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  • richardmitnick 1:04 pm on August 14, 2018 Permalink | Reply
    Tags: Accelerator Science, , Brute-force approach to particle hunt, , , , , , ,   

    From Nature: “LHC physicists embrace brute-force approach to particle hunt” 

    Nature Mag
    From Nature

    14 August 2018
    Davide Castelvecchi

    The world’s most powerful particle collider has yet to turn up new physics [since Higgs] — now some physicists are turning to a different strategy.

    1
    The ATLAS detector at the Large Hadron Collider near Geneva, Switzerland.Credit: Stefano Dal Pozzolo/Contrasto /eyevine

    A once-controversial approach to particle physics has entered the mainstream at the Large Hadron Collider (LHC).

    LHC

    CERN map


    CERN LHC Tunnel

    CERN LHC particles

    The LHC’s major ATLAS experiment has officially thrown its weight behind the method — an alternative way to hunt through the reams of data created by the machine — as the collider’s best hope for detecting behaviour that goes beyond the standard model of particle physics. Conventional techniques have so far come up empty-handed.

    So far, almost all studies at the LHC — at CERN, Europe’s particle-physics laboratory near Geneva, Switzerland — have involved ‘targeted searches’ for signatures of favoured theories. The ATLAS collaboration now describes its first all-out ‘general’ search of the detector’s data, in a preprint posted on the arXiv server last month and submitted to European Physics Journal C. Another major LHC experiment, CMS, is working on a similar project.

    “My goal is to try to come up with a really new way to look for new physics” — one driven by the data rather than by theory, says Sascha Caron of Radboud University Nijmegen in the Netherlands, who has led the push for the approach at ATLAS. General searches are to the targeted ones what spell checking an entire text is to searching that text for a particular word. These broad searches could realize their full potential in the near future, when combined with increasingly sophisticated artificial-intelligence (AI) methods.

    LHC researchers hope that the methods will lead them to their next big discovery — something that hasn’t happened since the detection of the Higgs boson in 2012, which put in place the final piece of the standard model. Developed in the 1960s and 1970s, the model describes all known subatomic particles, but physicists suspect that there is more to the story — the theory doesn’t account for dark matter, for instance. But big experiments such as the LHC have yet to find evidence for such behaviour. That means it’s important to try new things, including general searches, says Gian Giudice, who heads CERN’s theory department and is not involved in any of the experiments. “This is the right approach, at this point.”

    Collision course

    The LHC smashes together millions of protons per second at colossal energies to produce a profusion of decay particles, which are recorded by detectors such as ATLAS and CMS. Many different types of particle interaction can produce the same debris. For example, the decay of a Higgs might produce a pair of photons, but so do other, more common, processes. So, to search for the Higgs, physicists first ran simulations to predict how many of those ‘impostor’ pairs to expect. They then counted all photon pairs recorded in the detector and compared them to their simulations. The difference — a slight excess of photon pairs within a narrow range of energies — was evidence that the Higgs existed.

    ATLAS and CMS have run hundreds more of these targeted searches to look for particles that do not appear in the standard model.

    CERN/ATLAS detector


    CERN/CMS Detector

    The Standard Model of elementary particles (more schematic depiction), with the three generations of matter, gauge bosons in the fourth column, and the Higgs boson in the fifth.


    Standard Model of Particle Physics from Symmetry Magazine

    Many searches have looked for various flavours of supersymmetry, a theorized extension of the model that includes hypothesized particles such as the neutralino, a candidate for dark matter. But these searches have come up empty so far.

    Standard model of Supersymmetry DESY

    This leaves open the possibility that there are exotic particles that produce signatures no one has thought of — something that general searches have a better chance of finding. Physicists have yet to look, for example, events that produced three photons instead of two, Caron says. “We have hundreds of people looking at Higgs decay and supersymmetry, but maybe we are missing something nobody thought of,” says Arnd Meyer, a CMS member at Aachen University in Germany.

    Whereas targeted searches typically look at only a handful of the many types of decay product, the latest study looked at more than 700 types at once. The study analysed data collected in 2015, the first year after an LHC upgrade raised the energy of proton collisions in the collider from 8 teraelectronvolts (TeV) to 13 TeV. At CMS, Meyer and a few collaborators have conducted a proof-of-principle study, which hasn’t been published, on a smaller set of data from the 8 TeV run.

