the school announced the creation of an artificial intelligence research lab called The MIT-IBM Watson AI Lab. IBM will spend $240 million over the next decade, and the lab will be staffed by MIT and IBM scientists. In October 2018 MIT announced that it would open a new Schwarzman College of Computing dedicated to the study of artificial intelligence, named after lead donor and The Blackstone Group CEO Stephen Schwarzman. The focus of the new college is to study not just AI, but interdisciplinary AI education, and how AI can be used in fields as diverse as history and biology. The cost of buildings and new faculty for the new college is expected to be $1 billion upon completion.

    The Caltech/MIT Advanced aLIGO (US) was designed and constructed by a team of scientists from California Institute of Technology (US), Massachusetts Institute of Technology, and industrial contractors, and funded by The National Science Foundation (US).

    It was designed to open the field of gravitational-wave astronomy through the detection of gravitational waves predicted by general relativity. Gravitational waves were detected for the first time by the LIGO detector in 2015. For contributions to the LIGO detector and the observation of gravitational waves, two Caltech physicists, Kip Thorne and Barry Barish, and The Massachusetts Institute of Technology (US) physicist Rainer Weiss won the Nobel Prize in physics in 2017. Weiss, who is also a Massachusetts Institute of Technology graduate, designed the laser interferometric technique, which served as the essential blueprint for the LIGO.

    The mission of The Massachusetts Institute of Technology is to advance knowledge and educate students in science, technology, and other areas of scholarship that will best serve the nation and the world in the twenty-first century. We seek to develop in each member of the Massachusetts Institute of Technology community the ability and passion to work wisely, creatively, and effectively for the betterment of humankind.

     
  • richardmitnick 12:31 pm on August 27, 2021 Permalink | Reply
    Tags: "SURP Student Spotlight-Sina Babaei Zadeh", , Mathematics,   

    From Dunlap Institute for Astronomy and Astrophysics (CA) : “SURP Student Spotlight-Sina Babaei Zadeh” 

    From Dunlap Institute for Astronomy and Astrophysics (CA)

    At

    University of Toronto (CA)

    8.24.21

    1
    Originally from Toronto, Sina is going into his second year of math and astrophysics double major at Western University (CA) this fall. In addition to his SURP grant, he was awarded the Aurora Borealis Fellowship.

    What made you decide to participate in SURP?

    I have always wanted to participate in scientific research. I was fortunate enough to be offered several amazing research opportunities this summer (e.g. CGCS and U of T SURF). I chose SURP because of its attractive resources, especially its mentors. Moreover, SURP offered a variety of events in addition to research such as weekly astronomy seminars and even a free summer school in coding. Truly, I chose SURP because it is not an ordinary undergraduate research project, but a summer in an astronomer’s shoes.

    What is your favourite thing about SURP?

    This is a hard question as there are a lot of top things, but if I had to select one, I would choose the diversity at every level from mentors to administrators to SURP students themselves. There are people from all around the world with unique backgrounds and views. This allows you to experience and learn about research topics and methods in North America, but also from other continents. For instance, I got to work with a UK based simulation- one of the largest in the world- because one of my mentors had completed his education in the UK and thus had familiarity with it. This diversity is also great for learning about other cultures and perspectives, something that I highly value.

    Can you tell us about your research project?

    In our project, we have utilized the EAGLE database, a very large simulation, containing data on about a million galaxies and their relative properties such as SFR (star formation rate) to test if we can make predictions about the properties of a particular galaxy based on its assembly history. Specifically, we grouped galaxies based on the closeness of SFH (star formation history) to exponential functions governed by a single parameter. This allowed us to draw conclusions and trends about the differences of each group when compared to each other. Both our approaches will enable us to predict how galaxies like our own Milky Way may look like in future and predict their early history.

    Can you explain how SURP has perhaps been different from your undergrad work?

    One obvious difference is the learning environment. In regular classes, the student to teacher ratio is very high, but in SURP it can be even smaller than one (in my case it was 1:3)! This allows you to work with top scientists very closely and actually feel part of the researcher community. Furthermore, the environment is much more relaxed and you can just chat with your mentors anytime that you want whether it’s a research question, or just social chatter! Although research is open ended and can be much more intimidating than reading undergraduate textbooks, the support is also at a higher level and as long as you are motivated, it will be much more valuable than normal courses. Simply, the maximum you can do in an undergraduate class is to achieve a perfect grade, but at SURP the maximum is virtually limitless.

    What are your plans for the future?

    I want to keep my options open. After SURP, graduate school in astronomy is a likely possibility. All I know is that I feel tremendously grateful to have had the opportunity to participate in SURP and attend university in general. I really want to try my best to be in the position of helping the next generation in a few years, especially my fellow black Canadians. This will allow me to give back some of the things that I have used, and enable many other students to have quality experiences like I did at SURP. To put it simply, SURP has not given me a glimpse of what a career in astronomy will look like, it has also expanded my vision and made me a more mature individual.

    See the full article here .


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    Please help promote STEM in your local schools.


    Stem Education Coalition

    Dunlap Institute campus

    The Dunlap Institute for Astronomy & Astrophysics (CA) at University of Toronto (CA) is an endowed research institute with nearly 70 faculty, postdocs, students and staff, dedicated to innovative technology, ground-breaking research, world-class training, and public engagement. The research themes of its faculty and Dunlap Fellows span the Universe and include: optical, infrared and radio instrumentation; Dark Energy; large-scale structure; the Cosmic Microwave Background; the interstellar medium; galaxy evolution; cosmic magnetism; and time-domain science.

    The Dunlap Institute (CA), University of Toronto Department of Astronomy & Astrophysics (CA), Canadian Institute for Theoretical Astrophysics (CA), and Centre for Planetary Sciences (CA) comprise the leading centre for astronomical research in Canada, at the leading research university in the country, the University of Toronto (CA).

    The Dunlap Institute (CA) is committed to making its science, training and public outreach activities productive and enjoyable for everyone, regardless of gender, sexual orientation, disability, physical appearance, body size, race, nationality or religion.

    Our work is greatly enhanced through collaborations with the Department of Astronomy & Astrophysics (CA), Canadian Institute for Theoretical Astrophysics (CA), David Dunlap Observatory (CA), Ontario Science Centre (CA), Royal Astronomical Society of Canada (CA), the Toronto Public Library (CA), and many other partners.

    NIROSETI team from left to right Rem Stone UCO Lick Observatory Dan Werthimer, UC Berkeley; Jérôme Maire, U Toronto; Shelley Wright, UCSD; Patrick Dorval, U Toronto; Richard Treffers, Starman Systems. (Image by Laurie Hatch).

    The University of Toronto(CA) is a public research university in Toronto, Ontario, Canada, located on the grounds that surround Queen’s Park. It was founded by royal charter in 1827 as King’s College, the oldest university in the province of Ontario.

    Originally controlled by the Church of England, the university assumed its present name in 1850 upon becoming a secular institution.

    As a collegiate university, it comprises eleven colleges each with substantial autonomy on financial and institutional affairs and significant differences in character and history. The university also operates two satellite campuses located in Scarborough and Mississauga.

    University of Toronto has evolved into Canada’s leading institution of learning, discovery and knowledge creation. We are proud to be one of the world’s top research-intensive universities, driven to invent and innovate.

    Our students have the opportunity to learn from and work with preeminent thought leaders through our multidisciplinary network of teaching and research faculty, alumni and partners.

    The ideas, innovations and actions of more than 560,000 graduates continue to have a positive impact on the world.

    Academically, the University of Toronto is noted for movements and curricula in literary criticism and communication theory, known collectively as the Toronto School.

    The university was the birthplace of insulin and stem cell research, and was the site of the first electron microscope in North America; the identification of the first black hole Cygnus X-1; multi-touch technology, and the development of the theory of NP-completeness.

    The university was one of several universities involved in early research of deep learning. It receives the most annual scientific research funding of any Canadian university and is one of two members of the Association of American Universities (US) outside the United States, the other being McGill(CA).

    The Varsity Blues are the athletic teams that represent the university in intercollegiate league matches, with ties to gridiron football, rowing and ice hockey. The earliest recorded instance of gridiron football occurred at University of Toronto’s University College in November 1861.

    The university’s Hart House is an early example of the North American student centre, simultaneously serving cultural, intellectual, and recreational interests within its large Gothic-revival complex.

    The University of Toronto has educated three Governors General of Canada, four Prime Ministers of Canada, three foreign leaders, and fourteen Justices of the Supreme Court. As of March 2019, ten Nobel laureates, five Turing Award winners, 94 Rhodes Scholars, and one Fields Medalist have been affiliated with the university.

    Early history

    The founding of a colonial college had long been the desire of John Graves Simcoe, the first Lieutenant-Governor of Upper Canada and founder of York, the colonial capital. As an University of Oxford (UK)-educated military commander who had fought in the American Revolutionary War, Simcoe believed a college was needed to counter the spread of republicanism from the United States. The Upper Canada Executive Committee recommended in 1798 that a college be established in York.

    On March 15, 1827, a royal charter was formally issued by King George IV, proclaiming “from this time one College, with the style and privileges of a University … for the education of youth in the principles of the Christian Religion, and for their instruction in the various branches of Science and Literature … to continue for ever, to be called King’s College.” The granting of the charter was largely the result of intense lobbying by John Strachan, the influential Anglican Bishop of Toronto who took office as the college’s first president. The original three-storey Greek Revival school building was built on the present site of Queen’s Park.

    Under Strachan’s stewardship, King’s College was a religious institution closely aligned with the Church of England and the British colonial elite, known as the Family Compact. Reformist politicians opposed the clergy’s control over colonial institutions and fought to have the college secularized. In 1849, after a lengthy and heated debate, the newly elected responsible government of the Province of Canada voted to rename King’s College as the University of Toronto and severed the school’s ties with the church. Having anticipated this decision, the enraged Strachan had resigned a year earlier to open Trinity College as a private Anglican seminary. University College was created as the nondenominational teaching branch of the University of Toronto. During the American Civil War the threat of Union blockade on British North America prompted the creation of the University Rifle Corps which saw battle in resisting the Fenian raids on the Niagara border in 1866. The Corps was part of the Reserve Militia lead by Professor Henry Croft.

    Established in 1878, the School of Practical Science was the precursor to the Faculty of Applied Science and Engineering which has been nicknamed Skule since its earliest days. While the Faculty of Medicine opened in 1843 medical teaching was conducted by proprietary schools from 1853 until 1887 when the faculty absorbed the Toronto School of Medicine. Meanwhile the university continued to set examinations and confer medical degrees. The university opened the Faculty of Law in 1887, followed by the Faculty of Dentistry in 1888 when the Royal College of Dental Surgeons became an affiliate. Women were first admitted to the university in 1884.

    A devastating fire in 1890 gutted the interior of University College and destroyed 33,000 volumes from the library but the university restored the building and replenished its library within two years. Over the next two decades a collegiate system took shape as the university arranged federation with several ecclesiastical colleges including Strachan’s Trinity College in 1904. The university operated the Royal Conservatory of Music from 1896 to 1991 and the Royal Ontario Museum from 1912 to 1968; both still retain close ties with the university as independent institutions. The University of Toronto Press was founded in 1901 as Canada’s first academic publishing house. The Faculty of Forestry founded in 1907 with Bernhard Fernow as dean was Canada’s first university faculty devoted to forest science. In 1910, the Faculty of Education opened its laboratory school, the University of Toronto Schools.

    World wars and post-war years

    The First and Second World Wars curtailed some university activities as undergraduate and graduate men eagerly enlisted. Intercollegiate athletic competitions and the Hart House Debates were suspended although exhibition and interfaculty games were still held. The David Dunlap Observatory in Richmond Hill opened in 1935 followed by the University of Toronto Institute for Aerospace Studies in 1949. The university opened satellite campuses in Scarborough in 1964 and in Mississauga in 1967. The university’s former affiliated schools at the Ontario Agricultural College and Glendon Hall became fully independent of the University of Toronto and became part of University of Guelph (CA) in 1964 and York University (CA) in 1965 respectively. Beginning in the 1980s reductions in government funding prompted more rigorous fundraising efforts.

    Since 2000

    In 2000 Kin-Yip Chun was reinstated as a professor of the university after he launched an unsuccessful lawsuit against the university alleging racial discrimination. In 2017 a human rights application was filed against the University by one of its students for allegedly delaying the investigation of sexual assault and being dismissive of their concerns. In 2018 the university cleared one of its professors of allegations of discrimination and antisemitism in an internal investigation after a complaint was filed by one of its students.

    The University of Toronto was the first Canadian university to amass a financial endowment greater than c. $1 billion in 2007. On September 24, 2020 the university announced a $250 million gift to the Faculty of Medicine from businessman and philanthropist James C. Temerty- the largest single philanthropic donation in Canadian history. This broke the previous record for the school set in 2019 when Gerry Schwartz and Heather Reisman jointly donated $100 million for the creation of a 750,000-square foot innovation and artificial intelligence centre.

    Research

    Since 1926 the University of Toronto has been a member of the Association of American Universities (US) a consortium of the leading North American research universities. The university manages by far the largest annual research budget of any university in Canada with sponsored direct-cost expenditures of $878 million in 2010. In 2018 the University of Toronto was named the top research university in Canada by Research Infosource with a sponsored research income (external sources of funding) of $1,147.584 million in 2017. In the same year the university’s faculty averaged a sponsored research income of $428,200 while graduate students averaged a sponsored research income of $63,700. The federal government was the largest source of funding with grants from the Canadian Institutes of Health Research; the Natural Sciences and Engineering Research Council; and the Social Sciences and Humanities Research Council amounting to about one-third of the research budget. About eight percent of research funding came from corporations- mostly in the healthcare industry.

    The first practical electron microscope was built by the physics department in 1938. During World War II the university developed the G-suit- a life-saving garment worn by Allied fighter plane pilots later adopted for use by astronauts.Development of the infrared chemiluminescence technique improved analyses of energy behaviours in chemical reactions. In 1963 the asteroid 2104 Toronto was discovered in the David Dunlap Observatory (CA) in Richmond Hill and is named after the university. In 1972 studies on Cygnus X-1 led to the publication of the first observational evidence proving the existence of black holes. Toronto astronomers have also discovered the Uranian moons of Caliban and Sycorax; the dwarf galaxies of Andromeda I, II and III; and the supernova SN 1987A. A pioneer in computing technology the university designed and built UTEC- one of the world’s first operational computers- and later purchased Ferut- the second commercial computer after UNIVAC I. Multi-touch technology was developed at Toronto with applications ranging from handheld devices to collaboration walls. The AeroVelo Atlas which won the Igor I. Sikorsky Human Powered Helicopter Competition in 2013 was developed by the university’s team of students and graduates and was tested in Vaughan.

    The discovery of insulin at the University of Toronto in 1921 is considered among the most significant events in the history of medicine. The stem cell was discovered at the university in 1963 forming the basis for bone marrow transplantation and all subsequent research on adult and embryonic stem cells. This was the first of many findings at Toronto relating to stem cells including the identification of pancreatic and retinal stem cells. The cancer stem cell was first identified in 1997 by Toronto researchers who have since found stem cell associations in leukemia; brain tumors; and colorectal cancer. Medical inventions developed at Toronto include the glycaemic index; the infant cereal Pablum; the use of protective hypothermia in open heart surgery; and the first artificial cardiac pacemaker. The first successful single-lung transplant was performed at Toronto in 1981 followed by the first nerve transplant in 1988; and the first double-lung transplant in 1989. Researchers identified the maturation promoting factor that regulates cell division and discovered the T-cell receptor which triggers responses of the immune system. The university is credited with isolating the genes that cause Fanconi anemia; cystic fibrosis; and early-onset Alzheimer’s disease among numerous other diseases. Between 1914 and 1972 the university operated the Connaught Medical Research Laboratories- now part of the pharmaceutical corporation Sanofi-Aventis. Among the research conducted at the laboratory was the development of gel electrophoresis.

    The University of Toronto is the primary research presence that supports one of the world’s largest concentrations of biotechnology firms. More than 5,000 principal investigators reside within 2 kilometres (1.2 mi) from the university grounds in Toronto’s Discovery District conducting $1 billion of medical research annually. MaRS Discovery District is a research park that serves commercial enterprises and the university’s technology transfer ventures. In 2008, the university disclosed 159 inventions and had 114 active start-up companies. Its SciNet Consortium operates the most powerful supercomputer in Canada.

