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  • richardmitnick 3:18 pm on July 28, 2021 Permalink | Reply
    Tags: "Life in space-Preparing for an increasingly tangible reality", A.I., Aeronautical and Astronautical Engineering, , , , Computer Science, , , , , , , ,   

    From Massachusetts Institute of Technology (US) : “Life in space-Preparing for an increasingly tangible reality” 

    MIT News

    From Massachusetts Institute of Technology (US)

    July 28, 2021
    Sarah Beckmann | MIT Media Lab

    1
    Che-Wei Wang operates the Zenolith, a free-flying pointing device to orient space travelers in the universe, while Ariel Ekblaw looks on. Ekblaw is director of the Space Exploration Initiative at MIT and instructor of a class on preparing research projects for microgravity flights. Credit: Steve Boxall/ZERO-G.

    As a not-so-distant future that includes space tourism and people living off-planet approaches, the MIT Media Lab Space Exploration Initiative is designing and researching the activities humans will pursue in new, weightless environments.

    Since 2017, the Space Exploration Initiative (SEI) has orchestrated regular parabolic flights through the ZERO-G Research Program to test experiments that rely on microgravity. This May, the SEI supported researchers from the Media Lab; MIT’s departments of Aeronautics and Astronautics (AeroAstro), Earth, Atmospheric and Planetary Sciences (EAPS), and Mechanical Engineering; MIT Kavli Institute; the MIT Program in Art, Culture, and Technology; the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) (US); the John A. Paulson School of Engineering and Applied Sciences (SEAS) at Harvard University (US); the Center for Collaborative Arts and Media at Yale University (US); the multi-affiliated Szostak Laboratory -Harvard University, and the Harvard-MIT Program in Health Sciences and Technology to fly 22 different projects exploring research as diverse as fermentation, reconfigurable space structures, and the search for life in space.

    Most of these projects resulted from the 2019 or 2020 iterations of MAS.838 / 16.88 (Prototyping Our Space Future) taught by Ariel Ekblaw, SEI founder and director, who began teaching the class in 2018. (Due to the Covid-19 pandemic, the 2020 flight was postponed, leading to two cohorts being flown this year.)

    “The course is intentionally titled ‘Prototyping our Sci-Fi Space Future,’” she says, “because this flight opportunity that SEI wrangles, for labs across MIT, is meant to incubate and curate the future artifacts for life in space and robotic exploration — bringing the Media Lab’s uniqueness, magic, and creativity into the process.”

    The class prepares researchers for the realities of parabolic flights, which involves conducting experiments in short, 20-second bursts of zero gravity. As the course continues to offer hands-on research and logistical preparation, and as more of these flights are executed, the projects themselves are demonstrating increasing ambition and maturity.

    “Some students are repeat flyers who have matured their experiments, and [other experiments] come from researchers across the MIT campus from a record number of MIT departments, labs, and centers, and some included alumni and other external collaborators,” says Maria T. Zuber, MIT’s vice president for research and SEI faculty advisor. “In short, there was stiff competition to be selected, and some of the experiments are sufficiently far along that they’ll soon be suitable for spaceflight.”

    Dream big, design bold

    Both the 2020 and 2021 flight cohorts included daring new experiments that speak to SEI’s unique focus on research across disciplines. Some look to capitalize on the advantages of microgravity, while others seek to help find ways of living and working without the force that governs every moment of life on Earth.

    Che-Wei Wang, Sands Fish, and Mehak Sarang from SEI collaborated on Zenolith, a free-flying pointing device to orient space travelers in the universe — or, as the research team puts it, a 3D space compass. “We were able to perform some maneuvers in zero gravity and confirm that our control system was functioning quite well, the first step towards having the device point to any spot in the solar system,” says Sarang. “We’ll still have to tweak the design as we work towards our ultimate goal of sending the device to the International Space Station!”

    Then there’s the Gravity Loading Countermeasure Skinsuit project by Rachel Bellisle, a doctoral student in the Harvard-MIT Program in Health Sciences and Technology and a Draper Fellow.

    3
    The Skinsuit targets multiple physiological systems, aiming to mitigate spaceflight-induced musculoskeletal adaptations, such as spinal elongation. Additionally, the Skinsuit may provide benefits to the sensorimotor system, which have not been tested in previous studies. The sensorimotor effects of microgravity are difficult to simulate on Earth, even in bed rest analogs or body-weight suspension, due to the constant force of gravity on the body and body-load receptors. The goal of this project is to use the microgravity afforded by a parabolic flight to explore a research question: Can the Skinsuit restore sensorimotor functions that are typically altered in microgravity?

    The Skinsuit is designed to replicate the effects of Earth gravity for use in exercise on future missions to the moon or to Mars, and to further attenuate microgravity-induced physiological effects in current ISS mission scenarios. The suit has a 10-plus-year history of development at MIT and internationally, with prior parabolic flight experiments. Skinsuit originated in the lab of Dava Newman, who now serves as Media Lab director.

    “Designing, flying, and testing an actual prototype is the best way that I know of to prepare our suit designs for actual long-term spaceflight missions,” says Newman. “And flying in microgravity and partial gravity on the ZERO-G plane is a blast!”

    Alongside the Skinsuit are two more projects flown this spring that involve wearables and suit prototypes: the Peristaltic Suit developed by Media Lab researcher Irmandy Wicaksono and the Bio-Digital Wearables or Space Health Enhancement project by Media Lab researcher Pat Pataranutaporn.

    “Wearables have the potential to play a critical role in monitoring, supporting, and sustaining human life in space, lessening the need for human medical expert intervention,” Pataranutaporn says. “Also, having this microgravity experience after our SpaceCHI workshop … gave me so many ideas for thinking about other on-body systems that can augment humans in space — that I don’t think I would get from just reading a research paper.”

    AgriFuge, from Somayajulu Dhulipala and Manwei Chan (graduate students in MIT’s departments of Mechanical Engineering and AeroAstro, respectively), offers future astronauts a rotating plant habitat that provides simulated gravity as well as a controllable irrigation system. AgriFuge anticipates a future of long-duration missions where the crew will grow their own plants — to replenish oxygen and food, as well as for the psychological benefits of caring for plants. Two more cooking-related projects that flew this spring include H0TP0T, by Larissa Zhou from Harvard SEAS, and Gravity Proof, by Maggie Coblentz of the SEI — each of which help demonstrate a growing portfolio of practical “life in space” research being tested on these flights.

    The human touch

    In addition to the increasingly ambitious and sophisticated individual projects, an emerging theme in SEI’s microgravity endeavor is a focus on approaches to different aspects of life and culture in space — not only in relation to cooking, but also architecture, music, and art.

    Sanjana Sharma of the SEI flew her Fluid Expressions project this spring, which centers around the design of a memory capsule that functions as both a traveler’s painting kit for space and an embodied, material reminder of home. During the flight, she was able to produce three abstract watercolor paintings. “The most important part of this experience for me,” she says, “was the ability to develop a sense of what zero gravity actually feels like, as well as how the motions associated with painting differ during weightlessness.”

    Ekblaw has been mentoring two new architectural projects as part of the SEI’s portfolio, building on her own TESSERAE work for in-space self-assembly: Self Assembling Space Frames by SEI’s Che-Wei Wang and Reconfigurable space structures by Martin Nisser of MIT CSAIL. Wang envisions his project as a way to build private spaces in zero-gravity environments. “You could think of it like a pop-up tent for space,” he says. “The concept can potentially scale to much larger structures that self-assemble in space, outside space stations.”