    Neither experiment has found significant deviations so far. This was not surprising, the teams say, because the data sets were relatively small. Both ATLAS and CMS are now searching the data collected in 2016 and 2017, a trove tens of times larger.

    Statistical cons

    The approach “has clear advantages, but also clear shortcomings”, says Markus Klute, a physicist at the Massachusetts Institute of Technology in Cambridge. Klute is part of CMS and has worked on general searches in at previous experiments, but he was not directly involved in the more recent studies. One limitation is statistical power. If a targeted search finds a positive result, there are standard procedures for calculating its significance; when casting a wide net, however, some false positives are bound to arise. That was one reason that general searches had not been favoured in the past: many physicists feared that they could lead down too many blind alleys. But the teams say they have put a lot of work into making their methods more solid. “I am excited this came forward,” says Klute.

    Most of the people power and resources at the LHC experiments still go into targeted searches, and that might not change anytime soon. “Some people doubt the usefulness of such general searches, given that we have so many searches that exhaustively cover much of the parameter space,” says Tulika Bose of Boston University in Massachusetts, who helps to coordinate the research programme at CMS.

    Many researchers who work on general searches say that they eventually want to use AI to do away with standard-model simulations altogether. Proponents of this approach hope to use machine learning to find patterns in the data without any theoretical bias. “We want to reverse the strategy — let the data tell us where to look next,” Caron says. Computer scientists are also pushing towards this type of ‘unsupervised’ machine learning — compared with the supervised type, in which the machine ‘learns’ from going through data that have been tagged previously by humans.

    See the full article here .

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    Stem Education Coalition

    Nature is a weekly international journal publishing the finest peer-reviewed research in all fields of science and technology on the basis of its originality, importance, interdisciplinary interest, timeliness, accessibility, elegance and surprising conclusions. Nature also provides rapid, authoritative, insightful and arresting news and interpretation of topical and coming trends affecting science, scientists and the wider public.

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  • richardmitnick 3:34 pm on August 9, 2018 Permalink | Reply
    Tags: Accelerator Science, , , Mini antimatter accelerator could rival the likes of the Large Hadron Collider, , ,   

    From Imperial College London: “Mini antimatter accelerator could rival the likes of the Large Hadron Collider” 

    Imperial College London
    From Imperial College London

    09 August 2018
    Hayley Dunning

    1
    Simulation of groups of positrons being concentrated into a beam and accelerated. No image credit .

    Researchers have found a way to accelerate antimatter in a 1000x smaller space than current accelerators, boosting the science of exotic particles.

    The new method could be used to probe more mysteries of physics, like the properties of the Higgs boson and the nature of dark matter and dark energy, and provide more sensitive testing of aircraft and computer chips.

    The method has been modelled using the properties of existing lasers, with experiments planned soon. If proven, the technology could allow many more labs around the world to conduct antimatter acceleration experiments.

    Particle accelerators in facilities such as the Large Hadron Collider (LHC) in CERN and the Linac Coherent Light Source (LCLS) at Stanford University in the United States, speed up elementary particles like protons and electrons.

    LHC

    CERN map


    CERN LHC Tunnel

    CERN LHC particles

    SLAC/LCLS

    These accelerated particles can be smashed together, as in the LHC, to produce particles that are more elementary, like the Higgs boson, which gives all other particles mass.

    They can also be used to generate x-ray laser light, such as in the LCLS, which is used to image extremely fast and small process, like photosynthesis.

    Shrinking accelerators to fit in a lab

    However, to get to these high speeds, the accelerators need to use equipment that is at least two kilometres long. Previously, researchers at Imperial College London had invented a system that could accelerate electrons using equipment only meters long.

    Now a researcher at Imperial has invented a method of accelerating the antimatter version of electrons – called positrons – in a system that would be just centimetres long.

    The accelerator would require a type of laser system that currently covers around 25 square metres, but that is already present in many physics labs.

    Dr Aakash Sahai, from the Department of Physics at Imperial reported his method today in the Physical Review Journal for Accelerators and Beams. He said: “With this new accelerator method, we could drastically reduce the size and the cost of antimatter acceleration. What is now only possible by using large physics facilities at tens of million-dollar costs could soon be possible in ordinary physics labs.”

    “The technologies used in facilities like the Large Hadron Collider or the Linac Coherent Light Source have not undergone significant advances since their invention in the 1950s [not true, HL-LHC and LCLS II are on the way] . They are expensive to run, and it may be that we will soon have all we can get out of them [not true].