     
  • richardmitnick 3:00 pm on August 25, 2021 Permalink | Reply
    Tags: "CAMERA Mathematicians Build an Algorithm to ‘Do the Twist’", A mathematical algorithm to decipher the rotational dynamics of twisting particles in large complex systems., , , Mathematics, Studying the properties of suspensions and solutions of colloids; macromolecules; and polymers., XPCS works by focusing a coherent beam of X-rays to capture light scattered off of particles in suspension.,   

    From DOE’s Lawrence Berkeley National Laboratory (US): “CAMERA Mathematicians Build an Algorithm to ‘Do the Twist’” 

    From DOE’s Lawrence Berkeley National Laboratory (US)

    August 18, 2021

    New Approach Extracts Rotational Diffusion from X-ray Photon Correlation Spectroscopy Experiments.

    Mathematicians at the Center for Advanced Mathematics for Energy Research Applications (CAMERA) at Lawrence Berkeley National Laboratory (Berkeley Lab) have developed a mathematical algorithm to decipher the rotational dynamics of twisting particles in large complex systems from the X-ray scattering patterns observed in highly sophisticated X-ray photon correlation spectroscopy (XPCS) experiments.

    1
    Schematic illustration of the XPCS experiments. The translation and rotation of the particles within the scattering volume leads to variation of the speckle patterns shown on the right. (While the grainy, noise-like texture makes these images appear visually similar, the MTECS algorithm is able to detect and analyze tiny variations between patterns.)

    These experiments — designed to study the properties of suspensions and solutions of colloids, macromolecules and polymers — have been established as key scientific drivers to many of the ongoing coherent light source upgrades occurring within the U.S. Department of Energy (DOE). The new mathematical methods, developed by the CAMERA team of Zixi Hu, Jeffrey Donatelli, and James Sethian, have the potential to reveal far more information about the function and properties of complex materials than was previously possible.

    Particles in a suspension undergo Brownian motion, jiggling around as they move (translate) and spin (rotate). The sizes of these random fluctuations depend on the shape and structure of the materials and contain information about dynamics, with applications across molecular biology, drug discovery, and materials science.

    XPCS works by focusing a coherent beam of X-rays to capture light scattered off of particles in suspension. A detector picks up the resulting speckle patterns, which contain several tiny fluctuations in the signal that encode detailed information about the dynamics of the observed system. To capitalize on this capability, the upcoming coherent light source upgrades at Berkeley Lab’s Advanced Light Source (ALS), Argonne’s Advanced Photon Source (APS), and SLAC’s Linac Coherent Light Source are all planning some of the world’s most advanced XPCS experiments, taking advantage of the unprecedented coherence and brightness.

    But once you collect the data from all these images, how do you get any useful information out of them? A workhorse technique to extract dynamical information from XPCS is to compute what’s known as the temporal autocorrelation, which measures how the pixels in the speckle patterns change after a certain passage of time. The autocorrelation function stitches the still images together, just as an old-time movie comes to life as closely related postcard images fly by.

    Current algorithms have mainly been limited to extracting translational motions; think of a Pogo stick jumping from spot to spot. However, no previous algorithms were capable of extracting “rotational diffusion” information about how structures spin and rotate — information that is critical to understanding the function and dynamical properties of a physical system. Getting to this hidden information is a major challenge.
    Twisting the Light Away

    A breakthrough came when experts came together for a CAMERA workshop on XPCS in February 2019 to discuss critical emerging needs in the field. Extracting rotational diffusion was a key goal, and Hu, a UC Berkeley math graduate student; Donatelli, the CAMERA Lead for Mathematics; and Sethian, Professor of Mathematics at UC Berkeley and CAMERA Director, teamed up to tackle the problem head on.

    The result of their work is a powerful new mathematical and algorithmic approach to extract rotational information, now working in 2D and easily scalable to 3D. With remarkably few images (less than 4,000), the method can easily predict simulated rotational diffusion coefficients to within a few percent. Details of the algorithm were published August 18 in the PNAS.

    The key idea is to go beyond the standard autocorrelation function, instead seeking the extra information about rotation contained in angular-temporal cross-correlation functions, which compare how pixels change in both time and space. This is a major jump in mathematical complexity: simple data matrices turn into 4-way data tensors, and the theory relating the rotational information to these tensors involves advanced harmonic analysis, linear algebra, and tensor analysis. To relate the desired rotational information to the data, Hu developed a highly sophisticated mathematical model that describes how the angular-temporal correlations behave as a function of the rotational dynamics from this new complex set of equations.

    “There were lots of layered mysteries to unravel in order to build a good mathematical and algorithmic framework to solve the problem,” said Hu. “There was information related to both static structures and to dynamic properties, and these properties needed to be systematically exploited to build a consistent framework. Taken together, they present a wonderful opportunity to weave together many mathematical ideas. Getting this approach to pick up useful information out of what seems at first glance to be awfully noisy was great fun.”

    However, solving this set of equations to recover the rotational dynamics is challenging, as it consists of several layers of different types of mathematical problems that are difficult to solve all at once. To tackle this challenge, the team built on Donatelli’s earlier work on Multi-Tiered Iterative Projections (M-TIP), which is designed to solve complex inverse problems where the goal is to find the input that produces an observed output. The idea of M-TIP is to break a complex problem into subparts, using the best inversion/pseudoinversion you can for each subpart, and iterate through those subsolutions until they converge to a solution that solves all parts of the problem.

    Hu and his colleagues took these ideas and built a sister method, “Multi-Tiered Estimation for Correlation Spectroscopy (M-TECS),” solving the complex layered set of equations through systematic substeps.

    2
    Schematic illustration of the M-TECS algorithm for determining the rotational diffusion coefficient of a dynamical system from its XPCS cross-correlation data. M-TECS works by splitting up the inversion into subparts, each of which of efficient mathematical tricks for inverting/pseudoinverting, and then iterating over those subparts until convergence to the correct solution.

    “The powerful thing about the M-TECS approach is that it exploits the fact that the problem can be separated into high-dimensional linear parts and low-dimensional nonlinear and nonconvex parts, each of which have efficient solutions on their own, but they would turn into an exceedingly difficult optimization problem if they were instead to be solved for all at once,” said Donatelli.

    “This is what enables M-TECS to efficiently determine rotational dynamics from such a complex system of equations, whereas standard optimization approaches would run into trouble both in terms of convergence and computational cost.”

    Opening the Door to New Experiments

    “XPCS is a powerful technique that will feature prominently in the ALS upgrade. This work opens up a new dimension to XPCS, and will allow us to explore the dynamics of complex materials such as rotating molecules inside water channels,” said Alexander Hexemer, Program Lead for Computing at the ALS.

    Hu, who won UC Berkeley’s Bernard Friedman Prize for this work, has joined CAMERA — part of Berkeley Lab’s Computational Research Division — as its newest member. “This sort of mathematical and algorithmic co-design is the hallmark of good applied mathematics, in which new mathematics plays a pivotal role in solving practical problems at the forefront of scientific inquiry,” said Sethian.

    The CAMERA team is currently working with beamline scientists at the ALS and APS to design new XPCS experiments that can fully leverage the team’s mathematical and algorithmic approach to study new rotational dynamics properties from important materials. The team is also working on extending their mathematical and algorithmic framework work to recover more general types of dynamical properties from XPCS, as well as apply these methods to other correlation imaging technologies.

    This work is supported by CAMERA, which is jointly funded by the DOE Office of Science Advanced Scientific Computing Research (US) and the Office of Basic Energy Sciences, both within the Department of Energy’s (US) Office of Science.

    See the full article here .

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    Please help promote STEM in your local schools.

    Stem Education Coalition


    Bringing Science Solutions to the World

    In the world of science, Lawrence Berkeley National Laboratory (Berkeley Lab) (US) is synonymous with “excellence.” Thirteen Nobel prizes are associated with Berkeley Lab. Seventy Lab scientists are members of the National Academy of Sciences (NAS), one of the highest honors for a scientist in the United States. Thirteen of our scientists have won the National Medal of Science, our nation’s highest award for lifetime achievement in fields of scientific research. Eighteen of our engineers have been elected to the National Academy of Engineering, and three of our scientists have been elected into the Institute of Medicine. In addition, Berkeley Lab has trained thousands of university science and engineering students who are advancing technological innovations across the nation and around the world.

    Berkeley Lab is a member of the national laboratory system supported by the U.S. Department of Energy through its Office of Science. It is managed by the University of California (US) and is charged with conducting unclassified research across a wide range of scientific disciplines. Located on a 202-acre site in the hills above the UC Berkeley campus that offers spectacular views of the San Francisco Bay, Berkeley Lab employs approximately 3,232 scientists, engineers and support staff. The Lab’s total costs for FY 2014 were $785 million. A recent study estimates the Laboratory’s overall economic impact through direct, indirect and induced spending on the nine counties that make up the San Francisco Bay Area to be nearly $700 million annually. The Lab was also responsible for creating 5,600 jobs locally and 12,000 nationally. The overall economic impact on the national economy is estimated at $1.6 billion a year. Technologies developed at Berkeley Lab have generated billions of dollars in revenues, and thousands of jobs. Savings as a result of Berkeley Lab developments in lighting and windows, and other energy-efficient technologies, have also been in the billions of dollars.

    Berkeley Lab was founded in 1931 by Ernest Orlando Lawrence, a University of California-Berkeley (US) physicist who won the 1939 Nobel Prize in physics for his invention of the cyclotron, a circular particle accelerator that opened the door to high-energy physics. It was Lawrence’s belief that scientific research is best done through teams of individuals with different fields of expertise, working together. His teamwork concept is a Berkeley Lab legacy that continues today.

    History

    1931–1941

    The laboratory was founded on August 26, 1931, by Ernest Lawrence, as the Radiation Laboratory of the University of California, Berkeley, associated with the Physics Department. It centered physics research around his new instrument, the cyclotron, a type of particle accelerator for which he was awarded the Nobel Prize in Physics in 1939.

    LBNL 88 inch cyclotron.


    Throughout the 1930s, Lawrence pushed to create larger and larger machines for physics research, courting private philanthropists for funding. He was the first to develop a large team to build big projects to make discoveries in basic research. Eventually these machines grew too large to be held on the university grounds, and in 1940 the lab moved to its current site atop the hill above campus. Part of the team put together during this period includes two other young scientists who went on to establish large laboratories; J. Robert Oppenheimer founded DOE’s Los Alamos Laboratory (US), and Robert Wilson founded Fermi National Accelerator Laboratory(US).

    1942–1950

    Leslie Groves visited Lawrence’s Radiation Laboratory in late 1942 as he was organizing the Manhattan Project, meeting J. Robert Oppenheimer for the first time. Oppenheimer was tasked with organizing the nuclear bomb development effort and founded today’s Los Alamos National Laboratory to help keep the work secret. At the RadLab, Lawrence and his colleagues developed the technique of electromagnetic enrichment of uranium using their experience with cyclotrons. The “calutrons” (named after the University) became the basic unit of the massive Y-12 facility in Oak Ridge, Tennessee. Lawrence’s lab helped contribute to what have been judged to be the three most valuable technology developments of the war (the atomic bomb, proximity fuse, and radar). The cyclotron, whose construction was stalled during the war, was finished in November 1946. The Manhattan Project shut down two months later.

    1951–2018

    After the war, the Radiation Laboratory became one of the first laboratories to be incorporated into the Atomic Energy Commission (AEC) (now Department of Energy (US). The most highly classified work remained at Los Alamos, but the RadLab remained involved. Edward Teller suggested setting up a second lab similar to Los Alamos to compete with their designs. This led to the creation of an offshoot of the RadLab (now the Lawrence Livermore National Laboratory (US)) in 1952. Some of the RadLab’s work was transferred to the new lab, but some classified research continued at Berkeley Lab until the 1970s, when it became a laboratory dedicated only to unclassified scientific research.

    Shortly after the death of Lawrence in August 1958, the UC Radiation Laboratory (both branches) was renamed the Lawrence Radiation Laboratory. The Berkeley location became the Lawrence Berkeley Laboratory in 1971, although many continued to call it the RadLab. Gradually, another shortened form came into common usage, LBNL. Its formal name was amended to Ernest Orlando Lawrence Berkeley National Laboratory in 1995, when “National” was added to the names of all DOE labs. “Ernest Orlando” was later dropped to shorten the name. Today, the lab is commonly referred to as “Berkeley Lab”.

    The Alvarez Physics Memos are a set of informal working papers of the large group of physicists, engineers, computer programmers, and technicians led by Luis W. Alvarez from the early 1950s until his death in 1988. Over 1700 memos are available on-line, hosted by the Laboratory.

    The lab remains owned by the Department of Energy (US), with management from the University of California (US). Companies such as Intel were funding the lab’s research into computing chips.

    Science mission

    From the 1950s through the present, Berkeley Lab has maintained its status as a major international center for physics research, and has also diversified its research program into almost every realm of scientific investigation. Its mission is to solve the most pressing and profound scientific problems facing humanity, conduct basic research for a secure energy future, understand living systems to improve the environment, health, and energy supply, understand matter and energy in the universe, build and safely operate leading scientific facilities for the nation, and train the next generation of scientists and engineers.

    The Laboratory’s 20 scientific divisions are organized within six areas of research: Computing Sciences; Physical Sciences; Earth and Environmental Sciences; Biosciences; Energy Sciences; and Energy Technologies. Berkeley Lab has six main science thrusts: advancing integrated fundamental energy science; integrative biological and environmental system science; advanced computing for science impact; discovering the fundamental properties of matter and energy; accelerators for the future; and developing energy technology innovations for a sustainable future. It was Lawrence’s belief that scientific research is best done through teams of individuals with different fields of expertise, working together. His teamwork concept is a Berkeley Lab tradition that continues today.

    Berkeley Lab operates five major National User Facilities for the DOE Office of Science (US):

    The Advanced Light Source (ALS) is a synchrotron light source with 41 beam lines providing ultraviolet, soft x-ray, and hard x-ray light to scientific experiments.

    LBNL/ALS


    The ALS is one of the world’s brightest sources of soft x-rays, which are used to characterize the electronic structure of matter and to reveal microscopic structures with elemental and chemical specificity. About 2,500 scientist-users carry out research at ALS every year. Berkeley Lab is proposing an upgrade of ALS which would increase the coherent flux of soft x-rays by two-three orders of magnitude.

    The DOE Joint Genome Institute (US) supports genomic research in support of the DOE missions in alternative energy, global carbon cycling, and environmental management. The JGI’s partner laboratories are Berkeley Lab, DOE’s Lawrence Livermore National Laboratory (US), DOE’s Oak Ridge National Laboratory (US)(ORNL), DOE’s Pacific Northwest National Laboratory (US) (PNNL), and the HudsonAlpha Institute for Biotechnology (US). The JGI’s central role is the development of a diversity of large-scale experimental and computational capabilities to link sequence to biological insights relevant to energy and environmental research. Approximately 1,200 scientist-users take advantage of JGI’s capabilities for their research every year.

    The LBNL Molecular Foundry (US) [above] is a multidisciplinary nanoscience research facility. Its seven research facilities focus on Imaging and Manipulation of Nanostructures; Nanofabrication; Theory of Nanostructured Materials; Inorganic Nanostructures; Biological Nanostructures; Organic and Macromolecular Synthesis; and Electron Microscopy. Approximately 700 scientist-users make use of these facilities in their research every year.

    The DOE’s NERSC National Energy Research Scientific Computing Center (US) is the scientific computing facility that provides large-scale computing for the DOE’s unclassified research programs. Its current systems provide over 3 billion computational hours annually. NERSC supports 6,000 scientific users from universities, national laboratories, and industry.

    DOE’s NERSC National Energy Research Scientific Computing Center(US) at Lawrence Berkeley National Laboratory

    The Genepool system is a cluster dedicated to the DOE Joint Genome Institute’s computing needs. Denovo is a smaller test system for Genepool that is primarily used by NERSC staff to test new system configurations and software.

    PDSF is a networked distributed computing cluster designed primarily to meet the detector simulation and data analysis requirements of physics, astrophysics and nuclear science collaborations.

    NERSC is a DOE Office of Science User Facility.

    The DOE’s Energy Science Network (US) is a high-speed network infrastructure optimized for very large scientific data flows. ESNet provides connectivity for all major DOE sites and facilities, and the network transports roughly 35 petabytes of traffic each month.