    Onward and upward

    Two projects that explore different notions of the search for life in space include Ø-scillation, a collaboration between several scientists at the MIT Kavli Institute, Media Lab, EAPS, and Harvard; and the Electronic Life-detection Instrument (ELI) by Chris Carr, former MIT EAPS researcher and current Georgia Institute of Technology (US) faculty member, and Daniel Duzdevich, a postdoc at the Szostak Laboratory.

    The ELI project is a continuation of work within Zuber’s lab, and has been flown on previous flights. “Broadly, our goals are to build a low-mass life-detection instrument capable of detecting life as we know it — or as we don’t know it,” says Carr. During the 2021 flight, the researchers tested upgraded hardware that permits automatic real-time sub-nanometer gap control to improve the measurement fidelity of the system — with generally successful results.

    Microgravity Hybrid Extrusion, led by SEI’s mission integrator, Sean Auffinger, alongside Ekblaw, Nisser, Wang, and MIT Undergraduate Research Opportunities Program student Aiden Padilla, was tested on both flights this spring and works toward building in situ, large-scale space structures — it’s also one of the selected projects being flown on an ISS mission in December 2021. The SEI is also planning a prospective “Astronaut Interaction” mission on the ISS in 2022, where artifacts like Zenolith will have the chance to be manipulated by astronauts directly.

    This is a momentous fifth anniversary year for SEI. As these annual flights continue, and the experiments aboard them keep growing more advanced, researchers are setting their sights higher — toward designing and preparing for the future of interplanetary civilization.

    See the full article here .


    five-ways-keep-your-child-safe-school-shootings
    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 (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 Whitehead Institute (US).

    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 11:09 am on July 1, 2021 Permalink | Reply
    Tags: "The power of two", , , , , , Computer Science, , Ellen Zhong, , , , 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 .


    five-ways-keep-your-child-safe-school-shootings
    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 8:43 pm on June 17, 2021 Permalink | Reply
    Tags: "Clearing the way toward robust quantum computing", , , Computer Science, , ,   

    From Massachusetts Institute of Technology (US) : “Clearing the way toward robust quantum computing” 

    MIT News

    From Massachusetts Institute of Technology (US)

    June 16, 2021
    Michaela Jarvis | Research Laboratory of Electronics

    MIT researchers demonstrate a way to sharply reduce errors in two-qubit gates, a significant advance toward fully realizing quantum computation.

    1
    A tunable coupler can switch the qubit-qubit interaction on and off. Unwanted, residual (ZZ) interaction between the two qubits is eliminated by harnessing higher energy levels of the coupler.
    Credit: Krantz Nanoart.

    MIT researchers have made a significant advance on the road toward the full realization of quantum computation, demonstrating a technique that eliminates common errors in the most essential operation of quantum algorithms, the two-qubit operation or “gate.”

    “Despite tremendous progress toward being able to perform computations with low error rates with superconducting quantum bits (qubits), errors in two-qubit gates, one of the building blocks of quantum computation, persist,” says Youngkyu Sung, an MIT graduate student in electrical engineering and computer science who is the lead author of a paper on this topic published today in Physical Review X. “We have demonstrated a way to sharply reduce those errors.”

    In quantum computers, the processing of information is an extremely delicate process performed by the fragile qubits, which are highly susceptible to decoherence, the loss of their quantum mechanical behavior. In previous research conducted by Sung and the research group he works with, MIT Engineering Quantum Systems, tunable couplers were proposed, allowing researchers to turn two-qubit interactions on and off to control their operations while preserving the fragile qubits. The tunable coupler idea represented a significant advance and was cited, for example, by Google as being key to their recent demonstration of the advantage that quantum computing holds over classical computing.

    Still, addressing error mechanisms is like peeling an onion: Peeling one layer reveals the next. In this case, even when using tunable couplers, the two-qubit gates were still prone to errors that resulted from residual unwanted interactions between the two qubits and between the qubits and the coupler. Such unwanted interactions were generally ignored prior to tunable couplers, as they did not stand out — but now they do. And, because such residual errors increase with the number of qubits and gates, they stand in the way of building larger-scale quantum processors. The Physical Review X paper provides a new approach to reduce such errors.

    “We have now taken the tunable coupler concept further and demonstrated near 99.9 percent fidelity for the two major types of two-qubit gates, known as Controlled-Z gates and iSWAP gates,” says William D. Oliver, an associate professor of electrical engineering and computer science, MIT Lincoln Laboratory fellow, director of the Center for Quantum Engineering, and associate director of the Research Laboratory of Electronics, home of the Engineering Quantum Systems group. “Higher-fidelity gates increase the number of operations one can perform, and more operations translates to implementing more sophisticated algorithms at larger scales.”

    To eliminate the error-provoking qubit-qubit interactions, the researchers harnessed higher energy levels of the coupler to cancel out the problematic interactions. In previous work, such energy levels of the coupler were ignored, although they induced non-negligible two-qubit interactions.

    “Better control and design of the coupler is a key to tailoring the qubit-qubit interaction as we desire. This can be realized by engineering the multilevel dynamics that exist,” Sung says.

    The next generation of quantum computers will be error-corrected, meaning that additional qubits will be added to improve the robustness of quantum computation.

    “Qubit errors can be actively addressed by adding redundancy,” says Oliver, pointing out, however, that such a process only works if the gates are sufficiently good — above a certain fidelity threshold that depends on the error correction protocol. “The most lenient thresholds today are around 99 percent. However, in practice, one seeks gate fidelities that are much higher than this threshold to live with reasonable levels of hardware redundancy.”

    The devices used in the research, made at MIT’s Lincoln Laboratory, were fundamental to achieving the demonstrated gains in fidelity in the two-qubit operations, Oliver says.

    “Fabricating high-coherence devices is step one to implementing high-fidelity control,” he says.

    Sung says “high rates of error in two-qubit gates significantly limit the capability of quantum hardware to run quantum applications that are typically hard to solve with classical computers, such as quantum chemistry simulation and solving optimization problems.”

    Up to this point, only small molecules have been simulated on quantum computers, simulations that can easily be performed on classical computers.

    “In this sense, our new approach to reduce the two-qubit gate errors is timely in the field of quantum computation and helps address one of the most critical quantum hardware issues today,” he says.

    See the full article here .


    five-ways-keep-your-child-safe-school-shootings
    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, MIT 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 MIT. The university also has a strong entrepreneurial culture and MIT alumni have founded or co-founded many notable companies. MIT 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 MIT 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.

    MIT 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, MIT 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 MIT 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, MIT 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 MIT 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.

    MIT’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 MIT’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, MIT 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 MIT 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 MIT 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, MIT 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 MIT’s defense research. In this period MIT’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. MIT ultimately divested itself from the Instrumentation Laboratory and moved all classified research off-campus to the MIT (US) Lincoln Laboratoryfacility 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 MIT 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 MIT over its involvement in SDI (space weaponry) and CBW (chemical and biological warfare) research. More recently, MIT’s research for the military has included work on robots, drones and ‘battle suits’.

    Recent history

    MIT 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 MIT 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.

    MIT 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, MIT 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, MIT 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 MIT faculty adopted an open-access policy to make its scholarship publicly accessible online.