    “A new generation of compact, energetic and cheap accelerators of elusive particles would allow us to probe new physics – and allow many more labs worldwide to join the effort.”

    Creating ‘Higgs factories’ and testing aircraft

    While the method is currently undergoing experimental validation, Dr Sahai is confident it will be possible to produce a working prototype within a couple of years, based on the Department’s previous experience creating electron beams using a similar method.

    The method uses lasers and plasma – a gas of charged particles – to produce, concentrate positrons and accelerate them to create a beam. This centimetre-scale accelerator could use existing lasers to accelerate positron beams with tens of millions of particles to the same energy as reached over two kilometres at the Stanford accelerator.

    Colliding electron and positron beams could have implications in fundamental physics. For example, they could create a higher rate of Higgs bosons than the LHC can, allowing physicists to better study its properties. They could also be used to look for new particles thought to exist in a theory called ‘supersymmetry’, which would fill in some gaps in the Standard Model of particle physics.

    The Standard Model of elementary particles (more schematic depiction), with the three generations of matter, gauge bosons in the fourth column, and the Higgs boson in the fifth.


    Standard Model of Particle Physics from Symmetry Magazine

    3
    No image caption or credit.

    The positron beams would also have practical applications. Currently, when checking for faults and fracture risks in materials such as aircraft bodies, engine blades and computer chips, x-rays or electron beams are used. Positrons interact in a different way with these materials than x-rays and electrons, providing another dimension to the quality control process.

    Dr Sahai added: “It is particularly gratifying to do this work at Imperial, where our lab’s namesake – Professor Patrick Blackett – won a Nobel Prize for his invention of methods to track exotic particles like antimatter. Professor Abdus Salam, another Imperial academic, also won a Nobel Prize for the validation of his theory of weak force made possible only using a pre-LHC positron-electron collider machine at CERN. It’s wonderful to attempt to carry on this legacy.”

    See the full article here .

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    Imperial College London

    Imperial College London is a science-based university with an international reputation for excellence in teaching and research. Consistently rated amongst the world’s best universities, Imperial is committed to developing the next generation of researchers, scientists and academics through collaboration across disciplines. Located in the heart of London, Imperial is a multidisciplinary space for education, research, translation and commercialisation, harnessing science and innovation to tackle global challenges.

     
  • richardmitnick 12:14 pm on August 8, 2018 Permalink | Reply
    Tags: Accelerator Science, , , , New measurement of particle’s lifetime intrigues physicists, , ,   

    From CERN: “New measurement of particle’s lifetime intrigues physicists” 

    Cern New Bloc

    Cern New Particle Event

    CERN New Masthead

    From CERN

    8 Aug 2018
    Ana Lopes

    1
    A proton–proton collision event detected by LHCb earlier this year.

    A new measurement of one of a particle’s properties can sometimes throw up a value that, intriguingly, is very different from previous values. In a paper posted online and submitted to the journal Physical Review Letters, the LHCb collaboration at CERN reports precisely that for the lifetime of the so-called charmed omega. Using data from proton–proton collisions, the LHCb researchers have obtained a value for the particle’s lifetime that is nearly four times larger than previous measurements. New studies are already being planned to unravel this intriguing discrepancy, at LHCb and other experiments.

    The charmed omega belongs to a family of particles known as baryons. These particles, of which protons and neutrons are examples, comprise three smaller particles called quarks. But unlike protons, which contain three light quarks and are stable, the charmed omega contains two relatively light quarks and a heavier charm quark (the third heaviest of the six known types of quark), and eventually decays into other particles. Measurements of the lifetimes of charmed particles, and more generally of particles containing heavy quarks, are important because they test models of quantum chromodynamics – the theory that describes how quarks are stuck together by gluons.

    The lifetime of the charmed omega was measured more than a decade ago by the E687 and FOCUS collaborations at Fermilab in the US and by the WA89 collaboration at CERN. These collaborations measured the lifetime of the charmed omega by examining some dozens of charmed-omega decays in experiments in which a beam of particles strikes the nuclei in a fixed target. The average of the values measured by these experiments, which are all relatively close to one another, is 69 ± 12 femtoseconds (one femtosecond is a millionth of a billionth of a second).