    Berkeley Lab is the lead partner in the DOE’s Joint Bioenergy Institute (US) (JBEI), located in Emeryville, California. Other partners are the DOE’s Sandia National Laboratory (US), the University of California (UC) campuses of Berkeley and Davis, the Carnegie Institution for Science (US), and DOE’s Lawrence Livermore National Laboratory (US) (LLNL). JBEI’s primary scientific mission is to advance the development of the next generation of biofuels – liquid fuels derived from the solar energy stored in plant biomass. JBEI is one of three new U.S. Department of Energy (DOE) Bioenergy Research Centers (BRCs).

    Berkeley Lab has a major role in two DOE Energy Innovation Hubs. The mission of the Joint Center for Artificial Photosynthesis (JCAP) is to find a cost-effective method to produce fuels using only sunlight, water, and carbon dioxide. The lead institution for JCAP is the California Institute of Technology (US) and Berkeley Lab is the second institutional center. The mission of the Joint Center for Energy Storage Research (JCESR) is to create next-generation battery technologies that will transform transportation and the electricity grid. DOE’s Argonne National Laboratory (US) leads JCESR and Berkeley Lab is a major partner.

     
  • richardmitnick 12:25 pm on August 20, 2021 Permalink | Reply
    Tags: "How Big Data Carried Graph Theory Into New Dimensions", , Hypergraph, Markov chain, Mathematics, New kinds of network models that can find complex structures and signals in the noise of big data., , Simplicial complexes, Tensors,   

    From Quanta Magazine (US) : “How Big Data Carried Graph Theory Into New Dimensions” 

    From Quanta Magazine (US)

    August 19, 2021
    Stephen Ornes

    1
    Mike Hughes for Quanta Magazine.

    The mathematical language for talking about connections, which usually depends on networks — vertices (dots) and edges (lines connecting them) — has been an invaluable way to model real-world phenomena since at least the 18th century. But a few decades ago, the emergence of giant data sets forced researchers to expand their toolboxes and, at the same time, gave them sprawling sandboxes in which to apply new mathematical insights. Since then, said Josh Grochow, a computer scientist at the University of Colorado-Boulder (US), there’s been an exciting period of rapid growth as researchers have developed new kinds of network models that can find complex structures and signals in the noise of big data.

    Grochow is among a growing chorus of researchers who point out that when it comes to finding connections in big data, graph theory has its limits. A graph represents every relationship as a dyad, or pairwise interaction. However, many complex systems can’t be represented by binary connections alone. Recent progress in the field shows how to move forward.

    Consider trying to forge a network model of parenting. Clearly, each parent has a connection to a child, but the parenting relationship isn’t just the sum of the two links, as graph theory might model it. The same goes for trying to model a phenomenon like peer pressure.

    “There are many intuitive models. The peer pressure effect on social dynamics is only captured if you already have groups in your data,” said Leonie Neuhäuser of RWTH AACHEN UNIVERSITY [Rheinisch-Westfaelische Technische Hochschule (DE). But binary networks don’t capture group influences.

    Mathematicians and computer scientists use the term “higher-order interactions” to describe these complex ways that group dynamics, rather than binary links, can influence individual behaviors. These mathematical phenomena appear in everything from entanglement interactions in quantum mechanics to the trajectory of a disease spreading through a population. If a pharmacologist wanted to model drug interactions [npj Systems Biology and Applications], for example, graph theory might show how two drugs respond to each other — but what about three? Or four?

    While the tools for exploring these interactions are not new, it’s only in recent years that high-dimensional data sets have become an engine for discovery, giving mathematicians and network theorists new ideas. These efforts have yielded interesting results about the limits of graphs and the possibilities of scaling up.

    “Now we know that the network is just the shadow of the thing,” Grochow said. If a data set has a complex underlying structure, then modeling it as a graph may reveal only a limited projection of the whole story.

    “We’ve realized that the data structures we’ve used to study things, from a mathematical perspective, aren’t quite fitting what we’re seeing in the data,” said the mathematician Emilie Purvine of the DOE’s Pacific Northwest National Laboratory (US).

    Which is why mathematicians, computer scientists and other researchers are increasingly focusing on ways to generalize graph theory — in its many guises — to explore higher-order phenomena. The last few years have brought a torrent of proposed ways to characterize these interactions, and to mathematically verify them in high-dimensional data sets.

    For Purvine, the mathematical exploration of higher-order interactions is like the mapping of new dimensions. “Think about a graph as a foundation on a two-dimensional plot of land,” she said. The three-dimensional buildings that can go on top could vary significantly. “When you’re down at ground level, they look the same, but what you construct on top is different.”

    Enter the Hypergraph

    The search for those higher-dimensional structures is where the math turns especially murky — and interesting. The higher-order analogue of a graph, for example, is called a hypergraph, and instead of edges, it has “hyperedges.” These can connect multiple nodes, which means it can represent multi-way (or multilinear) relationships. Instead of a line, a hyperedge might be seen as a surface, like a tarp staked in three or more places.

    Which is fine, but there’s still a lot we don’t know about how these structures relate to their conventional counterparts. Mathematicians are currently learning which rules of graph theory also apply for higher-order interactions, suggesting new areas of exploration.

    To illustrate the kinds of relationship that a hypergraph can tease out of a big data set — and an ordinary graph can’t — Purvine points to a simple example close to home, the world of scientific publication. Imagine two data sets, each containing papers co-authored by up to three mathematicians; for simplicity, let’s name them A, B and C. One data set contains six papers, with two papers by each of the three distinct pairs (AB, AC and BC). The other contains only two papers total, each co-authored by all three mathematicians (ABC).

    A graph representation of co-authorship, taken from either data set, might look like a triangle, showing that each mathematician (three nodes) had collaborated with the other two (three links). If your only question was who had collaborated with whom, then you wouldn’t need a hypergraph, Purvine said

    But if you did have a hypergraph, you could also answer questions about less obvious structures. A hypergraph of the first set (with six papers), for example, could include hyperedges showing that each mathematician contributed to four papers. A comparison of hypergraphs from the two sets would show that the papers’ authors differed in the first set but was the same in the second.

    Hypergraphs in the Wild

    Such higher-order methods have already proved useful in applied research, such as when ecologists showed how the reintroduction of wolves to Yellowstone National Park in the 1990s triggered changes in biodiversity and in the structure of the food chain. And in one recent paper, Purvine and her colleagues analyzed a database of biological responses to viral infections, using hypergraphs to identify the most critical genes involved. They also showed how those interactions would have been missed by the usual pairwise analysis afforded by graph theory.

    “That’s the kind of power we’re seeing from hypergraphs, to go above and beyond graphs,” said Purvine.

    However, generalizing from graphs to hypergraphs quickly gets complicated. One way to illustrate this is to consider the canonical cut problem from graph theory, which asks: Given two distinct nodes on a graph, what’s the minimum number of edges you can cut to completely sever all connections between the two? Many algorithms can readily find the optimal number of cuts for a given graph.

    But what about cutting a hypergraph? “There are lots of ways of generalizing this notion of a cut to a hypergraph,” said Austin Benson, a mathematician at Cornell University (US). But there’s no one clear solution, he said, because a hyperedge could be severed various ways, creating new groups of nodes.

    Together with two colleagues, Benson recently tried to formalize all the different ways of splitting up a hypergraph. What they found hinted at a variety of computational complexities: For some situations, the problem was readily solved in polynomial time, which basically means a computer could crunch through solutions in a reasonable time. But for others, the problem was basically unsolvable — it was impossible to know for certain whether a solution existed at all.

    “There are still many open questions there,” Benson said. “Some of these impossibility results are interesting because you can’t possibly reduce them to graphs. And on the theory side, if you haven’t reduced it to something you could have found with a graph, it’s showing you that there is something new there.”

    The Mathematical Sandwich

    But the hypergraph isn’t the only way to explore higher-order interactions. Topology — the mathematical study of geometric properties that don’t change when you stretch, compress or otherwise transform objects — offers a more visual approach. When a topologist studies a network, they look for shapes and surfaces and dimensions. They might note that the edge connecting two nodes is one-dimensional and ask about the properties of one-dimensional objects in different networks. Or they might see the two-dimensional triangular surface formed by connecting three nodes and ask similar questions.

    Topologists call these structures simplicial complexes [European Journal of Physics]. These are, effectively, hypergraphs viewed through the framework of topology. Neural networks, which fall into the general category of machine learning, offer a telling example. They’re driven by algorithms designed to mimic how our brains’ neurons process information. Graph neural networks (GNNs), which model connections between things as pairwise connections, excel at inferring data that’s missing from large data sets, but as in other applications, they could miss interactions that only arise from groups of three or more. In recent years, computer scientists have developed simplicial neural networks, which use higher-order complexes to generalize the approach of GNNs to find these effects.

    Simplicial complexes connect topology to graph theory, and, like hypergraphs, they raise compelling mathematical questions that will drive future investigations. For example, in topology, special kinds of subsets of simplicial complexes are also themselves simplicial complexes and therefore have the same properties. If the same held true for a hypergraph, the subsets would include all the hyperedges within — including all the embedded two-way edges.

    But that’s not always the case. “What we’re seeing now is that data falls into this middle ground where not every hyperedge, not every complex interaction, is the same size as every other one,” Purvine said. “You can have a three-way interaction, but not the pairwise interactions.” Big data sets have shown clearly that the group influence often far outstrips the influence of an individual, whether in biological signaling networks or in social behaviors like peer pressure.

    Purvine describes data as filling the middle of a kind of mathematical sandwich, bound on top by these ideas from topology, and underneath by the limitations of graphs. Network theorists are now challenged to find the new rules for higher-order interactions. And for mathematicians, she said, “there’s room to play.”

    Random Walks and Matrices

    That sense of creative “play” extends to other tools as well. There are all sorts of beautiful connections between graphs and other tools for describing data, said Benson. “But as soon as you move to the higher-order setting, these connections are harder to come by.”

    That’s especially clear when you try to consider a higher-dimensional version of a Markov chain, he said. A Markov chain describes a multistage process in which the next stage depends only on an element’s current position; researchers have used Markov models to describe how things like information, energy and even money flow through a system. Perhaps the best-known example of a Markov chain is a random walk, which describes a path where each step is determined randomly from the one before it. A random walk is also a specific graph: Any walk along a graph can be shown as a sequence moving from node to node along links.

    But how to scale up something as simple as a walk? Researchers turn to higher-order Markov chains, which instead of depending only on current position can consider many of the previous states. This approach proved useful for modeling systems like web browsing behavior and airport traffic flows. Benson has ideas for other ways to extend it: He and his colleagues recently described [SIAM Review] a new model for stochastic, or random, processes that combines higher-order Markov chains with another tool called tensors. They tested it against a data set of taxi rides in New York City to see how well it could predict trajectories. The results were mixed: Their model predicted the movement of cabs better than a usual Markov chain, but neither model was very reliable.

    Tensors themselves represent yet another tool for studying higher-order interactions that has come into its own in recent years. To understand tensors, first think of matrices, which organize data into an array of rows and columns. Now imagine matrices made of matrices, or matrices that have not only rows and columns, but also depth or other dimensions of data. These are tensors. If every matrix corresponded to a musical duet, then tensors would include all possible configurations of instruments.

    Tensors are nothing new to physicists, who have long used them to describe, for example, the different possible quantum states of a particle, but network theorists adopted this tool to expand on the power of matrices in high-dimensional data sets. And mathematicians are using them to crack open new classes of problems. Grochow uses tensors to study the isomorphism problem, which essentially asks how you know whether two objects are, in some way, the same. His recent work with Youming Qiao has produced a new way to identify complex problems that might be difficult or impossible to solve.

    How to Hypergraph Responsibly

    Benson’s inconclusive taxi model raises a pervasive question: When do researchers actually need tools like hypergraphs? In many cases, under the right conditions, a hypergraph will deliver the exact same type of predictions and analyses as a graph. “If something is already encapsulated in the network, is it really necessary to model the system [as higher-order]?” asked Michael Schaub of RWTH Aachen University.

    It depends on the data set, he said. “A graph is a good abstraction for a social network, but social networks are so much more. With higher-order systems, there are more ways to model.” Graph theory may show how individuals are connected, for example, but not capture the ways in which clusters of friends on social media influence each other’s behavior.

    The same higher-order interactions won’t emerge in every data set, so new theories are, curiously, driven by the data — which challenges the underlying logical sense that drew Purvine to the field in the first place. “What I love about math is that it’s based in logic and if you follow the right direction, you get to the right answer. But sometimes, when you’re defining whole new areas of math, there’s this subjectivity of what is the right way of doing it,” she says. “And if you don’t recognize that there are multiple ways of doing it, you can maybe drive the community in the wrong direction.”

    Ultimately, Grochow said, these tools represent a kind of freedom, not just allowing researchers to better understand their data, but allowing mathematicians and computer scientists to explore new worlds of possibilities. “There’s endless stuff to explore. It’s interesting and beautiful, and a source of a lot of great questions.”

    See the full article here .


    five-ways-keep-your-child-safe-school-shootings

    Please help promote STEM in your local schools.

    Stem Education Coalition

    Formerly known as Simons Science News, Quanta Magazine (US) is an editorially independent online publication launched by the Simons Foundation to enhance public understanding of science. Why Quanta? Albert Einstein called photons “quanta of light.” Our goal is to “illuminate science.” At Quanta Magazine, scientific accuracy is every bit as important as telling a good story. All of our articles are meticulously researched, reported, edited, copy-edited and fact-checked.

     
  • richardmitnick 10:56 pm on July 26, 2021 Permalink | Reply
    Tags: "SURP Student Spotlight- Alicia Savelli", , , , , , Mathematics, ,   

    From Dunlap Institute for Astronomy and Astrophysics (CA) : “SURP Student Spotlight- Alicia Savelli” 

    From Dunlap Institute for Astronomy and Astrophysics (CA)

    At

    University of Toronto (CA)

    7.27.21

    1
    Alicia is thrilled to be part of the SURP program, studying Milky Way-like galaxies in simulations alongside Dr. Ted Mackereth and Dr. Josh Speagle. Having concurrently completed a B.Sc. in Mathematics with a minor in Physics and a B.Ed. at Brock University, Alicia is now upgrading her physics minor to a major and is heading into her final year of undergraduate studies. She is originally from Burlington, Ontario and now lives in the Niagara region.

    What made you decide to participate in SURP?

    I have always wanted to spend my life studying math and science, and SURP has given me the invaluable opportunity to be an active member of the scientific community through new and exciting original research. SURP also holds special importance to me because, although Brock University (CA) Physics has been wonderful to me, unfortunately the university does not yet have an astronomy & astrophysics program. I am very passionate about astrophysics and SURP has been an amazing introduction into this world!

    What is your favourite thing about SURP?

    It is difficult to choose only one! I have loved that every day has been about constant learning – whether the subject is our Milky Way Analogues, astronomy as a whole, coding, or other professional skills – in an environment full of people with the same interests as me. I am so grateful to be immersed in a group of such kind, enthusiastic, and supportive colleagues who encourage my love of learning, especially my supervisors Ted and Josh who consistently go out of their way to enhance my skills and understanding. SURP has allowed me so much growth academically, professionally, and personally.

    Can you tell us about your research project?

    Our research looks at galaxies from the EAGLE suite of cosmological simulations and their properties as they form and evolve over time and space. We select “Milky Way Analogues” from the simulations based on observed properties of the Milky Way, and examine their likeness with respect both to the remaining galaxies in the simulation and to our observed values for the Milky Way. Through our research, we hope to understand what makes a galaxy “typical” and to refine our definition of “Milky-Way-ness”.

    Can you explain how SURP has perhaps been different from your undergrad work?

    My undergraduate work has been helpful in giving me a thorough background in math and physics that I can now apply to my own research in the SURP program. Most of my undergrad courses focused mainly on developing foundational skills and knowledge regarding a wide range of topics, but SURP has allowed me the opportunity for more engaged, more involved, and more directed learning about a subject that I am deeply interested in and that is currently relatively unexplored thus far. SURP has been an incredible supplement to my undergraduate work.

    What are your plans for the future?

    After completing my undergraduate studies, my plan is to start grad school in pursuit of a PhD. My ultimate career goal is to become a professor of astrophysics. Another passion of mine is teaching, and I have even taken some time off between degrees to teach secondary school math and science. Becoming a professor would ideally allow me to exercise my love for astrophysics both through research and teaching.