    MIT 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 MIT community with thousands of police officers from the New England region and Canada. On November 25, 2013, MIT 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 MIT 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), MIT, 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 MIT physicist Rainer Weiss won the Nobel Prize in physics in 2017. Weiss, who is also an MIT 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 8:13 am on June 14, 2021 Permalink | Reply
    Tags: "The road ahead- Raquel Urtasun's startup to ‘unleash full power of AI’ on self-driving cars", , , , Computer Science, , Women in STEM-Raquel Urtasun   

    From University of Toronto (CA) : Women in STEM-Raquel Urtasun “The road ahead- Raquel Urtasun’s startup to ‘unleash full power of AI’ on self-driving cars” 

    From University of Toronto (CA)

    June 10, 2021
    Rahul Kalvapalle

    1
    Raquel Urtasun, a U of T professor of computer science and world-leading expert in machine learning and computer vision, has launched her own Toronto-based, self-driving vehicle company with more than $100 million in funding (photo by Natalia Dolan)

    More than $100-million in funding. Two decades of artificial intelligence expertise. Ten years of experience in self-driving technology. A 40-strong team of scientists and engineers.

    The list of resources at Raquel Urtasun’s fingertips as she takes the wheel of Waabi, an autonomous vehicle startup, is impressive to say the least. The goal? Use AI to finally resolve the technical and financial challenges that have hindered the full commercialization of self-driving technology.

    It’s the first foray into entrepreneurship for Urtasun, a professor of computer science at the University of Toronto and one of the world’s leading experts in machine learning and computer vision. She says she was inspired to start her own company after four years as chief scientist and head of Uber ATG’s self-driving car lab in Toronto, where she realized need for a new generation of self-driving technologies that leverage AI’s full potential.

    “The thought of what would be the best way to do this grew and grew in my head until it became clear that, if you really want to change technology, the best way to do it is to start a new company,” Urtasun says.

    Urtasun’s new venture emerged from stealth mode earlier this week to announce one of the largest rounds of initial financing ever secured by a Canadian startup, raising more than $100 million from investors including Silicon Valley-based Khosla Ventures and Uber. Other investors include fellow U of T AI luminaries Geoffrey Hinton, a University Professor Emeritus, and Sanja Fidler, an associate professor of computer science, as well as Stanford University’s Fei-Fei Li and Pieter Abbeel of the University of California, Berkeley.

    Urtasun says the self-driving industry’s current players aren’t taking full advantage of the power of AI.

    “There is a little bit of AI there, but it doesn’t have a prominent role. Instead, it’s solving very specific sub-problems within the massive software stack – or brain of the self-driving car,” she says. “This causes difficulty in that it requires really complex, time-consuming manual tuning.

    “As a consequence of this, scaling the technology is costly and technically very challenging.”

    Waabi addresses this by utilizing “deep learning, probabilistic inference and complex optimization” to create a new class of algorithms, the likes of which Urtasun says have never been seen before in industry or academia.

    Key to Waabi’s approach is its novel autonomous system – essentially, the software brain of the self-driving vehicle – that is “end-to-end trainable,” meaning the entire software stack can automatically learn from data, removing the need for constant manual tuning and tweaking.

    The system is also “interpretable and explainable,” meaning it’s possible to deduce why it opts for certain manoeuvers over others – crucial for safety verification.

    It’s also capable of complex reasoning, which Urtasun says is vital for eventual real-world applications.

    “If you think about when you’re driving and arrive at an intersection, there’s a lot of things happening in your brain – you do very complex inference about what everybody’s doing at the intersection, how it will affect you, etc.” Urtasun says. “That’s what our new generation of algorithms provides – this ability to do really complex reasoning within the AI system.”

    Waabi also has a revolutionary simulator system that can test the algorithms and software with “an unprecedented level of fidelity,” Urtasun says.

    “When people in the industry say they test millions of miles of simulation, they’re really only testing the motion-planning component – which is one piece among this big software stack,” she says.

    “Waabi has the ability to simulate how the world looks at scale, how sensors observe the scene and the behaviours of humans in a way that’s very realistic and in real time.”

    That means significantly fewer hours of on-road drive testing.

    “Typically, companies have hundreds of vehicles that they’re driving so that they can observe how the system works. And every time you change something, you change the behaviour, so you have to drive again and again and again,” Urtasun says. “[Waabi] can develop, test in simulation and reduce the need for driving in the real-world.”

    It also means a system that’s safer because it can be trained to manage not only typical driving scenarios, but also ‘edge cases’ – situations that arise at extreme operating parameters.

    “We can train the system to handle those edge cases in simulation,” Urtasun says. “So, you end up with a system that is much safer, that you can develop faster and that requires less capital to develop because you need very few people compared to the traditional approach – and less testing in the real world.

    “[You] really unleash the power of AI.”

    The company’s name reflects its approach. “Waabi” means “she has vision” in Ojibwe (“a new vision to help solve self-driving,” Urtasun says) and means “simple” in Japanese – an ode to the simplicity of the software stack.

    “[It’s] a perfect definition of our technology and a perfect name for our company,” Urtasun says. “Plus, it sounds cool.”

    The potential applications for Waabi’s technology are wide-ranging, Urtasun says, but the initial focus will be the long-haul trucking sector – a departure from her time at Uber, where she worked on passenger vehicles. She notes that truck-driving is recognized as one of the most dangerous occupations, and that the industry suffers from a shortage of drivers. “Automation can serve those industry needs,” she says.

    Urtasun adds that long-haul trucking is also a prudent area to focus on because there’s less complexity involved with highway driving than is the case in cities.

    “Highways are still very difficult – don’t get me wrong – but they’re less complex compared to a city like Toronto, with all the things that might happen and how people follow the rules – well, very few people follow the rules. So, you need to handle all that complexity.”

    Toronto’s notoriously bad traffic aside, Urtasun says there’s nowhere else she’d rather set up an AI company.

    “When people ask me, ‘Why here?’ I say, ‘Why not?’ I love Toronto, I love Canada. It’s an amazing place to do innovation – there’s incredible talent and support from the government,” she says, pointing to Toronto’s emergence as a world-leading AI hub thanks to initiatives such as the Vector Institute for Artificial Intelligence, which she co-founded.

    “It’s been incredible to see the transformation that the city has gone through,” she says. “It was the case that people were leaving and going to California. Now, not only are we retaining talent but so much incredible talent is coming in – even from Silicon Valley,”

    There’s also plenty of talent to be tapped at U of T, Urtasun adds.

    “We have amazing U of T students who are doing great work within the company,” she says. “I really look forward to partnering closely with U of T to provide opportunities to the incredible talent that the university has. For me, it’s always been very important to [help develop] students – so that continues to be the case.”

    As the CEO of an AI-powered autonomous vehicle startup, Urtasun says it’s important for her to set an example for women and girls interested in pursuing careers in technology.

    “I think it’s very important that young girls, in particular, realize that this is not a man’s world. Technology is going to change the world and they definitely have a say,” she says.

    She adds Waabi and other technology companies benefit immensely from diverse leadership and perspectives – and so do their customers.

    “It’s important that in order to solve complex problems, we have diversity of opinions, approaches and backgrounds,” she says. “Waabi excels at all three types of diversity, which I think is the way to build incredible technology as well as showcase the diversity of the users who are going to use the technology at the end of the day.”

    See the full article here .


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

    Please help promote STEM in your local schools.