    The new LHCb measurement is based on proton–proton collision data comprising about 1000 charmed-omega decays. The LHCb researchers determined the particle’s lifetime by comparing these decays with those of another particle whose lifetime is known very precisely; a similar approach was recently used by the team to determine the lifetime of a “doubly charmed” particle. The charmed-omega result – a lifetime of 268 ± 26 femtoseconds – is much larger than the average of the older values.

    However, none of these measurements contradicts the theoretical estimates of the charmed omega’s lifetime, which rely on subtle calculations based on quantum chromodynamics and include predictions ranging from 60 to 520 femtoseconds. The jury is therefore out on whether the older values or the new one will stand, but the discrepancy between the values will no doubt prompt researchers to make new measurements and revise the theoretical estimates.

    See the full article here.


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    Meet CERN in a variety of places:

    Quantum Diaries
    QuantumDiaries

    Cern Courier

    THE FOUR MAJOR PROJECT COLLABORATIONS

    ATLAS
    CERN ATLAS New

    ALICE
    CERN ALICE New

    CMS
    CERN CMS New

    LHCb
    CERN LHCb New II

    LHC

    CERN map

    CERN LHC Grand Tunnel

    CERN LHC particles

    OTHER PROJECTS AT CERN

    CERN AEGIS

    CERN ALPHA

    CERN ALPHA

    CERN AMS

    CERN ACACUSA

    CERN ASACUSA

    CERN ATRAP

    CERN ATRAP

    CERN AWAKE

    CERN AWAKE

    CERN CAST

    CERN CAST Axion Solar Telescope

    CERN CLOUD

    CERN CLOUD

    CERN COMPASS

    CERN COMPASS

    CERN DIRAC

    CERN DIRAC

    CERN ISOLDE

    CERN ISOLDE

    CERN LHCf

    CERN LHCf

    CERN NA62

    CERN NA62

    CERN NTOF

    CERN TOTEM

    CERN UA9

     
  • richardmitnick 12:00 pm on August 8, 2018 Permalink | Reply
    Tags: Accelerator Science, , , Could a new type of quark fix the “unnaturalness” of the Standard Model?, , , , , ,   

    From CERN ATLAS: “Could a new type of quark fix the “unnaturalness” of the Standard Model?” 

    CERN ATLAS Higgs Event

    CERN/ATLAS
    From CERN ATLAS

    8th August 2018
    ATLAS Collaboration

    1
    Figure 1: One of the Feynman diagrams for T pair production at the LHC. (Image: ATLAS Collaboration © CERN 2018)

    While the discovery of the Higgs boson at the Large Hadron Collider (LHC) in 2012 confirmed many Standard Model predictions, it has raised as many questions as it has answered. For example, interactions at the quantum level between the Higgs boson and the top quark ought to lead to a huge Higgs boson mass, possibly as large as the Planck mass (>1018 GeV). So why is it only 125 GeV? Is there a mechanism at play to cancel these large quantum corrections caused by the top quark (t)? Finding a way to explain the lightness of the Higgs boson is one of the top (no pun intended) questions in particle physics.

    A wide range of solutions have been proposed and a common feature in many of them is the existence of vector-like quarks – in particular, a vector-like top quark (T). Like other quarks, vector-like quarks would be spin-½ particles that interact via the strong force. While all spin-½ particles have left- and right-handed components, the weak force only interacts with the left-handed components of Standard Model particles. However, vector-like quarks would have “ambidextrous” interactions with the weak force, giving them a bit more leeway in how they decay. While the Standard Model top quark always decays to a bottom quark (b) by emitting a W boson (t→Wb), a vector-like top can decay three different ways: T→Wb, T→Zt or T→Ht (Figure 1).

    2
    Figure 2: Lower limit (scale on right axis) on the mass of a vector-like top as a function of the branching ratio to Wb and Ht (bottom and left axes). (Image: ATLAS Collaboration © CERN 2018)

    The ATLAS collaboration uses a custom-built programme to search for vector-like top pairs in LHC data. It utilizes data from several dedicated analyses, each of them sensitive to various experimental signatures (involving leptons, boosted objects and/or large missing transverse momentum). This allows ATLAS to look for all of possible decays, increasing the chance of discovery.

    ATLAS has now gone one step further by performing a combination of all of the individual searches. While individual analyses are designed to study a particular sets of decays, combined results provide sensitivity to all possible sets of decays. These have allowed ATLAS to search for vector-like tops with masses over 1200 GeV. It appears, however, that vector-like tops are so far nowhere to be found. On the bright side, the combination allows ATLAS to set the most stringent lower limits on the mass of a vector-like top for arbitrary sets of branching ratios to the three decay modes (Figure 2).