    See the full article here .


    five-ways-keep-your-child-safe-school-shootings

    Please help promote STEM in your local schools.


    Stem Education Coalition

    Dunlap Institute campus

    The Dunlap Institute for Astronomy & Astrophysics (CA) at University of Toronto (CA) is an endowed research institute with nearly 70 faculty, postdocs, students and staff, dedicated to innovative technology, ground-breaking research, world-class training, and public engagement. The research themes of its faculty and Dunlap Fellows span the Universe and include: optical, infrared and radio instrumentation; Dark Energy; large-scale structure; the Cosmic Microwave Background; the interstellar medium; galaxy evolution; cosmic magnetism; and time-domain science.

    The Dunlap Institute (CA), University of Toronto Department of Astronomy & Astrophysics (CA), Canadian Institute for Theoretical Astrophysics (CA), and Centre for Planetary Sciences (CA) comprise the leading centre for astronomical research in Canada, at the leading research university in the country, the University of Toronto (CA).

    The Dunlap Institute (CA) is committed to making its science, training and public outreach activities productive and enjoyable for everyone, regardless of gender, sexual orientation, disability, physical appearance, body size, race, nationality or religion.

    Our work is greatly enhanced through collaborations with the Department of Astronomy & Astrophysics (CA), Canadian Institute for Theoretical Astrophysics (CA), David Dunlap Observatory (CA), Ontario Science Centre (CA), Royal Astronomical Society of Canada (CA), the Toronto Public Library (CA), and many other partners.

    NIROSETI team from left to right Rem Stone UCO Lick Observatory Dan Werthimer, UC Berkeley; Jérôme Maire, U Toronto; Shelley Wright, UCSD; Patrick Dorval, U Toronto; Richard Treffers, Starman Systems. (Image by Laurie Hatch).

    The University of Toronto(CA) is a public research university in Toronto, Ontario, Canada, located on the grounds that surround Queen’s Park. It was founded by royal charter in 1827 as King’s College, the oldest university in the province of Ontario.

    Originally controlled by the Church of England, the university assumed its present name in 1850 upon becoming a secular institution.

    As a collegiate university, it comprises eleven colleges each with substantial autonomy on financial and institutional affairs and significant differences in character and history. The university also operates two satellite campuses located in Scarborough and Mississauga.

    University of Toronto has evolved into Canada’s leading institution of learning, discovery and knowledge creation. We are proud to be one of the world’s top research-intensive universities, driven to invent and innovate.

    Our students have the opportunity to learn from and work with preeminent thought leaders through our multidisciplinary network of teaching and research faculty, alumni and partners.

    The ideas, innovations and actions of more than 560,000 graduates continue to have a positive impact on the world.

    Academically, the University of Toronto is noted for movements and curricula in literary criticism and communication theory, known collectively as the Toronto School.

    The university was the birthplace of insulin and stem cell research, and was the site of the first electron microscope in North America; the identification of the first black hole Cygnus X-1; multi-touch technology, and the development of the theory of NP-completeness.

    The university was one of several universities involved in early research of deep learning. It receives the most annual scientific research funding of any Canadian university and is one of two members of the Association of American Universities (US) outside the United States, the other being McGill(CA).

    The Varsity Blues are the athletic teams that represent the university in intercollegiate league matches, with ties to gridiron football, rowing and ice hockey. The earliest recorded instance of gridiron football occurred at University of Toronto’s University College in November 1861.

    The university’s Hart House is an early example of the North American student centre, simultaneously serving cultural, intellectual, and recreational interests within its large Gothic-revival complex.

    The University of Toronto has educated three Governors General of Canada, four Prime Ministers of Canada, three foreign leaders, and fourteen Justices of the Supreme Court. As of March 2019, ten Nobel laureates, five Turing Award winners, 94 Rhodes Scholars, and one Fields Medalist have been affiliated with the university.

    Early history

    The founding of a colonial college had long been the desire of John Graves Simcoe, the first Lieutenant-Governor of Upper Canada and founder of York, the colonial capital. As an University of Oxford (UK)-educated military commander who had fought in the American Revolutionary War, Simcoe believed a college was needed to counter the spread of republicanism from the United States. The Upper Canada Executive Committee recommended in 1798 that a college be established in York.

    On March 15, 1827, a royal charter was formally issued by King George IV, proclaiming “from this time one College, with the style and privileges of a University … for the education of youth in the principles of the Christian Religion, and for their instruction in the various branches of Science and Literature … to continue for ever, to be called King’s College.” The granting of the charter was largely the result of intense lobbying by John Strachan, the influential Anglican Bishop of Toronto who took office as the college’s first president. The original three-storey Greek Revival school building was built on the present site of Queen’s Park.

    Under Strachan’s stewardship, King’s College was a religious institution closely aligned with the Church of England and the British colonial elite, known as the Family Compact. Reformist politicians opposed the clergy’s control over colonial institutions and fought to have the college secularized. In 1849, after a lengthy and heated debate, the newly elected responsible government of the Province of Canada voted to rename King’s College as the University of Toronto and severed the school’s ties with the church. Having anticipated this decision, the enraged Strachan had resigned a year earlier to open Trinity College as a private Anglican seminary. University College was created as the nondenominational teaching branch of the University of Toronto. During the American Civil War the threat of Union blockade on British North America prompted the creation of the University Rifle Corps which saw battle in resisting the Fenian raids on the Niagara border in 1866. The Corps was part of the Reserve Militia lead by Professor Henry Croft.

    Established in 1878, the School of Practical Science was the precursor to the Faculty of Applied Science and Engineering which has been nicknamed Skule since its earliest days. While the Faculty of Medicine opened in 1843 medical teaching was conducted by proprietary schools from 1853 until 1887 when the faculty absorbed the Toronto School of Medicine. Meanwhile the university continued to set examinations and confer medical degrees. The university opened the Faculty of Law in 1887, followed by the Faculty of Dentistry in 1888 when the Royal College of Dental Surgeons became an affiliate. Women were first admitted to the university in 1884.

    A devastating fire in 1890 gutted the interior of University College and destroyed 33,000 volumes from the library but the university restored the building and replenished its library within two years. Over the next two decades a collegiate system took shape as the university arranged federation with several ecclesiastical colleges including Strachan’s Trinity College in 1904. The university operated the Royal Conservatory of Music from 1896 to 1991 and the Royal Ontario Museum from 1912 to 1968; both still retain close ties with the university as independent institutions. The University of Toronto Press was founded in 1901 as Canada’s first academic publishing house. The Faculty of Forestry founded in 1907 with Bernhard Fernow as dean was Canada’s first university faculty devoted to forest science. In 1910, the Faculty of Education opened its laboratory school, the University of Toronto Schools.

    World wars and post-war years

    The First and Second World Wars curtailed some university activities as undergraduate and graduate men eagerly enlisted. Intercollegiate athletic competitions and the Hart House Debates were suspended although exhibition and interfaculty games were still held. The David Dunlap Observatory in Richmond Hill opened in 1935 followed by the University of Toronto Institute for Aerospace Studies in 1949. The university opened satellite campuses in Scarborough in 1964 and in Mississauga in 1967. The university’s former affiliated schools at the Ontario Agricultural College and Glendon Hall became fully independent of the University of Toronto and became part of University of Guelph (CA) in 1964 and York University (CA) in 1965 respectively. Beginning in the 1980s reductions in government funding prompted more rigorous fundraising efforts.

    Since 2000

    In 2000 Kin-Yip Chun was reinstated as a professor of the university after he launched an unsuccessful lawsuit against the university alleging racial discrimination. In 2017 a human rights application was filed against the University by one of its students for allegedly delaying the investigation of sexual assault and being dismissive of their concerns. In 2018 the university cleared one of its professors of allegations of discrimination and antisemitism in an internal investigation after a complaint was filed by one of its students.

    The University of Toronto was the first Canadian university to amass a financial endowment greater than c. $1 billion in 2007. On September 24, 2020 the university announced a $250 million gift to the Faculty of Medicine from businessman and philanthropist James C. Temerty- the largest single philanthropic donation in Canadian history. This broke the previous record for the school set in 2019 when Gerry Schwartz and Heather Reisman jointly donated $100 million for the creation of a 750,000-square foot innovation and artificial intelligence centre.

    Research

    Since 1926 the University of Toronto has been a member of the Association of American Universities (US) a consortium of the leading North American research universities. The university manages by far the largest annual research budget of any university in Canada with sponsored direct-cost expenditures of $878 million in 2010. In 2018 the University of Toronto was named the top research university in Canada by Research Infosource with a sponsored research income (external sources of funding) of $1,147.584 million in 2017. In the same year the university’s faculty averaged a sponsored research income of $428,200 while graduate students averaged a sponsored research income of $63,700. The federal government was the largest source of funding with grants from the Canadian Institutes of Health Research; the Natural Sciences and Engineering Research Council; and the Social Sciences and Humanities Research Council amounting to about one-third of the research budget. About eight percent of research funding came from corporations- mostly in the healthcare industry.

    The first practical electron microscope was built by the physics department in 1938. During World War II the university developed the G-suit- a life-saving garment worn by Allied fighter plane pilots later adopted for use by astronauts.Development of the infrared chemiluminescence technique improved analyses of energy behaviours in chemical reactions. In 1963 the asteroid 2104 Toronto was discovered in the David Dunlap Observatory (CA) in Richmond Hill and is named after the university. In 1972 studies on Cygnus X-1 led to the publication of the first observational evidence proving the existence of black holes. Toronto astronomers have also discovered the Uranian moons of Caliban and Sycorax; the dwarf galaxies of Andromeda I, II and III; and the supernova SN 1987A. A pioneer in computing technology the university designed and built UTEC- one of the world’s first operational computers- and later purchased Ferut- the second commercial computer after UNIVAC I. Multi-touch technology was developed at Toronto with applications ranging from handheld devices to collaboration walls. The AeroVelo Atlas which won the Igor I. Sikorsky Human Powered Helicopter Competition in 2013 was developed by the university’s team of students and graduates and was tested in Vaughan.

    The discovery of insulin at the University of Toronto in 1921 is considered among the most significant events in the history of medicine. The stem cell was discovered at the university in 1963 forming the basis for bone marrow transplantation and all subsequent research on adult and embryonic stem cells. This was the first of many findings at Toronto relating to stem cells including the identification of pancreatic and retinal stem cells. The cancer stem cell was first identified in 1997 by Toronto researchers who have since found stem cell associations in leukemia; brain tumors; and colorectal cancer. Medical inventions developed at Toronto include the glycaemic index; the infant cereal Pablum; the use of protective hypothermia in open heart surgery; and the first artificial cardiac pacemaker. The first successful single-lung transplant was performed at Toronto in 1981 followed by the first nerve transplant in 1988; and the first double-lung transplant in 1989. Researchers identified the maturation promoting factor that regulates cell division and discovered the T-cell receptor which triggers responses of the immune system. The university is credited with isolating the genes that cause Fanconi anemia; cystic fibrosis; and early-onset Alzheimer’s disease among numerous other diseases. Between 1914 and 1972 the university operated the Connaught Medical Research Laboratories- now part of the pharmaceutical corporation Sanofi-Aventis. Among the research conducted at the laboratory was the development of gel electrophoresis.

    The University of Toronto is the primary research presence that supports one of the world’s largest concentrations of biotechnology firms. More than 5,000 principal investigators reside within 2 kilometres (1.2 mi) from the university grounds in Toronto’s Discovery District conducting $1 billion of medical research annually. MaRS Discovery District is a research park that serves commercial enterprises and the university’s technology transfer ventures. In 2008, the university disclosed 159 inventions and had 114 active start-up companies. Its SciNet Consortium operates the most powerful supercomputer in Canada.

     
  • richardmitnick 12:13 pm on July 20, 2021 Permalink | Reply
    Tags: "A Video Tour of the Standard Model", , Mathematics, , , ,   

    From Quanta Magazine (US) via Symmetry: “A Video Tour of the Standard Model” 

    From Quanta Magazine

    via

    Symmetry Mag

    Symmetry

    July 16, 2021
    Kevin Hartnett

    1
    Standard Model of Particle Physics. Credit: Quanta Magazine.


    The Standard Model: The Most Successful Scientific Theory Ever.
    Video: The Standard Model of particle physics is the most successful scientific theory of all time. In this explainer, Cambridge University physicist David Tong recreates the model, piece by piece, to provide some intuition for how the fundamental building blocks of our universe fit together.
    Emily Buder/Quanta Magazine.
    Kristina Armitage and Rui Braz for Quanta Magazine.

    Recently, Quanta has explored the collaboration between physics and mathematics on one of the most important ideas in science: quantum field theory. The basic objects of a quantum field theory are quantum fields, which spread across the universe and, through their fluctuations, give rise to the most fundamental phenomena in the physical world. We’ve emphasized the unfinished business in both physics and mathematics — the ways in which physicists still don’t fully understand a theory they wield so effectively, and the grand rewards that await mathematicians if they can provide a full description of what quantum field theory actually is.

    This incompleteness, however, does not mean the work has been unsatisfying so far.

    For our final entry in this “Math Meets QFT” series, we’re exploring the most prominent quantum field theory of them all: the Standard Model. As the University of Cambridge (UK) physicist David Tong puts it in the accompanying video, it’s “the most successful scientific theory of all time” despite being saddled with a “rubbish name.”

    The Standard Model describes physics in the three spatial dimensions and one time dimension of our universe. It captures the interplay between a dozen quantum fields representing fundamental particles and a handful of additional fields representing forces. The Standard Model ties them all together into a single equation that scientists have confirmed countless times, often with astonishing accuracy. In the video, Professor Tong walks us through that equation term by term, introducing us to all the pieces of the theory and how they fit together. The Standard Model is complicated, but it is easier to work with than many other quantum field theories. That’s because sometimes the fields of the Standard Model interact with each other quite feebly, as writer Charlie Wood described in the second piece in our series.

    From Quanta Magazine : “Mathematicians Prove 2D Version of Quantum Gravity Really Works”

    The Standard Model has been a boon for physics, but it’s also had a bit of a hangover effect. It’s been extraordinarily effective at explaining experiments we can do here on Earth, but it can’t account for several major features of the wider universe, including the action of gravity at short distances and the presence of dark matter and dark energy. Physicists would like to move beyond the Standard Model to an even more encompassing physical theory. But, as the physicist Davide Gaiotto put it in the first piece in our series, the glow of the Standard Model is so strong that it’s hard to see beyond it.

    From Quanta Magazine : “The Mystery at the Heart of Physics That Only Math Can Solve”

    And that, maybe, is where math comes in. Mathematicians will have to develop a fresh perspective on quantum field theory if they want to understand it in a self-consistent and rigorous way. There’s reason to hope that this new vantage will resolve many of the biggest open questions in physics.

    The process of bringing QFT into math may take some time — maybe even centuries, as the physicist Nathan Seiberg speculated in the third piece in our series — but it’s also already well underway. By now, math and quantum field theory have indisputably met. It remains to be seen what happens as they really get to know each other.

    From Quanta Magazine : “Nathan Seiberg on How Math Might Complete the Ultimate Physics Theory”

    See the full article here .


    five-ways-keep-your-child-safe-school-shootings

    Please help promote STEM in your local schools.

    Stem Education Coalition

    Formerly known as Simons Science News, Quanta Magazine is an editorially independent online publication launched by the Simons Foundation to enhance public understanding of science. Why Quanta? Albert Einstein called photons “quanta of light.” Our goal is to “illuminate science.” At Quanta Magazine, scientific accuracy is every bit as important as telling a good story. All of our articles are meticulously researched, reported, edited, copy-edited and fact-checked.

     
  • richardmitnick 11:09 am on July 1, 2021 Permalink | Reply
    Tags: "The power of two", , , , , , , , Ellen Zhong, , , Mathematics, Software called cryoDRGN   

    From Massachusetts Institute of Technology (US) : “The power of two” 

    MIT News

    From Massachusetts Institute of Technology (US)

    June 30, 2021
    Saima Sidik | Department of Biology

    Graduate student Ellen Zhong helped biologists and mathematicians reach across departmental lines to address a longstanding problem in electron microscopy.