    Stem Education Coalition

    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 12:15 pm on February 13, 2021 Permalink | Reply
    Tags: "‘Multiplying’ light could be key to ultra-powerful optical computers", An optical computer would be superfast energy-efficient and able to process information simultaneously through multiple temporal or spatial optical channels., , Computer Science, From University of Cambridge (UK), , Optical or photonic computing uses photons produced by lasers or diodes for computation as opposed to classical computers which use electrons., Optical or photonic computing uses photons produced by lasers or diodes for computation., , We should start identifying different classes of problems that can be solved directly by a dedicated physical processor.   

    From University of Cambridge (UK): “‘Multiplying’ light could be key to ultra-powerful optical computers” 

    U Cambridge bloc

    From University of Cambridge (UK)

    08 Feb 2021
    Sarah Collins

    New type of optical computing could solve highly complex problems that are out of reach for even the most powerful supercomputers.

    1
    Artist’s impression of light pulses inside an optical computer. Credit: Gleb Berloff/Hills Road Sixth Form College.

    An important class of challenging computational problems, with applications in graph theory, neural networks, artificial intelligence and error-correcting codes can be solved by multiplying light signals, according to researchers from the University of Cambridge and Skolkovo Institute of Science and Technology in Russia.

    In a paper published in the journal Physical Review Letters, they propose a new type of computation that could revolutionise analogue computing by dramatically reducing the number of light signals needed while simplifying the search for the best mathematical solutions, allowing for ultra-fast optical computers.

    Optical or photonic computing uses photons produced by lasers or diodes for computation, as opposed to classical computers which use electrons. Since photons are essentially without mass and can travel faster than electrons, an optical computer would be superfast, energy-efficient and able to process information simultaneously through multiple temporal or spatial optical channels.

    The computing element in an optical computer – an alternative to the ones and zeroes of a digital computer – is represented by the continuous phase of the light signal, and the computation is normally achieved by adding two light waves coming from two different sources and then projecting the result onto ‘0’ or ‘1’ states.

    However, real life presents highly nonlinear problems, where multiple unknowns simultaneously change the values of other unknowns while interacting multiplicatively. In this case, the traditional approach to optical computing that combines light waves in a linear manner fails.

    Now, Professor Natalia Berloff from Cambridge’s Department of Applied Mathematics and Theoretical Physics and PhD student Nikita Stroev from Skolkovo Institute of Science and Technology [Сколковский институт науки и технологий] (RU)] have found that optical systems can combine light by multiplying the wave functions describing the light waves instead of adding them and may represent a different type of connections between the light waves.

    They illustrated this phenomenon with quasi-particles called polaritons – which are half-light and half-matter – while extending the idea to a larger class of optical systems such as light pulses in a fibre. Tiny pulses or blobs of coherent, superfast-moving polaritons can be created in space and overlap with one another in a nonlinear way, due to the matter component of polaritons.

    “We found the key ingredient is how you couple the pulses with each other,” said Stroev. “If you get the coupling and light intensity right, the light multiplies, affecting the phases of the individual pulses, giving away the answer to the problem. This makes it possible to use light to solve nonlinear problems.”

    The multiplication of the wave functions to determine the phase of the light signal in each element of these optical systems comes from the nonlinearity that occurs naturally or is externally introduced into the system.

    “What came as a surprise is that there is no need to project the continuous light phases onto ‘0’ and ‘1’ states necessary for solving problems in binary variables,” said Stroev. “Instead, the system tends to bring about these states at the end of its search for the minimum energy configuration. This is the property that comes from multiplying the light signals. On the contrary, previous optical machines require resonant excitation that fixes the phases to binary values externally.”

    The authors have also suggested and implemented a way to guide the system trajectories towards the solution by temporarily changing the coupling strengths of the signals.

    “We should start identifying different classes of problems that can be solved directly by a dedicated physical processor,” said Berloff, who also holds a position at Skolkovo Institute of Science and Technology. “Higher-order binary optimisation problems are one such class, and optical systems can be made very efficient in solving them.”

    There are still many challenges to be met before optical computing can demonstrate its superiority in solving hard problems in comparison with modern electronic computers: noise reduction, error correction, improved scalability, guiding the system to the true best solution are among them.

    “Changing our framework to directly address different types of problems may bring optical computing machines closer to solving real-world problems that cannot be solved by classical computers,” said Berloff.

    See the full article here .

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

    Please help promote STEM in your local schools.

    Stem Education Coalition

    U Cambridge Campus

    The University of Cambridge (UK) (abbreviated as Cantab in post-nominal letters) is a collegiate public research university in Cambridge, England. Founded in 1209, Cambridge is the second-oldest university in the English-speaking world and the world’s fourth-oldest surviving university. It grew out of an association of scholars who left the University of Oxford after a dispute with townsfolk. The two ancient universities share many common features and are often jointly referred to as “Oxbridge”.

    Cambridge is formed from a variety of institutions which include 31 constituent colleges and over 100 academic departments organised into six schools. The university occupies buildings throughout the town, many of which are of historical importance. The colleges are self-governing institutions founded as integral parts of the university. In the year ended 31 July 2014, the university had a total income of £1.51 billion, of which £371 million was from research grants and contracts. The central university and colleges have a combined endowment of around £4.9 billion, the largest of any university outside the United States. Cambridge is a member of many associations and forms part of the “golden triangle” of leading English universities and Cambridge University Health Partners, an academic health science centre. The university is closely linked with the development of the high-tech business cluster known as “Silicon Fen”.

     
  • richardmitnick 9:16 am on February 11, 2021 Permalink | Reply
    Tags: "Nanowire could provide a stable easy-to-make superconducting transistor", , Computer Science, Cryotron reboot, , In 1956 MIT electrical engineer Dudley Buck published a description of a superconducting computer switch called the cryotron., Josephson junction — essentially two superconductors separated by a thin insulator., , , , Superconductors — materials that conduct electricity without resistance — are remarkable., The nano-cryotron uses heat to trigger a switch rather than a magnetic field.   

    From MIT: “Nanowire could provide a stable easy-to-make superconducting transistor” 

    MIT News

    From MIT News

    February 11, 2021
    Daniel Ackerman

    Inspired by decades-old MIT research, the new technology could boost quantum computers and other superconducting electronics.

    1
    MIT researchers are developing a superconducting nanowire, which could enable more efficient superconducting electronics.
    Credits: Christine Daniloff/MIT.

    Superconductors — materials that conduct electricity without resistance — are remarkable. They provide a macroscopic glimpse into quantum phenomena, which are usually observable only at the atomic level. Beyond their physical peculiarity, superconductors are also useful. They’re found in medical imaging, quantum computers, and cameras used with telescopes.

    But superconducting devices can be finicky. Often, they’re expensive to manufacture and prone to err from environmental noise. That could change, thanks to research from Karl Berggren’s group in the Department of Electrical Engineering and Computer Science.

    The researchers are developing a superconducting nanowire, which could enable more efficient superconducting electronics. The nanowire’s potential benefits derive from its simplicity, says Berggren. “At the end of the day, it’s just a wire.”

    Berggren will present a summary of the research at this month’s IEEE Solid-state Circuits Conference.

    Resistance is futile

    Most metals lose resistance and become superconducting at extremely low temperatures, usually just a few degrees above absolute zero. They’re used to sense magnetic fields, especially in highly sensitive situations like monitoring brain activity. They also have applications in both quantum and classical computing.

    Underlying many of these superconductors is a device invented in the 1960s called the Josephson junction — essentially two superconductors separated by a thin insulator. “That’s what led to conventional superconducting electronics, and then ultimately to the superconducting quantum computer,” says Berggren.