    Between these limits on vector-like top quarks and those on other theories that could offer a solution (like supersymmetry), the case for a naturally light Higgs boson is not looking good… but Nature probably still has a few tricks up its sleeve for us to uncover.

    The Standard Model of elementary particles (more schematic depiction), with the three generations of matter, gauge bosons in the fourth column, and the Higgs boson in the fifth.


    Standard Model of Particle Physics from Symmetry Magazine

    See the full article here .


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    Please help promote STEM in your local schools.

    Stem Education Coalition

    CERN map


    CERN LHC Grand Tunnel
    CERN LHC particles
    LHC at CERN


    CERN Courier

    QuantumDiaries


    Quantum Diaries

     
  • richardmitnick 11:47 am on August 2, 2018 Permalink | Reply
    Tags: Accelerator Science, , , ,   

    From Quanta Magazine via Nautilus: “How Artificial Intelligence Can Supercharge the Search for New Particles” 

    Nautilus

    Nautilus

    Quanta Magazine
    From Quanta Magazine

    Jul 25, 2018
    Charlie Wood

    1
    In the hunt for new fundamental particles, physicists have always had to make assumptions about how the particles will behave. New machine learning algorithms don’t.
    Image by ATLAS Experiment © 2018 CERN

    The Large Hadron Collider (LHC) smashes a billion pairs of protons together each second.

    LHC

    CERN map


    CERN LHC Tunnel

    CERN LHC particles

    Occasionally the machine may rattle reality enough to have a few of those collisions generate something that’s never been seen before. But because these events are by their nature a surprise, physicists don’t know exactly what to look for. They worry that in the process of winnowing their data from those billions of collisions to a more manageable number, they may be inadvertently deleting evidence for new physics. “We’re always afraid we’re throwing the baby away with the bathwater,” said Kyle Cranmer, a particle physicist at New York University who works with the ATLAS experiment at CERN.

    CERN ATLAS

    Faced with the challenge of intelligent data reduction, some physicists are trying to use a machine learning technique called a “deep neural network” to dredge the sea of familiar events for new physics phenomena.

    In the prototypical use case, a deep neural network learns to tell cats from dogs by studying a stack of photos labeled “cat” and a stack labeled “dog.” But that approach won’t work when hunting for new particles, since physicists can’t feed the machine pictures of something they’ve never seen. So they turn to “weakly supervised learning,” where machines start with known particles and then look for rare events using less granular information, such as how often they might take place overall.

    In a paper posted on the scientific preprint site arxiv.org in May, three researchers proposed applying a related strategy to extend “bump hunting,” the classic particle-hunting technique that found the Higgs boson. The general idea, according to one of the authors, Ben Nachman, a researcher at the Lawrence Berkeley National Laboratory, is to train the machine to seek out rare variations in a data set.

    Consider, as a toy example in the spirit of cats and dogs, a problem of trying to discover a new species of animal in a data set filled with observations of forests across North America. Assuming that any new animals might tend to cluster in certain geographical areas (a notion that corresponds with a new particle that clusters around a certain mass), the algorithm should be able to pick them out by systematically comparing neighboring regions. If British Columbia happens to contain 113 caribous to Washington state’s 19 (even against a background of millions of squirrels), the program will learn to sort caribous from squirrels, all without ever studying caribous directly. “It’s not magic but it feels like magic,” said Tim Cohen, a theoretical particle physicist at the University of Oregon who also studies weak supervision.

    By contrast, traditional searches in particle physics usually require researchers to make an assumption about what the new phenomena will look like. They create a model of how the new particles will behave—for example, a new particle might tend to decay into particular constellations of known particles. Only after they define what they’re looking for can they engineer a custom search strategy. It’s a task that generally takes a Ph.D. student at least a year, and one that Nachman thinks could be done much faster, and more thoroughly.

    The proposed CWoLa algorithm, which stands for Classification Without Labels, can search existing data for any unknown particle that decays into either two lighter unknown particles of the same type, or two known particles of the same or different type. Using ordinary search methods, it would take the LHC collaborations at least 20 years to scour the possibilities for the latter, and no searches currently exist for the former. Nachman, who works on the ATLAS project, says CWoLa could do them all in one go.