    1
    Ellen Zhong, a graduate student from the Computational and Systems Biology Program, is using a computational pattern-recognition tool called a neural network to study the shapes of molecular machines.
    Credit: Matthew Brown.

    MIT’s Hockfield Court is bordered on the west by the ultramodern Stata Center, with its reflective, silver alcoves that jut off at odd angles, and on the east by Building 68, which is a simple, window-lined, cement rectangle. At first glance, Bonnie Berger’s mathematics lab in the Stata Center and Joey Davis’s biology lab in Building 68 are as different as the buildings that house them. And yet, a recent collaboration between these two labs shows how their disciplines complement each other. The partnership started when Ellen Zhong, a graduate student from the Computational and Systems Biology (CSB) Program, decided to use a computational pattern-recognition tool called a neural network to study the shapes of molecular machines. Three years later, Zhong’s project is letting scientists see patterns that run beneath the surface of their data, and deepening their understanding of the molecules that shape life.

    Zhong’s work builds on a technique from the 1970s called cryo-electron microscopy (cryo-EM), which lets researchers take high-resolution images of frozen protein complexes. Over the past decade, better microscopes and cameras have led to a “resolution revolution” in cryo-EM that’s allowed scientists to see individual atoms within proteins. But, as good as these images are, they’re still only static snapshots. In reality, many of these molecular machines are constantly changing shape and composition as cells carry out their normal functions and adjust to new situations.

    Along with former Berger lab member Tristan Belper, Zhong devised software called cryoDRGN. The tool uses neural nets to combine hundreds of thousands of cryo-EM images, and shows scientists the full range of three-dimensional conformations that protein complexes can take, letting them reconstruct the proteins’ motion as they carry out cellular functions. Understanding the range of shapes that protein complexes can take helps scientists develop drugs that block viruses from entering cells, study how pests kill crops, and even design custom proteins that can cure disease. Covid-19 vaccines, for example, work partly because they include a mutated version of the virus’s spike protein that’s stuck in its active conformation, so vaccinated people produce antibodies that block the virus from entering human cells. Scientists needed to understand the variety of shapes that spike proteins can take in order to figure out how to force spike into its active conformation.

    Getting off the computer and into the lab

    Zhong’s interest in computational biology goes back to 2011 when, as a chemical engineering undergrad at the University of Virginia (US), she worked with Professor Michael Shirts to simulate how proteins fold and unfold. After college, Zhong took her skills to a company called D. E. Shaw Research, where, as a scientific programmer, she took a computational approach to studying how proteins interact with small-molecule drugs.

    “The research was very exciting,” Zhong says, “but all based on computer simulations. To really understand biological systems, you need to do experiments.”

    This goal of combining computation with experimentation motivated Zhong to join MIT’s CSB PhD program, where students often work with multiple supervisors to blend computational work with bench work. Zhong “rotated” in both the Davis and Berger labs, then decided to combine the Davis lab’s goal of understanding how protein complexes form with the Berger lab’s expertise in machine learning and algorithms. Davis was interested in building up the computational side of his lab, so he welcomed the opportunity to co-supervise a student with Berger, who has a long history of collaborating with biologists.

    Davis himself holds a dual bachelor’s degree in computer science and biological engineering, so he’s long believed in the power of combining complementary disciplines. “There are a lot of things you can learn about biology by looking in a microscope,” he says. “But as we start to ask more complicated questions about entire systems, we’re going to require computation to manage the high-dimensional data that come back.”


    Reconstructing Molecules in Motion.

    Before rotating in the Davis lab, Zhong had never performed bench work before — or even touched a pipette. She was fascinated to find how streamlined some very powerful molecular biology techniques can be. Still, Zhong realized that physical limitations mean that biology is much slower when it’s done at the bench instead of on a computer. “With computational research, you can automate experiments and run them super quickly, whereas in the wet lab, you only have two hands, so you can only do one experiment at a time,” she says.

    Zhong says that synergizing the two different cultures of the Davis and Berger labs is helping her become a well-rounded, adaptable scientist. Working around experimentalists in the Davis lab has shown her how much labor goes into experimental results, and also helped her to understand the hurdles that scientists face at the bench. In the Berger lab, she enjoys having coworkers who understand the challenges of computer programming.

    “The key challenge in collaborating across disciplines is understanding each other’s ‘languages,’” Berger says. “Students like Ellen are fortunate to be learning both biology and computing dialects simultaneously.”

    Bringing in the community

    Last spring revealed another reason for biologists to learn computational skills: these tools can be used anywhere there’s a computer and an internet connection. When the Covid-19 pandemic hit, Zhong’s colleagues in the Davis lab had to wind down their bench work for a few months, and many of them filled their time at home by using cryo-EM data that’s freely available online to help Zhong test her cryoDRGN software. The difficulty of understanding another discipline’s language quickly became apparent, and Zhong spent a lot of time teaching her colleagues to be programmers. Seeing the problems that nonprogrammers ran into when they used cryoDRGN was very informative, Zhong says, and helped her create a more user-friendly interface.

    Although the paper announcing cryoDRGN was just published in February, the tool created a stir as soon as Zhong posted her code online, many months prior. The cryoDRGN team thinks this is because leveraging knowledge from two disciplines let them visualize the full range of structures that protein complexes can have, and that’s something researchers have wanted to do for a long time. For example, the cryoDRGN team recently collaborated with researchers from Harvard and Washington universities to study locomotion of the single-celled organism Chlamydomonas reinhardtii. The mechanisms they uncovered could shed light on human health conditions, like male infertility, that arise when cells lose the ability to move. The team is also using cryoDRGN to study the structure of the SARS-CoV-2 spike protein, which could help scientists design treatments and vaccines to fight coronaviruses.

    Zhong, Berger, and Davis say they’re excited to continue using neural nets to improve cryo-EM analysis, and to extend their computational work to other aspects of biology. Davis cited mass spectrometry as “a ripe area to apply computation.” This technique can complement cryo-EM by showing researchers the identities of proteins, how many of them are bound together, and how cells have modified them.

    “Collaborations between disciplines are the future,” Berger says. “Researchers focused on a single discipline can take it only so far with existing techniques. Shining a different lens on the problem is how advances can be made.”

    Zhong says it’s not a bad way to spend a PhD, either. Asked what she’d say to incoming graduate students considering interdisciplinary projects, she says: “Definitely do it.”

    See the full article here .


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    Please help promote STEM in your local schools.

    Stem Education Coalition

    MIT Seal

    USPS “Forever” postage stamps celebrating Innovation at MIT.

    MIT Campus

    Massachusetts Institute of Technology (US) is a private land-grant research university in Cambridge, Massachusetts. The institute has an urban campus that extends more than a mile (1.6 km) alongside the Charles River. The institute also encompasses a number of major off-campus facilities such as the MIT Lincoln Laboratory, the Bates Center, and the Haystack Observatory, as well as affiliated laboratories such as the Broad and Whitehead Institutes.

    Founded in 1861 in response to the increasing industrialization of the United States, Massachusetts Institute of Technology (US) adopted a European polytechnic university model and stressed laboratory instruction in applied science and engineering. It has since played a key role in the development of many aspects of modern science, engineering, mathematics, and technology, and is widely known for its innovation and academic strength. It is frequently regarded as one of the most prestigious universities in the world.

    As of December 2020, 97 Nobel laureates, 26 Turing Award winners, and 8 Fields Medalists have been affiliated with MIT as alumni, faculty members, or researchers. In addition, 58 National Medal of Science recipients, 29 National Medals of Technology and Innovation recipients, 50 MacArthur Fellows, 80 Marshall Scholars, 3 Mitchell Scholars, 22 Schwarzman Scholars, 41 astronauts, and 16 Chief Scientists of the U.S. Air Force have been affiliated with Massachusetts Institute of Technology (US) . The university also has a strong entrepreneurial culture and MIT alumni have founded or co-founded many notable companies. Massachusetts Institute of Technology (US) is a member of the Association of American Universities (AAU).

    Foundation and vision

    In 1859, a proposal was submitted to the Massachusetts General Court to use newly filled lands in Back Bay, Boston for a “Conservatory of Art and Science”, but the proposal failed. A charter for the incorporation of the Massachusetts Institute of Technology, proposed by William Barton Rogers, was signed by John Albion Andrew, the governor of Massachusetts, on April 10, 1861.

    Rogers, a professor from the University of Virginia (US), wanted to establish an institution to address rapid scientific and technological advances. He did not wish to found a professional school, but a combination with elements of both professional and liberal education, proposing that:

    “The true and only practicable object of a polytechnic school is, as I conceive, the teaching, not of the minute details and manipulations of the arts, which can be done only in the workshop, but the inculcation of those scientific principles which form the basis and explanation of them, and along with this, a full and methodical review of all their leading processes and operations in connection with physical laws.”

    The Rogers Plan reflected the German research university model, emphasizing an independent faculty engaged in research, as well as instruction oriented around seminars and laboratories.

    Early developments

    Two days after Massachusetts Institute of Technology (US) was chartered, the first battle of the Civil War broke out. After a long delay through the war years, MIT’s first classes were held in the Mercantile Building in Boston in 1865. The new institute was founded as part of the Morrill Land-Grant Colleges Act to fund institutions “to promote the liberal and practical education of the industrial classes” and was a land-grant school. In 1863 under the same act, the Commonwealth of Massachusetts founded the Massachusetts Agricultural College, which developed as the University of Massachusetts Amherst (US)). In 1866, the proceeds from land sales went toward new buildings in the Back Bay.

    Massachusetts Institute of Technology (US) was informally called “Boston Tech”. The institute adopted the European polytechnic university model and emphasized laboratory instruction from an early date. Despite chronic financial problems, the institute saw growth in the last two decades of the 19th century under President Francis Amasa Walker. Programs in electrical, chemical, marine, and sanitary engineering were introduced, new buildings were built, and the size of the student body increased to more than one thousand.

    The curriculum drifted to a vocational emphasis, with less focus on theoretical science. The fledgling school still suffered from chronic financial shortages which diverted the attention of the MIT leadership. During these “Boston Tech” years, Massachusetts Institute of Technology (US) faculty and alumni rebuffed Harvard University (US) president (and former MIT faculty) Charles W. Eliot’s repeated attempts to merge MIT with Harvard College’s Lawrence Scientific School. There would be at least six attempts to absorb MIT into Harvard. In its cramped Back Bay location, MIT could not afford to expand its overcrowded facilities, driving a desperate search for a new campus and funding. Eventually, the MIT Corporation approved a formal agreement to merge with Harvard, over the vehement objections of MIT faculty, students, and alumni. However, a 1917 decision by the Massachusetts Supreme Judicial Court effectively put an end to the merger scheme.

    In 1916, the Massachusetts Institute of Technology (US) administration and the MIT charter crossed the Charles River on the ceremonial barge Bucentaur built for the occasion, to signify MIT’s move to a spacious new campus largely consisting of filled land on a one-mile-long (1.6 km) tract along the Cambridge side of the Charles River. The neoclassical “New Technology” campus was designed by William W. Bosworth and had been funded largely by anonymous donations from a mysterious “Mr. Smith”, starting in 1912. In January 1920, the donor was revealed to be the industrialist George Eastman of Rochester, New York, who had invented methods of film production and processing, and founded Eastman Kodak. Between 1912 and 1920, Eastman donated $20 million ($236.6 million in 2015 dollars) in cash and Kodak stock to MIT.

    Curricular reforms

    In the 1930s, President Karl Taylor Compton and Vice-President (effectively Provost) Vannevar Bush emphasized the importance of pure sciences like physics and chemistry and reduced the vocational practice required in shops and drafting studios. The Compton reforms “renewed confidence in the ability of the Institute to develop leadership in science as well as in engineering”. Unlike Ivy League schools, Massachusetts Institute of Technology (US) catered more to middle-class families, and depended more on tuition than on endowments or grants for its funding. The school was elected to the Association of American Universities (US)in 1934.

    Still, as late as 1949, the Lewis Committee lamented in its report on the state of education at Massachusetts Institute of Technology (US) that “the Institute is widely conceived as basically a vocational school”, a “partly unjustified” perception the committee sought to change. The report comprehensively reviewed the undergraduate curriculum, recommended offering a broader education, and warned against letting engineering and government-sponsored research detract from the sciences and humanities. The School of Humanities, Arts, and Social Sciences and the MIT Sloan School of Management were formed in 1950 to compete with the powerful Schools of Science and Engineering. Previously marginalized faculties in the areas of economics, management, political science, and linguistics emerged into cohesive and assertive departments by attracting respected professors and launching competitive graduate programs. The School of Humanities, Arts, and Social Sciences continued to develop under the successive terms of the more humanistically oriented presidents Howard W. Johnson and Jerome Wiesner between 1966 and 1980.

    Massachusetts Institute of Technology (US)‘s involvement in military science surged during World War II. In 1941, Vannevar Bush was appointed head of the federal Office of Scientific Research and Development and directed funding to only a select group of universities, including MIT. Engineers and scientists from across the country gathered at Massachusetts Institute of Technology (US)’s Radiation Laboratory, established in 1940 to assist the British military in developing microwave radar. The work done there significantly affected both the war and subsequent research in the area. Other defense projects included gyroscope-based and other complex control systems for gunsight, bombsight, and inertial navigation under Charles Stark Draper’s Instrumentation Laboratory; the development of a digital computer for flight simulations under Project Whirlwind; and high-speed and high-altitude photography under Harold Edgerton. By the end of the war, Massachusetts Institute of Technology (US) became the nation’s largest wartime R&D contractor (attracting some criticism of Bush), employing nearly 4000 in the Radiation Laboratory alone and receiving in excess of $100 million ($1.2 billion in 2015 dollars) before 1946. Work on defense projects continued even after then. Post-war government-sponsored research at MIT included SAGE and guidance systems for ballistic missiles and Project Apollo.

    These activities affected Massachusetts Institute of Technology (US) profoundly. A 1949 report noted the lack of “any great slackening in the pace of life at the Institute” to match the return to peacetime, remembering the “academic tranquility of the prewar years”, though acknowledging the significant contributions of military research to the increased emphasis on graduate education and rapid growth of personnel and facilities. The faculty doubled and the graduate student body quintupled during the terms of Karl Taylor Compton, president of Massachusetts Institute of Technology (US) between 1930 and 1948; James Rhyne Killian, president from 1948 to 1957; and Julius Adams Stratton, chancellor from 1952 to 1957, whose institution-building strategies shaped the expanding university. By the 1950s, Massachusetts Institute of Technology (US) no longer simply benefited the industries with which it had worked for three decades, and it had developed closer working relationships with new patrons, philanthropic foundations and the federal government.

    In late 1960s and early 1970s, student and faculty activists protested against the Vietnam War and Massachusetts Institute of Technology (US)’s defense research. In this period Massachusetts Institute of Technology (US)’s various departments were researching helicopters, smart bombs and counterinsurgency techniques for the war in Vietnam as well as guidance systems for nuclear missiles. The Union of Concerned Scientists was founded on March 4, 1969 during a meeting of faculty members and students seeking to shift the emphasis on military research toward environmental and social problems. Massachusetts Institute of Technology (US) ultimately divested itself from the Instrumentation Laboratory and moved all classified research off-campus to the MIT (US) Lincoln Laboratory facility in 1973 in response to the protests. The student body, faculty, and administration remained comparatively unpolarized during what was a tumultuous time for many other universities. Johnson was seen to be highly successful in leading his institution to “greater strength and unity” after these times of turmoil. However six Massachusetts Institute of Technology (US) students were sentenced to prison terms at this time and some former student leaders, such as Michael Albert and George Katsiaficas, are still indignant about MIT’s role in military research and its suppression of these protests. (Richard Leacock’s film, November Actions, records some of these tumultuous events.)

    In the 1980s, there was more controversy at Massachusetts Institute of Technology (US) over its involvement in SDI (space weaponry) and CBW (chemical and biological warfare) research. More recently, Massachusetts Institute of Technology (US)’s research for the military has included work on robots, drones and ‘battle suits’.