    However, the Josephson junction “is fundamentally quite a delicate object,” Berggren adds. That translates directly into cost and complexity of manufacturing, especially for the thin insulating later. Josephson junction-based superconductors also may not play well with others: “If you try to interface it with conventional electronics, like the kinds in our phones or computers, the noise from those just swamps the Josephson junction. So, this lack of ability to control larger-scale objects is a real disadvantage when you’re trying to interact with the outside world.”

    To overcome these disadvantages, Berggren is developing a new technology — the superconducting nanowire — with roots older than the Josephson junction itself.

    Cryotron reboot

    In 1956, MIT electrical engineer Dudley Buck published a description of a superconducting computer switch called the cryotron. The device was little more than two superconducting wires: One was straight, and the other was coiled around it. The cryotron acts as a switch, because when current flows through the coiled wire, its magnetic field reduces the current flowing through the straight wire.

    At the time, the cryotron was much smaller than other types of computing switches, like vacuum tubes or transistors, and Buck thought the cryotron could become the building block of computers. But in 1959, Buck died suddenly at age 32, halting the development of the cryotron. (Since then, transistors have been scaled to microscopic sizes and today make up the core logic components of computers.)

    Now, Berggren is rekindling Buck’s ideas about superconducting computer switches. “The devices we’re making are very much like cryotrons in that they don’t require Josephson junctions,” he says. He dubbed his superconducting nanowire device the nano-cryotron in tribute to Buck — though it works a bit differently than the original cryotron.

    The nano-cryotron uses heat to trigger a switch, rather than a magnetic field. In Berggren’s device, current runs through a superconducting, supercooled wire called the “channel.” That channel is intersected by an even smaller wire called a “choke” — like a multilane highway intersected by a side road. When current is sent through the choke, its superconductivity breaks down and it heats up. Once that heat spreads from the choke to the main channel, it causes the main channel to also lose its superconducting state.

    Berggren’s group has already demonstrated proof-of-concept for the nano-cryotron’s use as an electronic component. A former student of Berggren’s, Adam McCaughan, developed a device that uses nano-cryotrons to add binary digits. And Berggren has successfully used nano-cryotrons as an interface between superconducting devices and classical, transistor-based electronics.

    Berggren says his group’s superconducting nanowire could one day complement — or perhaps compete with — Josephson junction-based superconducting devices. “Wires are relatively easy to make, so it may have some advantages in terms of manufacturability,” he says.

    He thinks the nano-cryotron could one day find a home in superconducting quantum computers and supercooled electronics for telescopes. Wires have low power dissipation, so they may also be handy for energy-hungry applications, he says. “It’s probably not going to replace the transistors in your phone, but if it could replace the transistor in a server farm or data center? That would be a huge impact.”

    Beyond specific applications, Berggren takes a broad view of his work on superconducting nanowires. “We’re doing fundamental research, here. While we’re interested in applications, we’re just also interested in: What are some different kinds of ways to do computing? As a society, we’ve really focused on semiconductors and transistors. But we want to know what else might be out there.”

    Initial funding for nano-cryotron research in the Berggren lab was provided by the National Science Foundation.

    See the full article here .


    five-ways-keep-your-child-safe-school-shootings
    Please help promote STEM in your local schools.


    Stem Education Coalition

    MIT Seal

    The mission of MIT 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 MIT community the ability and passion to work wisely, creatively, and effectively for the betterment of humankind.

    USPS “Forever” postage stamps celebrating Innovation at MIT.

    MIT Campus

     
  • richardmitnick 4:42 pm on February 4, 2021 Permalink | Reply
    Tags: "Chemistry and computer science join forces to apply artificial intelligence to chemical reactions", (BO) allows faster and more efficient syntheses of chemicals., , , Bayesian Optimization (BO)-a widely used strategy in the sciences., , Computer Science, , Reaction optimization is ubiquitous in chemical synthesis both in academia and across the chemical industry., The real strength of Bayesian Optimization is that it allows us to model high-dimensional problems and capture trends that we may not see in the data so it can process the data a lot better.   

    From Princeton University: “Chemistry and computer science join forces to apply artificial intelligence to chemical reactions” 

    Princeton University
    From Princeton University

    Feb. 3, 2021
    Wendy Plump, Department of Chemistry

    In the past few years, researchers have turned increasingly to data science techniques to aid problem-solving in organic synthesis.

    Researchers in the lab of Abigail Doyle, Princeton’s A. Barton Hepburn Professor of Chemistry, have developed open-source software that provides them with a state-of-the-art optimization algorithm to use in everyday work, folding what’s been learned in the machine learning field into synthetic chemistry.

    1
    Princeton chemists Benjamin Shields and Abigail Doyle worked with computer scientist Ryan Adams (not pictured) to create machine learning software that can optimize reactions — using artificial intelligence to speed through thousands of reactions that chemists used to have to labor through one by one. Credit: C. Todd Reichart, Department of Chemistry.

    The software adapts key principles of Bayesian Optimization (BO) to allow faster and more efficient syntheses of chemicals.

    Based on the Bayes Theorem, a mathematical formula for determining conditional probability, BO is a widely used strategy in the sciences. Broadly defined, it allows people and computers use prior knowledge to inform and optimize future decisions.

    The chemists in Doyle’s lab, in collaboration with Ryan Adams, a professor of computer science, and colleagues at Bristol-Myers Squibb, compared human decision-making capabilities with the software package. They found that the optimization tool yields both greater efficiency over human participants and less bias on a test reaction. Their work appears in the current issue of the journal Nature.

    “Reaction optimization is ubiquitous in chemical synthesis, both in academia and across the chemical industry,” said Doyle. “Since chemical space is so large, it is impossible for chemists to evaluate the entirety of a reaction space experimentally. We wanted to develop and assess BO as a tool for synthetic chemistry given its success for related optimization problems in the sciences.”

    Benjamin Shields, a former postdoctoral fellow in the Doyle lab and the paper’s lead author, created the Python package.

    “I come from a synthetic chemistry background, so I definitely appreciate that synthetic chemists are pretty good at tackling these problems on their own,” said Shields. “Where I think the real strength of Bayesian Optimization comes in is that it allows us to model these high-dimensional problems and capture trends that we may not see in the data ourselves, so it can process the data a lot better.

    “And two, within a space, it will not be held back by the biases of a human chemist,” he added.

    How it works

    The software started as an out-of-field project to fulfill Shields’ doctoral requirements. Doyle and Shield then formed a team under the Center for Computer Assisted Synthesis (C-CAS), a National Science Foundation initiative launched at five universities to transform how the synthesis of complex organic molecules is planned and executed. Doyle has been a principal investigator with C-CAS since 2019.

    “Reaction optimization can be an expensive and time-consuming process,” said Adams, who is also the director of the Program in Statistics and Machine Learning. “This approach not only accelerates it using state-of-the-art techniques, but also finds better solutions than humans would typically identify. I think this is just the beginning of what’s possible with Bayesian Optimization in this space.”

    Users start by defining a search space — plausible experiments to consider — such as a list of catalysts, reagents, ligands, solvents, temperatures, and concentrations. Once that space is prepared and the user defines how many experiments to run, the software chooses initial experimental conditions to be evaluated. Then it suggests new experiments to run, iterating through a smaller and smaller cast of choices until the reaction is optimized.

    “In designing the software, I tried to include ways for people to kind of inject what they know about a reaction,” said Shields. “No matter how you use this or machine learning in general, there’s always going to be a case where human expertise is valuable.”