    Other experimental particle physicists agree it could be a worthwhile project. “We’ve looked in a lot of the predictable pockets, so starting to fill in the corners we haven’t looked in is an important direction for us to go in next,” said Kate Pachal, a physicist who searches for new particle bumps with the ATLAS project. She batted around the idea of trying to design flexible software that could deal with a range of particle masses last year with some colleagues, but no one knew enough about machine learning. “Now I think it might be the time to try this,” she said.

    The hope is that neural networks could pick up on subtle correlations in the data that resist current modeling efforts. Other machine learning techniques have successfully boosted the efficiency of certain tasks at the LHC, such as identifying “jets” made by bottom-quark particles. The work has left no doubt that some signals are escaping physicists’ notice. “They’re leaving information on the table, and when you spend $10 billion on a machine, you don’t want to leave information on the table,” said Daniel Whiteson, a particle physicist at the University of California, Irvine.

    Yet machine learning is rife with cautionary tales of programs that confused arms with dumbbells (or worse). At the LHC, some worry that the shortcuts will end up reflecting gremlins in the machine itself, which experimental physicists take great pains to intentionally overlook. “Once you find an anomaly, is it new physics or is it something funny that went on with the detector?” asked Till Eifert, a physicist on ATLAS.

    See the full article here .


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    Please help promote STEM in your local schools.

    Stem Education Coalition

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

     
  • richardmitnick 3:20 pm on August 1, 2018 Permalink | Reply
    Tags: Accelerator Science, , , , , , ,   

    From Symmetry: “Machine learning proliferates in particle physics” 

    Symmetry Mag
    From Symmetry

    08/01/18
    Manuel Gnida

    1

    A new review in Nature chronicles the many ways machine learning is popping up in particle physics research.

    Experiments at the Large Hadron Collider produce about a million gigabytes of data every second.

    LHC

    CERN map


    CERN LHC Tunnel

    CERN LHC particles

    Even after reduction and compression, the data amassed in just one hour at the LHC is similar to the data volume Facebook collects in an entire year.

    Luckily, particle physicists don’t have to deal with all of that data all by themselves. They partner with a form of artificial intelligence that learns how to do complex analyses on its own, called machine learning.

    “Compared to a traditional computer algorithm that we design to do a specific analysis, we design a machine learning algorithm to figure out for itself how to do various analyses, potentially saving us countless man-hours of design and analysis work,” says College of William & Mary physicist Alexander Radovic, who works on the NOvA neutrino experiment.

    FNAL NOvA detector in northern Minnesota


    FNAL/NOvA experiment map

    Radovic and a group of researchers summarize current applications and future prospects of machine learning in particle physics in a paper published today in Nature.

    Sifting through big data

    To handle the gigantic data volumes produced in modern experiments like the ones at the LHC, researchers apply what they call “triggers”—dedicated hardware and software that decide in real time which data to keep for analysis and which data to toss out.

    In LHCb, an experiment that could shed light on why there is so much more matter than antimatter in the universe, machine learning algorithms make at least 70 percent of these decisions, says LHCb scientist Mike Williams from the Massachusetts Institute of Technology, one of the authors of the Nature summary.

    CERN LHCb chamber, LHC


    CERN/LHCb detector

    “Machine learning plays a role in almost all data aspects of the experiment, from triggers to the analysis of the remaining data,” he says.

    Machine learning has proven extremely successful in the area of analysis. The gigantic ATLAS and CMS detectors at the LHC, which enabled the discovery of the Higgs boson, each have millions of sensing elements whose signals need to be put together to obtain meaningful results.

    CERN ATLAS

    CERN/CMS Detector

    “These signals make up a complex data space,” says Michael Kagan of the US Department of Energy’s SLAC National Accelerator Laboratory, who works on ATLAS and was also an author on the Nature review. “We need to understand the relationship between them to come up with conclusions—for example, that a certain particle track in the detector was produced by an electron, a photon or something else.”

    Neutrino experiments also benefit from machine learning. NOvA [above], which is managed by Fermi National Accelerator Laboratory, studies how neutrinos change from one type to another as they travel through the Earth. These neutrino oscillations could potentially reveal the existence of a new neutrino type that some theories predict to be a particle of dark matter. NOvA’s detectors are watching out for charged particles produced when neutrinos hit the detector material, and machine learning algorithms identify them.