    Recent history

    Massachusetts Institute of Technology (US) has kept pace with and helped to advance the digital age. In addition to developing the predecessors to modern computing and networking technologies, students, staff, and faculty members at Project MAC, the Artificial Intelligence Laboratory, and the Tech Model Railroad Club wrote some of the earliest interactive computer video games like Spacewar! and created much of modern hacker slang and culture. Several major computer-related organizations have originated at MIT since the 1980s: Richard Stallman’s GNU Project and the subsequent Free Software Foundation were founded in the mid-1980s at the AI Lab; the MIT Media Lab was founded in 1985 by Nicholas Negroponte and Jerome Wiesner to promote research into novel uses of computer technology; the World Wide Web Consortium standards organization was founded at the Laboratory for Computer Science in 1994 by Tim Berners-Lee; the MIT OpenCourseWare project has made course materials for over 2,000 Massachusetts Institute of Technology (US) classes available online free of charge since 2002; and the One Laptop per Child initiative to expand computer education and connectivity to children worldwide was launched in 2005.

    Massachusetts Institute of Technology (US) was named a sea-grant college in 1976 to support its programs in oceanography and marine sciences and was named a space-grant college in 1989 to support its aeronautics and astronautics programs. Despite diminishing government financial support over the past quarter century, MIT launched several successful development campaigns to significantly expand the campus: new dormitories and athletics buildings on west campus; the Tang Center for Management Education; several buildings in the northeast corner of campus supporting research into biology, brain and cognitive sciences, genomics, biotechnology, and cancer research; and a number of new “backlot” buildings on Vassar Street including the Stata Center. Construction on campus in the 2000s included expansions of the Media Lab, the Sloan School’s eastern campus, and graduate residences in the northwest. In 2006, President Hockfield launched the MIT Energy Research Council to investigate the interdisciplinary challenges posed by increasing global energy consumption.

    In 2001, inspired by the open source and open access movements, Massachusetts Institute of Technology (US) launched OpenCourseWare to make the lecture notes, problem sets, syllabi, exams, and lectures from the great majority of its courses available online for no charge, though without any formal accreditation for coursework completed. While the cost of supporting and hosting the project is high, OCW expanded in 2005 to include other universities as a part of the OpenCourseWare Consortium, which currently includes more than 250 academic institutions with content available in at least six languages. In 2011, Massachusetts Institute of Technology (US) announced it would offer formal certification (but not credits or degrees) to online participants completing coursework in its “MITx” program, for a modest fee. The “edX” online platform supporting MITx was initially developed in partnership with Harvard and its analogous “Harvardx” initiative. The courseware platform is open source, and other universities have already joined and added their own course content. In March 2009 the Massachusetts Institute of Technology (US) faculty adopted an open-access policy to make its scholarship publicly accessible online.

    Massachusetts Institute of Technology (US) has its own police force. Three days after the Boston Marathon bombing of April 2013, MIT Police patrol officer Sean Collier was fatally shot by the suspects Dzhokhar and Tamerlan Tsarnaev, setting off a violent manhunt that shut down the campus and much of the Boston metropolitan area for a day. One week later, Collier’s memorial service was attended by more than 10,000 people, in a ceremony hosted by the Massachusetts Institute of Technology (US) community with thousands of police officers from the New England region and Canada. On November 25, 2013, Massachusetts Institute of Technology (US) announced the creation of the Collier Medal, to be awarded annually to “an individual or group that embodies the character and qualities that Officer Collier exhibited as a member of the Massachusetts Institute of Technology (US) community and in all aspects of his life”. The announcement further stated that “Future recipients of the award will include those whose contributions exceed the boundaries of their profession, those who have contributed to building bridges across the community, and those who consistently and selflessly perform acts of kindness”.

    In September 2017, the school announced the creation of an artificial intelligence research lab called the MIT-IBM Watson AI Lab. IBM will spend $240 million over the next decade, and the lab will be staffed by MIT and IBM scientists. In October 2018 MIT announced that it would open a new Schwarzman College of Computing dedicated to the study of artificial intelligence, named after lead donor and The Blackstone Group CEO Stephen Schwarzman. The focus of the new college is to study not just AI, but interdisciplinary AI education, and how AI can be used in fields as diverse as history and biology. The cost of buildings and new faculty for the new college is expected to be $1 billion upon completion.

    The Caltech/MIT Advanced aLIGO (US) was designed and constructed by a team of scientists from California Institute of Technology (US), Massachusetts Institute of Technology (US), and industrial contractors, and funded by the National Science Foundation (US) .

    MIT/Caltech Advanced aLigo .

    It was designed to open the field of gravitational-wave astronomy through the detection of gravitational waves predicted by general relativity. Gravitational waves were detected for the first time by the LIGO detector in 2015. For contributions to the LIGO detector and the observation of gravitational waves, two Caltech physicists, Kip Thorne and Barry Barish, and Massachusetts Institute of Technology (US) physicist Rainer Weiss won the Nobel Prize in physics in 2017. Weiss, who is also an Massachusetts Institute of Technology (US) graduate, designed the laser interferometric technique, which served as the essential blueprint for the LIGO.

    The mission of Massachusetts Institute of Technology (US) is to advance knowledge and educate students in science, technology, and other areas of scholarship that will best serve the nation and the world in the twenty-first century. We seek to develop in each member of the Massachusetts Institute of Technology (US) community the ability and passion to work wisely, creatively, and effectively for the betterment of humankind.

     
  • richardmitnick 7:30 am on June 27, 2021 Permalink | Reply
    Tags: "Looking for similarities across complex systems", , , Dunkel’s work is planted in theory and numerical principles of geometry; mechanics; and pattern formation., How does the motion of individual cells give rise to the structure of biological tissue?, Jörn Dunkel uses the “common language” of math to bridge disparate phenomena from an embryo’s wrinkles to the twist of spaghetti., , Mathematics   

    From Massachusetts Institute of Technology (US) : “Looking for similarities across complex systems” 

    MIT News

    From Massachusetts Institute of Technology (US)

    June 28, 2021
    Jennifer Chu

    Jörn Dunkel uses the “common language” of math to bridge disparate phenomena from an embryo’s wrinkles to the twist of spaghetti.

    1
    MIT mathematician Jörn Dunkel looks for similarities across complex systems. Credit: M. Scott Brauer.

    How does the motion of individual cells give rise to the structure of biological tissue? How do an embryo’s wrinkles relate to an animal’s shape? And what does the stability of knots have to do with the way spaghetti breaks?

    These are some of the questions Jörn Dunkel has explored at MIT, through the lens of mathematics.

    “There are many problems where, if you look at them from the right way, you can treat them in a similar manner because they have a common structure at some abstract level,” says Dunkel, who received tenure in 2020 as an associate professor in the Department of Mathematics.

    Dunkel’s work is planted in theory and numerical principles of geometry; mechanics; and pattern formation. From this base of mathematical operations, he has explored wide-ranging fields, looking for ways to bridge seemingly disparate systems through what he sees as the “common language” of math.

    “What’s helpful for me is to talk to people from many different fields,” Dunkel says. “This kicks me out of my comfort zone, and it’s almost like an algorithm for generating new ideas: Talk to people to get new perspectives, and then you try to combine that with what you know. And in this way you can make progress.”

    A system resettled

    Dunkel was born and raised in East Berlin, Germany, and vividly remembers the fall of the Berlin Wall, in 1989, as a time of both disruption and possibility.

    “It was a big, big change,” Dunkel recalls. “When my sister and I were little, our family couldn’t travel anywhere except for a small number of countries in the Eastern bloc. And when the wall came down, suddenly there were a lot of opportunities, and also uncertainties. There was more freedom to travel and see and learn different things. At the same time, people had to reestablish themselves, and many things were in limbo. You learned to adapt to a new system.”

    As the country’s schools restructured and settled into a unified, national education system, Dunkel was able for the first time to explore beyond East Berlin’s now-dissolved borders. After graduating from high school, he began to study at Humboldt University of Berlin [Humboldt-Universität zu Berlin] (DE). Dunkel’s undergraduate mentor, who worked in the area of active matter, introduced him to concepts of math and physics, and how to apply them to questions of biology, such as ways to describe how cells interact to give rise to macroscale tissues and whole organisms.

    “You start to see how things come together, and the way I was taught in those days had a big influence on how I think about systems today,” Dunkel says. “I was lucky many times along my path to have met people who helped teach and guide me.”

    Honest data

    After graduating with master’s degrees in math and physics, Dunkel dabbled briefly in astrophysics as a PhD student at the MPG Institute for Astrophysics [MPG Institut für Astrophysik](DE) before moving to the University of Augsburg [Universität Augsburg] (DE), in Germany, where he joined a statistical physics group headed by Peter Hanggi. There, he studied thermostatistical concepts in special relativity, and also in Brownian motion (the random motion of discrete particles), looking for ways to connect large-scale transport phenomena to their microscopic, single-particle machinery.

    He took the mathematical tools he developed in his PhD work to Oxford University (UK), where he did a postdoc with a group working in theoretical physics and exploring ways to mathematically model the individual and collective dynamics of bacterial cells. From there, he moved to University of Cambridge (UK), where he joined an experimental biophysics group as the only theory-oriented postdoc at the time. The researchers there were carrying out experiments on bacteria and algae and looking for patterns in the data to describe mathematically how the organisms swim.

    “What I learned there was, if you start working with a dataset that’s fundamentally new, it keeps you honest and forces you to think in new ways, because you have to explain that data,” Dunkel says. “So, even today when I advise my students, each one no matter the project, gets a real dataset to work with. Because as you try to understand the dataset, you can get new ideas that you wouldn’t have thought of otherwise.”

    Conscious capacity

    In 2013, Dunkel moved from the “other” Cambridge, to MIT, where he joined the Department of Mathematics as a junior faculty member in applied mathematics. In setting up his research program, he looked to develop mathematical tools to describe and predict the behavior of real-world phenomena at both the small and large scale, and to seek ways to mathematically bridge the two scales in various systems.

    He has primarily applied this thinking to understanding problems in developmental biology and soft matter, and has collaborated with experimentalists at MIT — especially professors Nikta Fakhri and Adam Martin — and elsewhere, looking through data they collect, for instance on the spiral waves in starfish eggs, for patterns that can be described and predicted through math. Dunkel has also intentionally left room to explore questions that might appear at first glance to divert from his main path of research.

    “For me it’s a conscious effort to leave capacities for new unexpected things,” Dunkel says. “This is what makes MIT special that you have this unique combination of people here who are excellent in so many areas and also very open to collaborating across the boundaries of disciplines.”

    A recent diversion sprang from a question that some of his students posed in class: Could a dry spaghetti noodle be broken in two? In addition to experimentally testing the idea, Dunkel helped the students develop a mathematical model to describe how the feat could be accomplished, with a precise bit of twisting.

    The work could have ended there. But it caught the attention of MIT Professor Matthias Kolle, who had developed a new type of fiber that changes color with strain. Kolle wondered whether the spaghetti model could be adapted to softer materials, to predict the strength of his fibers when knotted in certain configurations. He and Dunkel struck up a continuing collaboration, which has since drawn interest from surgeons looking to understand the stability of surgical knots, as well as biologists who are applying the model to predict the behavior of colonies of worms.

    “Though many of these systems are different, fundamentally, we can see similarities in the structure of their data,” Dunkel says. “It’s very easy to find differences. What’s more interesting is to find out what’s similar.”

    See the full article here .


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    Please help promote STEM in your local schools.

    Stem Education Coalition

    MIT Seal

    USPS “Forever” postage stamps celebrating Innovation at MIT.

    MIT Campus

    Massachusetts Institute of Technology (US) is a private land-grant research university in Cambridge, Massachusetts. The institute has an urban campus that extends more than a mile (1.6 km) alongside the Charles River. The institute also encompasses a number of major off-campus facilities such as the MIT Lincoln Laboratory, the Bates Center, and the Haystack Observatory, as well as affiliated laboratories such as the Broad and Whitehead Institutes.

    Founded in 1861 in response to the increasing industrialization of the United States, Massachusetts Institute of Technology (US) adopted a European polytechnic university model and stressed laboratory instruction in applied science and engineering. It has since played a key role in the development of many aspects of modern science, engineering, mathematics, and technology, and is widely known for its innovation and academic strength. It is frequently regarded as one of the most prestigious universities in the world.

    As of December 2020, 97 Nobel laureates, 26 Turing Award winners, and 8 Fields Medalists have been affiliated with MIT as alumni, faculty members, or researchers. In addition, 58 National Medal of Science recipients, 29 National Medals of Technology and Innovation recipients, 50 MacArthur Fellows, 80 Marshall Scholars, 3 Mitchell Scholars, 22 Schwarzman Scholars, 41 astronauts, and 16 Chief Scientists of the U.S. Air Force have been affiliated with Massachusetts Institute of Technology (US) . The university also has a strong entrepreneurial culture and MIT alumni have founded or co-founded many notable companies. Massachusetts Institute of Technology (US) is a member of the Association of American Universities (AAU).

    Foundation and vision

    In 1859, a proposal was submitted to the Massachusetts General Court to use newly filled lands in Back Bay, Boston for a “Conservatory of Art and Science”, but the proposal failed. A charter for the incorporation of the Massachusetts Institute of Technology, proposed by William Barton Rogers, was signed by John Albion Andrew, the governor of Massachusetts, on April 10, 1861.

    Rogers, a professor from the University of Virginia (US), wanted to establish an institution to address rapid scientific and technological advances. He did not wish to found a professional school, but a combination with elements of both professional and liberal education, proposing that:

    “The true and only practicable object of a polytechnic school is, as I conceive, the teaching, not of the minute details and manipulations of the arts, which can be done only in the workshop, but the inculcation of those scientific principles which form the basis and explanation of them, and along with this, a full and methodical review of all their leading processes and operations in connection with physical laws.”

    The Rogers Plan reflected the German research university model, emphasizing an independent faculty engaged in research, as well as instruction oriented around seminars and laboratories.

    Early developments

    Two days after Massachusetts Institute of Technology (US) was chartered, the first battle of the Civil War broke out. After a long delay through the war years, MIT’s first classes were held in the Mercantile Building in Boston in 1865. The new institute was founded as part of the Morrill Land-Grant Colleges Act to fund institutions “to promote the liberal and practical education of the industrial classes” and was a land-grant school. In 1863 under the same act, the Commonwealth of Massachusetts founded the Massachusetts Agricultural College, which developed as the University of Massachusetts Amherst (US)). In 1866, the proceeds from land sales went toward new buildings in the Back Bay.

    Massachusetts Institute of Technology (US) was informally called “Boston Tech”. The institute adopted the European polytechnic university model and emphasized laboratory instruction from an early date. Despite chronic financial problems, the institute saw growth in the last two decades of the 19th century under President Francis Amasa Walker. Programs in electrical, chemical, marine, and sanitary engineering were introduced, new buildings were built, and the size of the student body increased to more than one thousand.

    The curriculum drifted to a vocational emphasis, with less focus on theoretical science. The fledgling school still suffered from chronic financial shortages which diverted the attention of the MIT leadership. During these “Boston Tech” years, Massachusetts Institute of Technology (US) faculty and alumni rebuffed Harvard University (US) president (and former MIT faculty) Charles W. Eliot’s repeated attempts to merge MIT with Harvard College’s Lawrence Scientific School. There would be at least six attempts to absorb MIT into Harvard. In its cramped Back Bay location, MIT could not afford to expand its overcrowded facilities, driving a desperate search for a new campus and funding. Eventually, the MIT Corporation approved a formal agreement to merge with Harvard, over the vehement objections of MIT faculty, students, and alumni. However, a 1917 decision by the Massachusetts Supreme Judicial Court effectively put an end to the merger scheme.

    In 1916, the Massachusetts Institute of Technology (US) administration and the MIT charter crossed the Charles River on the ceremonial barge Bucentaur built for the occasion, to signify MIT’s move to a spacious new campus largely consisting of filled land on a one-mile-long (1.6 km) tract along the Cambridge side of the Charles River. The neoclassical “New Technology” campus was designed by William W. Bosworth and had been funded largely by anonymous donations from a mysterious “Mr. Smith”, starting in 1912. In January 1920, the donor was revealed to be the industrialist George Eastman of Rochester, New York, who had invented methods of film production and processing, and founded Eastman Kodak. Between 1912 and 1920, Eastman donated $20 million ($236.6 million in 2015 dollars) in cash and Kodak stock to MIT.

    Curricular reforms

    In the 1930s, President Karl Taylor Compton and Vice-President (effectively Provost) Vannevar Bush emphasized the importance of pure sciences like physics and chemistry and reduced the vocational practice required in shops and drafting studios. The Compton reforms “renewed confidence in the ability of the Institute to develop leadership in science as well as in engineering”. Unlike Ivy League schools, Massachusetts Institute of Technology (US) catered more to middle-class families, and depended more on tuition than on endowments or grants for its funding. The school was elected to the Association of American Universities (US)in 1934.