    The software and examples for its use can be accessed at this repository. GitHub links are available for the following: software that represents the chemicals under evaluation in a machine-readable format via density-functional theory; software for reaction optimization; and the game that collects chemists’ decision-making on optimization of the test reaction.

    See the full article here .

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    About Princeton: Overview

    Princeton University is a vibrant community of scholarship and learning that stands in the nation’s service and in the service of all nations. Chartered in 1746, Princeton is the fourth-oldest college in the United States. Princeton is an independent, coeducational, nondenominational institution that provides undergraduate and graduate instruction in the humanities, social sciences, natural sciences and engineering.

    As a world-renowned research university, Princeton seeks to achieve the highest levels of distinction in the discovery and transmission of knowledge and understanding. At the same time, Princeton is distinctive among research universities in its commitment to undergraduate teaching.

    Today, more than 1,100 faculty members instruct approximately 5,200 undergraduate students and 2,600 graduate students. The University’s generous financial aid program ensures that talented students from all economic backgrounds can afford a Princeton education.

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  • richardmitnick 5:30 pm on January 27, 2021 Permalink | Reply
    Tags: "Mira’s Last Journey: exploring the dark universe", , , , Computer Science, , , , The Last Journey. I. An extreme-scale simulation on the Mira supercomputer.   

    From DOE’s Argonne National Laboratory: “Mira’s Last Journey: exploring the dark universe” 

    Argonne Lab
    News from From DOE’s Argonne National Laboratory

    January 27, 2021
    Savannah Mitchem

    A massive simulation of the cosmos and a nod to the next generation of computing.

    1
    Visualization of the Last Journey simulation. Shown is the large-scale structure of the universe as a thin slice through the full simulation (lower left) and zoom-ins at different levels. The lower right panel shows one of the largest structures in the simulation. Credit: Argonne National Laboratory.

    A team of physicists and computer scientists from the U.S. Department of Energy’s (DOE) Argonne National Laboratory performed one of the five largest cosmological simulations ever. Data from the simulation will inform sky maps to aid leading large-scale cosmological experiments.

    The simulation, called the Last Journey, follows the distribution of mass across the universe over time — in other words, how gravity causes a mysterious invisible substance called Dark Matter to clump together to form larger-scale structures called halos, within which galaxies form and evolve.

    Caterpillar Project A Milky-Way-size dark-matter halo and its subhalos circled, an enormous suite of simulations . Griffen et al. 2016.

    The scientists performed the simulation on Argonne’s supercomputer Mira. The same team of scientists ran a previous cosmological simulation called the Outer Rim in 2013, just days after Mira turned on. After running simulations on the machine throughout its seven-year lifetime, the team marked Mira’s retirement with the Last Journey simulation.

    ANL ALCF MIRA IBM Blue Gene Q supercomputer at the Argonne Leadership Computing Facility.

    The Last Journey demonstrates how far observational and computational technology has come in just seven years, and it will contribute data and insight to experiments such as the Stage-4 ground-based cosmic microwave background experiment (CMB-S4), the Legacy Survey of Space and Time (carried out by the Rubin Observatory in Chile), the Dark Energy Spectroscopic Instrument and two NASA missions, the Roman Space Telescope and SPHEREx.

    NOIRLab Vera C. Rubin Observatory Telescope currently under construction on the El Peñón peak at Cerro Pachón Chile, a 2,682-meter-high mountain in Coquimbo Region, in northern Chile, alongside the existing Gemini South and Southern Astrophysical Research Telescopes, altitude 2,715 m (8,907 ft).

    LBNL/DESI spectroscopic instrument on the Mayall 4-meter telescope at Kitt Peak National Observatory, in the Quinlan Mountains in the Arizona-Sonoran Desert on the Tohono O’odham Nation, 88 kilometers 55 mi west-southwest of Tucson, Arizona, Altitude 2,096 m (6,877 ft).

    NOIRLab NOAO/Mayall 4 m telescope at Kitt Peak, Arizona, USA, at Kitt Peak National Observatory, in the Quinlan Mountains in the Arizona-Sonoran Desert on the Tohono O’odham Nation, 88 kilometers 55 mi west-southwest of Tucson, Arizona, Altitude 2,096 m (6,877 ft).

    Kitt Peak NOIRLab National Observatory of the Quinlan Mountains in the Arizona-Sonoran Desert on the Tohono O’odham Nation, 88 kilometers 55 mi west-southwest of Tucson, Arizona, Altitude 2,096 m (6,877 ft), annotated.

    NASA Nancy Grace Roman Space Telescope depiction.

    NASA’s SPHEREx Spectro-Photometer for the History of the Universe, Epoch of Reionization and Ices Explorer depiction. Credit: Caltech.

    “We worked with a tremendous volume of the universe, and we were interested in large-scale structures, like regions of thousands or millions of galaxies, but we also considered dynamics at smaller scales,” said Katrin Heitmann, deputy division director for Argonne’s High Energy Physics (HEP) division.

    The code that constructed the cosmos

    The six-month span for the Last Journey simulation and major analysis tasks presented unique challenges for software development and workflow. The team adapted some of the same code used for the 2013 Outer Rim simulation with some significant updates to make efficient use of Mira, an IBM Blue Gene/Q system that was housed at the Argonne Leadership Computing Facility (ALCF), a DOE Office of Science User Facility.

    ANL/ALCF

    Specifically, the scientists used the Hardware/Hybrid Accelerated Cosmology Code (HACC) and its analysis framework, CosmoTools, to enable incremental extraction of relevant information at the same time as the simulation was running.

    “Running the full machine is challenging because reading the massive amount of data produced by the simulation is computationally expensive, so you have to do a lot of analysis on the fly,” said Heitmann. ​“That’s daunting, because if you make a mistake with analysis settings, you don’t have time to redo it.”

    The team took an integrated approach to carrying out the workflow during the simulation. HACC would run the simulation forward in time, determining the effect of gravity on matter during large portions of the history of the universe. Once HACC determined the positions of trillions of computational particles representing the overall distribution of matter, CosmoTools would step in to record relevant information — such as finding the billions of halos that host galaxies — to use for analysis during post-processing.

    “When we know where the particles are at a certain point in time, we characterize the structures that have formed by using CosmoTools and store a subset of data to make further use down the line,” said Adrian Pope, physicist and core HACC and CosmoTools developer in Argonne’s Computational Science (CPS) division. ​“If we find a dense clump of particles, that indicates the location of a dark matter halo, and galaxies can form inside these dark matter halos.”

    The scientists repeated this interwoven process — where HACC moves particles and CosmoTools analyzes and records specific data — until the end of the simulation. The team then used features of CosmoTools to determine which clumps of particles were likely to host galaxies. For reference, around 100 to 1,000 particles represent single galaxies in the simulation.

    “We would move particles, do analysis, move particles, do analysis,” said Pope. ​“At the end, we would go back through the subsets of data that we had carefully chosen to store and run additional analysis to gain more insight into the dynamics of structure formation, such as which halos merged together and which ended up orbiting each other.”

    Using the optimized workflow with HACC and CosmoTools, the team ran the simulation in half the expected time.

    Community contribution

    The Last Journey simulation will provide data necessary for other major cosmological experiments to use when comparing observations or drawing conclusions about a host of topics. These insights could shed light on topics ranging from cosmological mysteries, such as the role of dark matter and dark energy in the evolution of the universe, to the astrophysics of galaxy formation across the universe.

    “This huge data set they are building will feed into many different efforts,” said Katherine Riley, director of science at the ALCF. ​“In the end, that’s our primary mission — to help high-impact science get done. When you’re able to not only do something cool, but to feed an entire community, that’s a huge contribution that will have an impact for many years.”

    The team’s simulation will address numerous fundamental questions in cosmology and is essential for enabling the refinement of existing models and the development of new ones, impacting both ongoing and upcoming cosmological surveys.

    “We are not trying to match any specific structures in the actual universe,” said Pope. ​“Rather, we are making statistically equivalent structures, meaning that if we looked through our data, we could find locations where galaxies the size of the Milky Way would live. But we can also use a simulated universe as a comparison tool to find tensions between our current theoretical understanding of cosmology and what we’ve observed.”

    Looking to exascale

    “Thinking back to when we ran the Outer Rim simulation, you can really see how far these scientific applications have come,” said Heitmann, who performed Outer Rim in 2013 with the HACC team and Salman Habib, CPS division director and Argonne Distinguished Fellow. ​“It was awesome to run something substantially bigger and more complex that will bring so much to the community.”

    As Argonne works towards the arrival of Aurora, the ALCF’s upcoming exascale supercomputer, the scientists are preparing for even more extensive cosmological simulations.

    Depiction of ANL ALCF Cray Intel SC18 Shasta Aurora exascale supercomputer, being built at DOE’s Argonne National Laboratory.

    Exascale computing systems will be able to perform a billion billion calculations per second — 50 times faster than many of the most powerful supercomputers operating today.

    “We’ve learned and adapted a lot during the lifespan of Mira, and this is an interesting opportunity to look back and look forward at the same time,” said Pope. ​“When preparing for simulations on exascale machines and a new decade of progress, we are refining our code and analysis tools, and we get to ask ourselves what we weren’t doing because of the limitations we have had until now.”

    The Last Journey was a gravity-only simulation, meaning it did not consider interactions such as gas dynamics and the physics of star formation. Gravity is the major player in large-scale cosmology, but the scientists hope to incorporate other physics in future simulations to observe the differences they make in how matter moves and distributes itself through the universe over time.

    “More and more, we find tightly coupled relationships in the physical world, and to simulate these interactions, scientists have to develop creative workflows for processing and analyzing,” said Riley. ​“With these iterations, you’re able to arrive at your answers — and your breakthroughs — even faster.”

    A paper on the simulation, titled ​The Last Journey. I. An extreme-scale simulation on the Mira supercomputer, was published on Jan. 27 in The Astrophysical Journal Supplement Series. The scientists are currently preparing follow-up papers to generate detailed synthetic sky catalogs.

    The work was a multidisciplinary collaboration between high energy physicists and computer scientists from across Argonne and researchers from Los Alamos National Laboratory.

    Funding for the simulation is provided by DOE’s Office of Science.

    See the full article here .

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    Argonne National Laboratory seeks solutions to pressing national problems in science and technology. The nation’s first national laboratory, Argonne conducts leading-edge basic and applied scientific research in virtually every scientific discipline. Argonne researchers work closely with researchers from hundreds of companies, universities, and federal, state and municipal agencies to help them solve their specific problems, advance America’s scientific leadership and prepare the nation for a better future. With employees from more than 60 nations, Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science. For more visit http://www.anl.gov.

    About the Advanced Photon Source

    The U. S. Department of Energy Office of Science’s Advanced Photon Source (APS) at Argonne National Laboratory is one of the world’s most productive X-ray light source facilities. The APS provides high-brightness X-ray beams to a diverse community of researchers in materials science, chemistry, condensed matter physics, the life and environmental sciences, and applied research. These X-rays are ideally suited for explorations of materials and biological structures; elemental distribution; chemical, magnetic, electronic states; and a wide range of technologically important engineering systems from batteries to fuel injector sprays, all of which are the foundations of our nation’s economic, technological, and physical well-being. Each year, more than 5,000 researchers use the APS to produce over 2,000 publications detailing impactful discoveries, and solve more vital biological protein structures than users of any other X-ray light source research facility. APS scientists and engineers innovate technology that is at the heart of advancing accelerator and light-source operations. This includes the insertion devices that produce extreme-brightness X-rays prized by researchers, lenses that focus the X-rays down to a few nanometers, instrumentation that maximizes the way the X-rays interact with samples being studied, and software that gathers and manages the massive quantity of data resulting from discovery research at the APS.

    This research used resources of the Advanced Photon Source, a U.S. DOE Office of Science User Facility operated for the DOE Office of Science by Argonne National Laboratory under Contract No. DE-AC02-06CH11357.
    Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science

    Argonne Lab Campus

     
  • richardmitnick 11:13 pm on January 20, 2021 Permalink | Reply
    Tags: "m-bits", "Silicon memory?", , , Computer Science, , , , Metamaterial can be reprogrammed with different properties., Metamaterials=“beyond matter”- engineered materials with properties not found in nature., You can activate and deactivate individual cells by applying a magnetic field.   

    From École Polytechnique Fédérale de Lausanne (CH) via COSMOS (AU): “Silicon memory?” 


    From École Polytechnique Fédérale de Lausanne (CH)

    via

    Cosmos Magazine bloc

    COSMOS (AU)

    21 January 2021
    Deborah Devis

    Metamaterial can be reprogrammed with different properties.

    1
    Credit: Matejmo / Getty Images.

    If you need a material that can literally be changed to suit you over time, look no further.

    Metamaterials – meaning “beyond matter” – are engineered materials with properties not found in nature. This gives them unique scope to work outside of the realms of “normal” acquired materials.

    One such example has recently been reported in Nature by Tian Chen, of École Polytechnique Fédérale de Lausanne, Switzerland, who designed a metamaterial that can be reprogrammed to have different mechanical properties after it is already made.

    “I wondered if there was a way to change the internal geometry of a material’s structure after it’s been created,” says Chen. “The idea was to develop a single material that can display a range of physical properties, like stiffness and strength, so that materials don’t have to be replaced each time.

    “For example, when you twist your ankle, you initially have to wear a stiff splint to hold the ankle in place. Then as it heals, you can switch to a more flexible one. Today you have to replace the entire splint, but the hope is that one day, a single material can serve both functions.”

    The material is made of small mechanical bits, called m-bits, that are reminiscent of computer bits.

    In a hard drive, tiny pieces of digital information can be stored as bits. Magnetic bits can be programmed to switch between the values of 0 and 1, or on/off, by magnetising them in different directions to confer binary information. That binary code can be controlled by an external electromagnetic circuit, which changes the direction of those bits to recode the hard driver with a new memory.

    So, if you’re storing your favourite song on a hard drive, the direction of those bits change based on the code that is imparted, and the digital properties of the hard-drive are altered to include the memory of how to play your song.

    This principal is somewhat like Chen’s material, except that he used mechanical units instead. His m-bits are made of silicon and magnetic powder and have a unique shape that allows each individual cell to move between a compressed and decompressed state. These two states act as the programmable binary code, like computer bits.

    2
    Slow-motion captures of programming by switching the equilibrium of the bistable shell. Credit: Tian Chen.

    This essentially means that the material can contain a memory about what it is supposed to be.

    “You can activate and deactivate individual cells by applying a magnetic field. That modifies the internal state of the metamaterial, and consequently its mechanical properties,” says Chen.