    Still, as late as 1949, the Lewis Committee lamented in its report on the state of education at Massachusetts Institute of Technology (US) that “the Institute is widely conceived as basically a vocational school”, a “partly unjustified” perception the committee sought to change. The report comprehensively reviewed the undergraduate curriculum, recommended offering a broader education, and warned against letting engineering and government-sponsored research detract from the sciences and humanities. The School of Humanities, Arts, and Social Sciences and the MIT Sloan School of Management were formed in 1950 to compete with the powerful Schools of Science and Engineering. Previously marginalized faculties in the areas of economics, management, political science, and linguistics emerged into cohesive and assertive departments by attracting respected professors and launching competitive graduate programs. The School of Humanities, Arts, and Social Sciences continued to develop under the successive terms of the more humanistically oriented presidents Howard W. Johnson and Jerome Wiesner between 1966 and 1980.

    Massachusetts Institute of Technology (US)‘s involvement in military science surged during World War II. In 1941, Vannevar Bush was appointed head of the federal Office of Scientific Research and Development and directed funding to only a select group of universities, including MIT. Engineers and scientists from across the country gathered at Massachusetts Institute of Technology (US)’s Radiation Laboratory, established in 1940 to assist the British military in developing microwave radar. The work done there significantly affected both the war and subsequent research in the area. Other defense projects included gyroscope-based and other complex control systems for gunsight, bombsight, and inertial navigation under Charles Stark Draper’s Instrumentation Laboratory; the development of a digital computer for flight simulations under Project Whirlwind; and high-speed and high-altitude photography under Harold Edgerton. By the end of the war, Massachusetts Institute of Technology (US) became the nation’s largest wartime R&D contractor (attracting some criticism of Bush), employing nearly 4000 in the Radiation Laboratory alone and receiving in excess of $100 million ($1.2 billion in 2015 dollars) before 1946. Work on defense projects continued even after then. Post-war government-sponsored research at MIT included SAGE and guidance systems for ballistic missiles and Project Apollo.

    These activities affected Massachusetts Institute of Technology (US) profoundly. A 1949 report noted the lack of “any great slackening in the pace of life at the Institute” to match the return to peacetime, remembering the “academic tranquility of the prewar years”, though acknowledging the significant contributions of military research to the increased emphasis on graduate education and rapid growth of personnel and facilities. The faculty doubled and the graduate student body quintupled during the terms of Karl Taylor Compton, president of Massachusetts Institute of Technology (US) between 1930 and 1948; James Rhyne Killian, president from 1948 to 1957; and Julius Adams Stratton, chancellor from 1952 to 1957, whose institution-building strategies shaped the expanding university. By the 1950s, Massachusetts Institute of Technology (US) no longer simply benefited the industries with which it had worked for three decades, and it had developed closer working relationships with new patrons, philanthropic foundations and the federal government.

    In late 1960s and early 1970s, student and faculty activists protested against the Vietnam War and Massachusetts Institute of Technology (US)’s defense research. In this period Massachusetts Institute of Technology (US)’s various departments were researching helicopters, smart bombs and counterinsurgency techniques for the war in Vietnam as well as guidance systems for nuclear missiles. The Union of Concerned Scientists was founded on March 4, 1969 during a meeting of faculty members and students seeking to shift the emphasis on military research toward environmental and social problems. Massachusetts Institute of Technology (US) ultimately divested itself from the Instrumentation Laboratory and moved all classified research off-campus to the MIT (US) Lincoln Laboratory facility in 1973 in response to the protests. The student body, faculty, and administration remained comparatively unpolarized during what was a tumultuous time for many other universities. Johnson was seen to be highly successful in leading his institution to “greater strength and unity” after these times of turmoil. However six Massachusetts Institute of Technology (US) students were sentenced to prison terms at this time and some former student leaders, such as Michael Albert and George Katsiaficas, are still indignant about MIT’s role in military research and its suppression of these protests. (Richard Leacock’s film, November Actions, records some of these tumultuous events.)

    In the 1980s, there was more controversy at Massachusetts Institute of Technology (US) over its involvement in SDI (space weaponry) and CBW (chemical and biological warfare) research. More recently, Massachusetts Institute of Technology (US)’s research for the military has included work on robots, drones and ‘battle suits’.

    Recent history

    Massachusetts Institute of Technology (US) has kept pace with and helped to advance the digital age. In addition to developing the predecessors to modern computing and networking technologies, students, staff, and faculty members at Project MAC, the Artificial Intelligence Laboratory, and the Tech Model Railroad Club wrote some of the earliest interactive computer video games like Spacewar! and created much of modern hacker slang and culture. Several major computer-related organizations have originated at MIT since the 1980s: Richard Stallman’s GNU Project and the subsequent Free Software Foundation were founded in the mid-1980s at the AI Lab; the MIT Media Lab was founded in 1985 by Nicholas Negroponte and Jerome Wiesner to promote research into novel uses of computer technology; the World Wide Web Consortium standards organization was founded at the Laboratory for Computer Science in 1994 by Tim Berners-Lee; the MIT OpenCourseWare project has made course materials for over 2,000 Massachusetts Institute of Technology (US) classes available online free of charge since 2002; and the One Laptop per Child initiative to expand computer education and connectivity to children worldwide was launched in 2005.

    Massachusetts Institute of Technology (US) was named a sea-grant college in 1976 to support its programs in oceanography and marine sciences and was named a space-grant college in 1989 to support its aeronautics and astronautics programs. Despite diminishing government financial support over the past quarter century, MIT launched several successful development campaigns to significantly expand the campus: new dormitories and athletics buildings on west campus; the Tang Center for Management Education; several buildings in the northeast corner of campus supporting research into biology, brain and cognitive sciences, genomics, biotechnology, and cancer research; and a number of new “backlot” buildings on Vassar Street including the Stata Center. Construction on campus in the 2000s included expansions of the Media Lab, the Sloan School’s eastern campus, and graduate residences in the northwest. In 2006, President Hockfield launched the MIT Energy Research Council to investigate the interdisciplinary challenges posed by increasing global energy consumption.

    In 2001, inspired by the open source and open access movements, Massachusetts Institute of Technology (US) launched OpenCourseWare to make the lecture notes, problem sets, syllabi, exams, and lectures from the great majority of its courses available online for no charge, though without any formal accreditation for coursework completed. While the cost of supporting and hosting the project is high, OCW expanded in 2005 to include other universities as a part of the OpenCourseWare Consortium, which currently includes more than 250 academic institutions with content available in at least six languages. In 2011, Massachusetts Institute of Technology (US) announced it would offer formal certification (but not credits or degrees) to online participants completing coursework in its “MITx” program, for a modest fee. The “edX” online platform supporting MITx was initially developed in partnership with Harvard and its analogous “Harvardx” initiative. The courseware platform is open source, and other universities have already joined and added their own course content. In March 2009 the Massachusetts Institute of Technology (US) faculty adopted an open-access policy to make its scholarship publicly accessible online.

    Massachusetts Institute of Technology (US) has its own police force. Three days after the Boston Marathon bombing of April 2013, MIT Police patrol officer Sean Collier was fatally shot by the suspects Dzhokhar and Tamerlan Tsarnaev, setting off a violent manhunt that shut down the campus and much of the Boston metropolitan area for a day. One week later, Collier’s memorial service was attended by more than 10,000 people, in a ceremony hosted by the Massachusetts Institute of Technology (US) community with thousands of police officers from the New England region and Canada. On November 25, 2013, Massachusetts Institute of Technology (US) announced the creation of the Collier Medal, to be awarded annually to “an individual or group that embodies the character and qualities that Officer Collier exhibited as a member of the Massachusetts Institute of Technology (US) community and in all aspects of his life”. The announcement further stated that “Future recipients of the award will include those whose contributions exceed the boundaries of their profession, those who have contributed to building bridges across the community, and those who consistently and selflessly perform acts of kindness”.

    In September 2017, the school announced the creation of an artificial intelligence research lab called the MIT-IBM Watson AI Lab. IBM will spend $240 million over the next decade, and the lab will be staffed by MIT and IBM scientists. In October 2018 MIT announced that it would open a new Schwarzman College of Computing dedicated to the study of artificial intelligence, named after lead donor and The Blackstone Group CEO Stephen Schwarzman. The focus of the new college is to study not just AI, but interdisciplinary AI education, and how AI can be used in fields as diverse as history and biology. The cost of buildings and new faculty for the new college is expected to be $1 billion upon completion.

    The Caltech/MIT Advanced aLIGO (US) was designed and constructed by a team of scientists from California Institute of Technology (US), Massachusetts Institute of Technology (US), and industrial contractors, and funded by the National Science Foundation (US) .

    MIT/Caltech Advanced aLigo .

    It was designed to open the field of gravitational-wave astronomy through the detection of gravitational waves predicted by general relativity. Gravitational waves were detected for the first time by the LIGO detector in 2015. For contributions to the LIGO detector and the observation of gravitational waves, two Caltech physicists, Kip Thorne and Barry Barish, and Massachusetts Institute of Technology (US) physicist Rainer Weiss won the Nobel Prize in physics in 2017. Weiss, who is also an Massachusetts Institute of Technology (US) graduate, designed the laser interferometric technique, which served as the essential blueprint for the LIGO.

    The mission of Massachusetts Institute of Technology (US) is to advance knowledge and educate students in science, technology, and other areas of scholarship that will best serve the nation and the world in the twenty-first century. We seek to develop in each member of the Massachusetts Institute of Technology (US) community the ability and passion to work wisely, creatively, and effectively for the betterment of humankind.

     
  • richardmitnick 4:17 pm on June 25, 2021 Permalink | Reply
    Tags: "Nathan Seiberg on How Math Might Complete the Ultimate Physics Theory", , From the time of the ancient Babylonians and Greeks there hasn’t been a real distinction between math and physics., Mathematics, Physicists and mathematicians are motivated by different questions. And different kinds of questions lead to different insights., , QFT: Quantum Field Theory, , Seiberg’s work has helped bring the study of quantum field theories closer to pure mathematics., The Standard Model of Particle Physics explains nearly every aspect of the physical world (except gravity)., We cannot yet formulate QFT in a rigorous way that would make mathematicians perfectly happy., [Isaac] Newton was motivated by physics when he invented calculus.   

    From Quanta Magazine : “Nathan Seiberg on How Math Might Complete the Ultimate Physics Theory” 

    From Quanta Magazine

    June 24, 2021
    Kevin Hartnett

    Even in an incomplete state, quantum field theory is the most successful physical theory ever discovered. Nathan Seiberg, one of its leading architects, talks about the gaps in QFT and how mathematicians could fill them.

    1
    Nathan Seiberg crosses a bridge over Stony Brook at the Institute for Advanced Study. Credit: Sasha Maslov for Quanta Magazine.

    Nathan Seiberg, 64, still does a lot of the electrical work and even some of the plumbing around his house in Princeton, New Jersey. It’s an interest he developed as a kid growing up in Israel, where he tinkered with his car and built a radio.

    “I was always fascinated by solving problems and understanding how things work,” he said.

    Seiberg’s professional career has been about problem solving, too, though nothing as straightforward as fixing radios. He’s a physicist at the Institute for Advanced Study (US), and over the course of a long and decorated career he has made many contributions to the development of Quantum Field Theory, or QFT.

    QFT refers broadly to the set of all possible quantum field theories. These are theories whose basic objects are “fields,” which stretch across space and time. There are fields associated with fundamental particles like electrons and quarks, and fields associated with fundamental forces, like gravity and electromagnetism. The most sweeping quantum field theory — and the most successful theory in the history of physics, period — is the Standard Model.

    It combines these fields into a single equation that explains nearly every aspect of the physical world (except gravity).

    By the time Seiberg started graduate school at the Weizmann Institute of Science (IL) in 1978, QFT was already well established as the principal perspective of physics. Its predictive power wasn’t in doubt, but many basic questions remained about how and why it worked so well.

    “It’s shocking that we have these techniques and sometimes they give beautiful answers, despite the fact that we don’t know how to formulate the problems rigorously,” said Seiberg.

    Much of Seiberg’s most important work has involved teasing apart how particular quantum field theories work the way they do. In the late 1980s he and Gregory Moore worked out mathematical details of types of quantum field theories called conformal field theories and topological field theories. Shortly after, partly in collaboration with Edward Witten, he focused on understanding features of three- and four-dimensional “supersymmetric” quantum field theories. This helped explain how quarks, the particles inside protons, are confined there.

    The work is complicated, but Seiberg retains an element of childlike fascination with it. Just as he once wanted to understand how a transistor radio produces sound, as a physicist he now seeks to explain how these quantum field theories yield often startlingly accurate predictions about the physical world.

    “You’re trying to figure out how something works and then you’re trying to use it,” he said.

    Seiberg’s work has also helped bring the study of quantum field theories closer to pure mathematics. In 1994, Witten discovered how to use physical phenomena that he and Seiberg had discovered to quantify basic characteristics of a space, like the number of holes it has. Their “Seiberg-Witten invariants” are now an essential tool in math. Seiberg believes quantum field theory and math must continue to grow closer if physicists are ever really going to understand the basic features underlying all quantum field theories.

    Quanta Magazine spoke with Seiberg about how physics and math are really two sides of the same coin, the ways in which QFT is incompletely understood today, and his own abandoned effort to write a textbook for the field. The interview has been condensed and edited for clarity.

    2
    Seiberg suspects that math and physics, which became separate fields of study only relatively recently, will one day merge together under the same deep intellectual structure. Credit: Sasha Maslov for Quanta Magazine.

    Math and physics have a long history together. What are some of the most important ways they have influenced each other over the centuries?

    From the time of the ancient Babylonians and Greeks there hasn’t been a real distinction between math and physics. They studied similar questions. There has been a lot of cross-fertilization between what today we call math and physics. [Isaac] Newton is a great example. He was motivated by physics when he invented calculus. Over the 20th century, things were a bit more complicated. People specialized in math or in physics.

    Physics usually offers very concrete questions and very concrete puzzles associated with reality and experiment. It’s also kind of grounded in reality. Math usually provides more generality, more powerful methods, and more rigor and precision. All of these elements are needed.

    Do you think they’ll continue to be increasingly separate fields?

    Given that they started as one field and lately diverged, but continue to influence each other, in the future I’d guess they’ll continue to influence each other to the point that there would be no clear separation between them. I think that there will be one deep, intellectual structure that encompasses math and physics.

    Why has QFT, and physics in general, been such a provocative stimulus for math?

    I think physicists and mathematicians are motivated by different questions. And different kinds of questions lead to different insights. There have been many examples where physicists came up with some ideas — which in most cases were not even rigorous — and mathematicians looked at them and said, “This is an equality between two different things; let’s try and prove it.” So the input from physics is another source of influence for the mathematicians. From this perspective, physics is like a machine that produces conjectures.

    And the track record with these conjectures has been quite amazing, so mathematicians have learned to take physics in general and quantum field theory in particular very seriously. But what is perhaps surprising for them is that they still can’t make QFT rigorous; they still can’t figure out where these insights come from.

    Let’s focus on the physics side for now, and that amazing track record. What are some of its biggest triumphs?

    QFT is by far the most successful theory ever created by mankind to explain anything. There are many [predictions] that agree perfectly with experiments to unprecedented accuracy. We’re talking about accuracy of up to the order of 12 digits between theory and experiment. And there are literally trillions and trillions of experiments that match the theory. I don’t think historically there has ever been any theory as successful as quantum field theory. And it includes as special cases all the previous discoveries, like Newton’s theory, [James Clerk] Maxwell’s theory of electromagnetism, and of course quantum mechanics and Albert Einstein’s special relativity. All these things are special cases of this one coherent intellectual structure. It’s an amazing, spectacular achievement.

    And yet we also think QFT is incomplete. What are its limitations?

    The biggest challenge is to merge it with Einstein’s general theory of relativity. There are many ideas how to do this. String theory is the main one. There has been a lot of progress, but we’re still not at the end of the story.

    You’ve referred to QFT as not yet “mature.” What do you mean by that?

    I have my preferred maturity test for a scientific field. That is to look at textbooks and at courses at universities that teach the topic. When you look at a mature field, most of the textbooks are more or less the same. They follow the same logical sequence of ideas. Similarly, most of the courses are more or less the same. When you learn calculus, you first learn one topic, then another, and then the third. It is the same sequence in all institutions. For me, this is a sign of a mature field.

    That’s not the case for QFT. There are several books with different perspectives from different points of view, with [ideas presented] in a different order. For me this means that we have not found the ultimate, streamlined version of presenting our understanding.

    You’ve also mentioned that it’s a sign of incompleteness that QFT doesn’t have its own place in mathematics. What does that mean?

    We cannot yet formulate QFT in a rigorous way that would make mathematicians perfectly happy. In special cases we can, but in general we cannot. In all the other theories in physics — in classical physics, in quantum mechanics — there is no such problem. Mathematicians have a rigorous description of it. They can prove theorems and make deep advances. That’s not yet the case in quantum field theory.

    I should emphasize that we do not look for rigor for the sake of rigor. That’s not our goal. But I think that the fact that we don’t yet have a rigorous description of it, the fact that mathematicians are not yet comfortable with it, is a clear reflection of the fact that we don’t yet fully understand what we’re doing.

    If we do have a rigorous description of QFT, it will give us new, deeper insights into the structure of the theory. It will give us new tools to perform calculations, and it will uncover new phenomena.

    Are we even close to doing this?

    Whatever approach we take, we get stuck somewhere. One approach that gets close to being rigorous is we imagine space as a lattice of points. Then we take the limit as the points approach each other and space becomes continuous. We describe space as a lattice, and as long as we’re on the lattice there is nothing non-rigorous about it. The challenge is to prove that the limit exists as the distance [between points on the lattice] becomes small and the number of points [on the lattice] becomes large. We assume this limit exists, but we cannot prove it.

    So if we do it, will a rigorous understanding of quantum field theory actually merge it with general relativity? That is, will it provide a long-sought theory of quantum gravity?

    It’s quite clear to me that there is one intellectual structure that includes everything. I think of quantum field theory as being the language of physics, simply because it already appears like the language of many different phenomena in many different fields. I expect it to encompass also quantum gravity. In fact, in special circumstances, quantum gravity is described by quantum field theory.

    It might take a century or two, even three centuries, to get there. But I personally don’t think it will take that long. This is not to say that in 200-300 years science will be over. There will still be many interesting questions to address. But with a better understanding of quantum field theory, I think [discovery] will be a lot faster.

    What could remain to be discovered after QFT is fully understood?

    Most physicists aren’t trying to find a more fundamental description of nature. [Instead they say,] “Given the rules, and given what we know, can we explain known phenomena and find new phenomena, like new materials that exhibit special properties?” I think this will continue for a long time. Nature is very rich, and once we fully understand the rules of nature we’ll be able to use these rules to predict new phenomena. This is not less exciting than finding the fundamental rules of nature.

    You mentioned that one indication the field of QFT is not complete is that it doesn’t yet have a canonical textbook. I mentioned this to another physicist recently, and he said a lot of people hope you’ll write it.

    I tried, actually, but I stopped. Around 2000, I took one summer, and at the end of the summer I had many pages written, and I realized I hated what I’d written.

    Honestly, my problem is that there are all these different ways of starting to write it, but I can’t find a preferred angle. I think it’s a reflection of the status of the field, a sign that it’s not yet mature enough. The fact that there isn’t a clear starting point, to me, is a sign that we haven’t yet found the ultimate way to think about it.

    See the full article here .


    five-ways-keep-your-child-safe-school-shootings

    Please help promote STEM in your local schools.

    Stem Education Coalition

    Formerly known as Simons Science News, Quanta Magazine is an editorially independent online publication launched by the Simons Foundation to enhance public understanding of science. Why Quanta? Albert Einstein called photons “quanta of light.” Our goal is to “illuminate science.” At Quanta Magazine, scientific accuracy is every bit as important as telling a good story. All of our articles are meticulously researched, reported, edited, copy-edited and fact-checked.

     
  • richardmitnick 11:37 am on June 25, 2021 Permalink | Reply
    Tags: "New math model traces the link between atmospheric CO2 and temperature over half a billion years", , , , , ESS: Earth system sensitivity, Mathematics,   

    From Rochester Institute of Technology (US) : “New math model traces the link between atmospheric CO2 and temperature over half a billion years” 

    From Rochester Institute of Technology (US)

    June 23, 2021
    Luke Auburn
    luke.auburn@rit.edu

    Lead author Assistant Professor Tony Wong’s paper featured in Nature Communications.

    1
    Assistant professor Tony Wong is the lead author of an article featured in the journal Nature Communications that outlines a new modeling method to explore the relationship between the Earth’s atmospheric carbon dioxide and surface temperature over hundreds of millions of years.

    A Rochester Institute of Technology mathematician helped develop a new modeling method to explore the relationship between the Earth’s atmospheric carbon dioxide (CO2) and surface temperature over hundreds of millions of years. Assistant professor Tony Wong is the lead author of an article featured in the journal Nature Communications that outlines the method. He hopes it will help answer fundamental questions about the geophysical processes that drive the Earth’s climate.

    Scientists often use a measurement method called equilibrium climate sensitivity (ECS) to study the long-term effect on temperature of doubling atmospheric CO2 concentrations above pre-industrial conditions. ECS is helpful for assessing the effectiveness of climate change policies and understanding changes of up to a few hundred years. Wong’s method works on a much grander scale and uses a measurement called Earth system sensitivity (ESS), which allows the method to factor in processes that take millions of years to change, such as the shifting of tectonic plates or variations in solar luminosity.

    “The model gives us better insight into how the world and its geophysical processes work,” said Wong, faculty in the School of Mathematical Sciences. “It offers this nice schematic to incorporate all of the physics that encapsulates our current understanding of the Earth’s system. If it doesn’t look good or there are areas where there are biases relative to data that we have, then that highlights a gap in the understanding of the physics of our world. So we can go back and say OK, so what do we need to do to improve our understanding of the world?”

    Wong said the new work improves upon previous studies that used more limited sets of data and less sophisticated statistical methods for calibration. He also noted that the team used a unique inverse parameter calibration approach.

    “It’s taking this kind of Sherlock Holmes approach of once you rule out what’s not possible, what you’re left with must contain the truth,” said Wong. “It’s an interesting approach and it’s nice because there’s this satisfying cycle where you run the model forward, you see how it compares against data, and you rule out the parameter values that don’t represent the world we live in.”

    Wong has been working with College of Science students on ways to leverage the new technique. Recent alumnus Ken Shultes ’20 (applied mathematics) ’21 MS (applied and computational mathematics) built on the method and is developing an even more detailed statistical technique to infer the best model parameter values based on observational data.

    See the full article here .

    five-ways-keep-your-child-safe-school-shootings

    Please help promote STEM in your local schools.

    Stem Education Coalition

    Rochester Institute of Technology (US) is a private doctoral university within the town of Henrietta in the Rochester, New York metropolitan area.

    RIT is composed of nine academic colleges, including National Technical Institute for the Deaf(RIT)(US). The Institute is one of only a small number of engineering institutes in the State of New York, including New York Institute of Technology, SUNY Polytechnic Institute, and Rensselaer Polytechnic Institute(US). It is most widely known for its fine arts, computing, engineering, and imaging science programs; several fine arts programs routinely rank in the national “Top 10” according to US News & World Report.

    The university offers undergraduate and graduate degrees, including doctoral and professional degrees and online masters as well.

    The university was founded in 1829 and is the tenth largest private university in the country in terms of full-time students. It is internationally known for its science; computer; engineering; and art programs as well as for the National Technical Institute for the Deaf- a leading deaf-education institution that provides educational opportunities to more than 1000 deaf and hard-of-hearing students. RIT is known for its Co-op program that gives students professional and industrial experience. It has the fourth oldest and one of the largest Co-op programs in the world. It is classified among “R2: Doctoral Universities – High research activity”.

    RIT’s student population is approximately 19,000 students, about 16,000 undergraduate and 3000 graduate. Demographically, students attend from all 50 states in the United States and from more than 100 countries around the world. The university has more than 4000 active faculty and staff members who engage with the students in a wide range of academic activities and research projects. It also has branches abroad, its global campuses, located in China, Croatia and United Arab Emirates (Dubai).

    Fourteen RIT alumni and faculty members have been recipients of the Pulitzer Prize.

    History

    The university began as a result of an 1891 merger between Rochester Athenæum, a literary society founded in 1829 by Colonel Nathaniel Rochester and associates and The Mechanics Institute- a Rochester school of practical technical training for local residents founded in 1885 by a consortium of local businessmen including Captain Henry Lomb- co-founder of Bausch & Lomb. The name of the merged institution at the time was called Rochester Athenæum and Mechanics Institute (RAMI). The Mechanics Institute however, was considered as the surviving school by taking over The Rochester Athenaeum’s charter. From the time of the merger until 1944 RAMI celebrated The former Mechanics Institute’s 1885 founding charter. In 1944 the school changed its name to Rochester Institute of Technology and re-established The Athenaeum’s 1829 founding charter and became a full-fledged research university.

    The university originally resided within the city of Rochester, New York, proper, on a block bounded by the Erie Canal; South Plymouth Avenue; Spring Street; and South Washington Street (approximately 43.152632°N 77.615157°W). Its art department was originally located in the Bevier Memorial Building. By the middle of the twentieth century, RIT began to outgrow its facilities, and surrounding land was scarce and expensive. Additionally in 1959 the New York Department of Public Works announced a new freeway- the Inner Loop- was to be built through the city along a path that bisected the university’s campus and required demolition of key university buildings. In 1961 an unanticipated donation of $3.27 million ($27,977,071 today) from local Grace Watson (for whom RIT’s dining hall was later named) allowed the university to purchase land for a new 1,300-acre (5.3 km^2) campus several miles south along the east bank of the Genesee River in suburban Henrietta. Upon completion in 1968 the university moved to the new suburban campus, where it resides today.

    In 1966 RIT was selected by the Federal government to be the site of the newly founded National Technical Institute for the Deaf (NTID). NTID admitted its first students in 1968 concurrent with RIT’s transition to the Henrietta campus.

    In 1979 RIT took over Eisenhower College- a liberal arts college located in Seneca Falls, New York. Despite making a 5-year commitment to keep Eisenhower open RIT announced in July 1982 that the college would close immediately. One final year of operation by Eisenhower’s academic program took place in the 1982–83 school year on the Henrietta campus. The final Eisenhower graduation took place in May 1983 back in Seneca Falls.

    In 1990 RIT started its first PhD program in Imaging Science – the first PhD program of its kind in the U.S. RIT subsequently established PhD programs in six other fields: Astrophysical Sciences and Technology; Computing and Information Sciences; Color Science; Microsystems Engineering; Sustainability; and Engineering. In 1996 RIT became the first college in the U.S to offer a Software Engineering degree at the undergraduate level.

    Colleges

    RIT has nine colleges:

    RIT College of Engineering Technology
    Saunders College of Business
    B. Thomas Golisano College of Computing and Information Sciences
    Kate Gleason College of Engineering
    RIT College of Health Sciences and Technology
    College of Art and Design
    RIT College of Liberal Arts
    RIT College of Science
    National Technical Institute for the Deaf

    There are also three smaller academic units that grant degrees but do not have full college faculties:

    RIT Center for Multidisciplinary Studies
    Golisano Institute for Sustainability
    University Studies

    In addition to these colleges, RIT operates three branch campuses in Europe, one in the Middle East and one in East Asia:

    RIT Croatia (formerly the American College of Management and Technology) in Dubrovnik and Zagreb, Croatia
    RIT Kosovo (formerly the American University in Kosovo) in Pristina, Kosovo
    RIT Dubai in Dubai, United Arab Emirates
    RIT China-Weihai Campus

    RIT also has international partnerships with the following schools:[34]

    Yeditepe University in Istanbul, Turkey
    Birla Institute of Technology and Science in India
    Pontificia Universidad Catolica Madre y Maestra (PUCMM) in Dominican Republic
    Instituto Tecnológico de Santo Domingo (INTEC) in Dominican Republic
    Universidad Tecnologica Centro-Americana (UNITEC) in Honduras
    Universidad del Norte (UNINORTE) in Colombia
    Universidad Peruana de Ciencias Aplicadas (UPC) in Peru

    Research

    RIT’s research programs are rapidly expanding. The total value of research grants to university faculty for fiscal year 2007–2008 totaled $48.5 million- an increase of more than twenty-two percent over the grants from the previous year. The university currently offers eight PhD programs: Imaging science; Microsystems Engineering; Computing and Information Sciences; Color science; Astrophysical Sciences and Technology; Sustainability; Engineering; and Mathematical modeling.

    In 1986 RIT founded the Chester F. Carlson Center for Imaging Science and started its first doctoral program in Imaging Science in 1989. The Imaging Science department also offers the only Bachelors (BS) and Masters (MS) degree programs in imaging science in the country. The Carlson Center features a diverse research portfolio; its major research areas include Digital Image Restoration; Remote Sensing; Magnetic Resonance Imaging; Printing Systems Research; Color Science; Nanoimaging; Imaging Detectors; Astronomical Imaging; Visual Perception; and Ultrasonic Imaging.

    The Center for Microelectronic and Computer Engineering was founded by RIT in 1986. The university was the first university to offer a bachelor’s degree in Microelectronic Engineering. The Center’s facilities include 50,000 square feet (4,600 m^2) of building space with 10,000 square feet (930 m^2) of clean room space. The building will undergo an expansion later this year. Its research programs include nano-imaging; nano-lithography; nano-power; micro-optical devices; photonics subsystems integration; high-fidelity modeling and heterogeneous simulation; microelectronic manufacturing; microsystems integration; and micro-optical networks for computational applications.

    The Center for Advancing the Study of CyberInfrastructure (CASCI) is a multidisciplinary center housed in the College of Computing and Information Sciences. The Departments of Computer science; Software Engineering; Information technology; Computer engineering; Imaging Science; and Bioinformatics collaborate in a variety of research programs at this center. RIT was the first university to launch a Bachelor’s program in Information technology in 1991; the first university to launch a Bachelor’s program in Software Engineering in 1996 and was also among the first universities to launch a Computer science Bachelor’s program in 1972. RIT helped standardize the Forth programming language and developed the CLAWS software package.

    The Center for Computational Relativity and Gravitation was founded in 2007. The CCRG comprises faculty and postdoctoral research associates working in the areas of general relativity; gravitational waves; and galactic dynamics. Computing facilities in the CCRG include gravitySimulator, a novel 32-node supercomputer that uses special-purpose hardware to achieve speeds of 4TFlops in gravitational N-body calculations, and newHorizons [image N/A], a state-of-the art 85-node Linux cluster for numerical relativity simulations.

    2
    Gravity Simulator at the Center for Computational Relativity and Gravitation, RIT, Rochester, New York, USA.

    The Center for Detectors was founded in 2010. The CfD designs; develops; and implements new advanced sensor technologies through collaboration with academic researchers; industry engineers; government scientists; and university/college students. The CfD operates four laboratories and has approximately a dozen funded projects to advance detectors in a broad array of applications, e.g. astrophysics; biomedical imaging; Earth system science; and inter-planetary travel. Center members span eight departments and four colleges.

    RIT has collaborated with many industry players in the field of research as well, including IBM; Xerox; Rochester’s Democrat and Chronicle; Siemens; National Aeronautics Space Agency(US); and the Defense Advanced Research Projects Agency (US) (DARPA). In 2005, it was announced by Russell W. Bessette- Executive Director New York State Office of Science Technology & Academic Research (NYSTAR), that RIT will lead the SUNY University at Buffalo (US) and Alfred University (US) in an initiative to create key technologies in microsystems; photonics; nanomaterials; and remote sensing systems and to integrate next generation IT systems. In addition, the collaboratory is tasked with helping to facilitate economic development and tech transfer in New York State. More than 35 other notable organizations have joined the collaboratory, including Boeing, Eastman Kodak, IBM, Intel, SEMATECH, ITT, Motorola, Xerox, and several Federal agencies, including as NASA.

    RIT has emerged as a national leader in manufacturing research. In 2017, the U.S. Department of Energy selected RIT to lead its Reducing Embodied-Energy and Decreasing Emissions (REMADE) Institute aimed at forging new clean energy measures through the Manufacturing USA initiative. RIT also participates in five other Manufacturing USA research institutes.

     
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