    The property that can be altered in this way is the stiffness of the material. When the cells are switched on by the magnetic field, the material is stiff; when they’re switched off, the material is more flexible.

    If that isn’t incredible enough, its possible to program various combinations of the on/off cells to provide a range of flexibility, basically whenever it’s needed.

    This is the first report that shows both programmed memory and physical change imparted by bits in a single material.

    This extraordinary combination of computer science and mechanical engineering strives to find the sweet spot between static material and machine. This unlocks potential materials that might be used in a plethora of useful items, from prosthetics to aeronautics to shock absorption in orthopaedic shoes.

    A few things need to be sorted out before it reaches the usable stage, though.

    “We could design a method for creating 3D structures, since what we’ve done so far is only in 2D,” says Pedro Reis, the leader of Chen’s lab at École Polytechnique Fédérale de Lausanne . “Or we could shrink the scale to make even smaller metamaterials.”

    Regardless, the ability to program the memory of materials so they’ll change properties is a very exciting development indeed.

    See the full article here .

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    EPFL campus

    EPFL (CH) is Europe’s most cosmopolitan technical university. It receives students, professors and staff from over 120 nationalities. With both a Swiss and international calling, it is therefore guided by a constant wish to open up; its missions of teaching, research and partnership impact various circles: universities and engineering schools, developing and emerging countries, secondary schools and gymnasiums, industry and economy, political circles and the general public.

     
  • richardmitnick 9:07 am on January 20, 2021 Permalink | Reply
    Tags: "The humans at the heart of AI", AI and robotics development pull us right into the heart of what it is to be human., , Computer Science, Garmi will learn from and teach the other robots in its network., In its AI research TUM focuses on two fields: embodied AI; the recently founded Munich Data Science Institute (MDSI) has a data- centric perspective., MSRM’s research agenda covers the understanding of humans in order to develop intelligent machines that can in turn help humans., Munich School of Robotics and Machine Intelligence (MSRM) at TUM, , , The robot called Garmi was designed through consultations with elderly people and caregivers to help the elderly to continue living independently., The Technical University of Munich (TUM) is ahead of the game when it comes to AI and robotics., The Technical University of Munich [Technische Universität München] (DE), We are not just doing engineering but we are creating a new discipline.   

    From The Technical University of Munich [Technische Universität München] (DE) via nature research: “The humans at the heart of AI” 

    Techniche Universitat Munchen

    From The Technical University of Munich [Technische Universität München] (DE)

    via

    nature research

    1.19.21

    The Technical University of Munich (TUM) is ahead of the game when it comes to AI and robotics. And that includes the societal side as much as the technological.

    1
    Sami Haddadin runs a ‘robot kindergarten’ where intelligent machines learn from each other.Credit: TUM.

    “AI and robotics development pull us right into the heart of what it is to be human,” says Sami Haddadin, founding director of the Munich School of Robotics and Machine Intelligence (MSRM) at TUM. “We’re not looking to usher in an ‘age of automatons’. Rather, we hope to enable a smooth transition to an age of human- machine interaction.”

    MSRM’s research agenda covers the understanding of humans in order to develop intelligent machines that can, in turn, help humans. Haddadin gives an example: give a young child a key and, within around 20 tries, they can unlock a door. A child’s intuitive ability to manipulate a tool is one aspect, but they also watch and learn from adults. Humans are born with this ability to transfer knowledge, but robots are not. It could take several million trials for a robot to use a key.

    “We don’t have time to wait for a single robot to insert a key into a keyhole, let alone learn how to turn it,” says Haddadin. “But we can connect AI robots so they can share what their algorithms have learned while trying. Basically, we run a robot kindergarten here at TUM.”

    MSRM is one of TUM’s Integrative Research Centers, bringing together researchers from various fields, from computer sciences to natural sciences, from medicine to social sciences. “We are not just doing engineering, but we are creating a new discipline,” says Haddadin. TUM pursues an “embedded ethics approach” integrating ethics throughout the whole technology development process.

    3
    Medical researchers at TUM’s university hospital work closely with AI researchers.Credit: TUM.

    This applies not least to technologies intended for everyday life. The robot called Garmi was designed through consultations with elderly people and caregivers to help the elderly to continue living independently. Garmi can do general tasks, collect medical data, help with rehabilitation exercises, and act as an avatar for communication with doctors and family members. “Garmi will learn from, and teach, the other robots in its network, so each robot can quickly adapt to an individual’s needs,” says Haddadin.

    In its AI research, TUM focuses on two fields. While MSRM concentrates on embodied AI, the recently founded Munich Data Science Institute (MDSI) has a data- centric perspective. On the one hand, it investigates the basic mathematical, informatics and algorithmic questions of data analysis and develops new fundamental theories and methods, especially for machine learning. On the other hand, the MDSI will develop applications in the different research fields of TUM, including quantum technology, climate science, aerospace and genome research.

    Daniel Rückert, professor for artificial intelligence in healthcare and medicine, is one of the MDSI members. His lab is within TUM’s university hospital, allowing his team to collaborate directly with doctors and radiologists. “That was one of the reasons why I returned to Germany after 20 years in the UK,” says Rückert, who until a few months ago worked at Imperial College London.

    4
    Assistant robot GARMI, developed by the Munich School of Robotics and Machine Intelligence, could help elderly people live a self-determined life. Credit: TUM; Astrid Eckert.

    Rückert and his team are working on using AI to generate medical images more efficiently and to facilitate their interpretation. Currently, they are developing a ‘smart’ MRI scanner that can detect whether it has generated enough information to make a comprehensive diagnosis. The technology could also compensate for movement, to improve scanning of active young children, for example, and even foetuses.

    Rückert believes that AI will ultimately make health-care more humane, not less. “By taking on the routine, time- consuming tasks inherent in data acquisition, image reconstruction and analysis, AI will give medical professionals more time to focus on patients.” And because it can leverage the power of big data in its analyses, AI can pick up on rare phenomena that the human eye might miss.

    “TUM is strong in both foundational and applied AI,” says Rückert. Recent research successes highlight the university’s broad range of disciplines. With machine learning methods, a research team has succeeded in making the mass analysis of proteins significantly faster than before and almost error-free. Another team has developed algorithms for autonomous vehicles that prevent accidents by predicting different variants of a traffic situation every millisecond.

    The university, together with other scientific institutions, global companies and start-ups, has emerged as one of the most outstanding research ecosystems worldwide. Munich was recently heralded by the European Commission as the best ICT hub in Europe. TUM, in particular, is driving many innovations. “One of our key strengths is the translation of research into useful technologies via strong partnerships with industry,” says Sami Haddadin.

    Now, with funding from the regional government of Bavaria, TUM is further boosting AI research and will create some 20 professorships in the coming months alone. “We welcome inquisitive, adventurous researchers from diverse disciplines to join us. Look at Leonardo DaVinci, who combined his imaginative, artistic flair with mathematical and scientific concepts to design beautiful machines,” says Haddadin. “This kind of multidisciplinary creativity is at the heart of TUM.”

    See the full article here .

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     Technische Universität München Campus

    The Technical University of Munich [Technische Universität München] (DE) is one of Europe’s top universities. It is committed to excellence in research and teaching, interdisciplinary education and the active promotion of promising young scientists. The university also forges strong links with companies and scientific institutions across the world. TUM was one of the first universities in Germany to be named a University of Excellence. Moreover, TUM regularly ranks among the best European universities in international rankings.

     
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