    From machine learning to deep learning

    Recent developments in machine learning often called “deep learning” promise to take applications in particle physics even further. Deep learning typically refers to the use of neural networks: computer algorithms with an architecture inspired by the dense network of neurons in the human brain.

    These neural nets learn on their own how to perform certain analysis tasks during a training period in which they are shown sample data, such as simulations, and are told how well they performed.

    Until recently, the success of neural nets was limited because training them used to be very hard, says co-author Kazuhiro Terao, a SLAC researcher working on the MicroBooNE neutrino experiment, which studies neutrino oscillations as part of Fermilab’s short-baseline neutrino program and will become a component of the future Deep Underground Neutrino Experiment at the Long-Baseline Neutrino Facility.

    FNAL/MicroBooNE

    FNAL LBNF/DUNE from FNAL to SURF, Lead, South Dakota, USA

    “These difficulties limited us to neural networks that were only a couple of layers deep,” he says. “Thanks to advances in algorithms and computing hardware, we now know much better how to build and train more capable networks hundreds or thousands of layers deep.”

    Many of the advances in deep learning are driven by tech giants’ commercial applications and the data explosion they have generated over the past two decades. “NOvA, for example, uses a neural network inspired by the architecture of the GoogleNet,” Radovic says. “It improved the experiment in ways that otherwise could have only been achieved by collecting 30 percent more data.”

    A fertile ground for innovation

    Machine learning algorithms become more sophisticated and fine-tuned day by day, opening up unprecedented opportunities to solve particle physics problems.

    Many of the new tasks they could be used for are related to computer vision, Kagan says. “It’s similar to facial recognition, except that in particle physics, image features are more abstract and complex than ears and noses.”

    Some experiments like NOvA and MicroBooNE produce data that can easily be translated into actual images, and AI can be readily used to identify features in them. In LHC experiments, on the other hand, images first need to be reconstructed from a murky pool of data generated by millions of sensor elements.

    “But even if the data don’t look like images, we can still use computer vision methods if we’re able to process the data in the right way,” Radovic says.

    One area where this approach could be very useful is the analysis of particle jets produced in large numbers at the LHC. Jets are narrow sprays of particles whose individual tracks are extremely challenging to separate. Computer vision technology could help identify features in jets.

    Another emerging application of deep learning is the simulation of particle physics data that predict, for example, what happens in particle collisions at the LHC and can be compared to the actual data. Simulations like these are typically slow and require immense computing power. AI, on the other hand, could do simulations much faster, potentially complementing the traditional approach.

    “Just a few years ago, nobody would have thought that deep neural networks can be trained to ‘hallucinate’ data from random noise,” Kagan says. “Although this is very early work, it shows a lot of promise and may help with the data challenges of the future.”

    Benefiting from healthy skepticism

    Despite all obvious advances, machine learning enthusiasts frequently face skepticism from their collaboration partners, in part because machine learning algorithms mostly work like “black boxes” that provide very little information about how they reached a certain conclusion.

    “Skepticism is very healthy,” Williams says. “If you use machine learning for triggers that discard data, like we do in LHCb, then you want to be extremely cautious and set the bar very high.”

    Therefore, establishing machine learning in particle physics requires constant efforts to better understand the inner workings of the algorithms and to do cross-checks with real data whenever possible.

    “We should always try to understand what a computer algorithm does and always evaluate its outcome,” Terao says. “This is true for every algorithm, not only machine learning. So, being skeptical shouldn’t stop progress.”

    Rapid progress has some researchers dreaming of what could become possible in the near future. “Today we’re using machine learning mostly to find features in our data that can help us answer some of our questions,” Terao says. “Ten years from now, machine learning algorithms may be able to ask their own questions independently and recognize when they find new physics.”

    See the full article here .


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    Symmetry is a joint Fermilab/SLAC publication.


     
  • richardmitnick 11:54 am on July 30, 2018 Permalink | Reply
    Tags: Accelerator Science, , , , LHC accelerates its first 'atoms', , ,   

    From CERN: “LHC accelerates its first ‘atoms'” 

    Cern New Bloc

    Cern New Particle Event

    CERN New Masthead

    From CERN

    27 July 2018
    Sarah Charley
    Posted by Kate Kahle

    1
    During a special one-day run, LHC operators injected lead “atoms” containing a single electron into the machine (Image: Maximilien Brice/Julien Ordan/CERN)

    Protons might be the Large Hadron Collider’s bread and butter, but that doesn’t mean it can’t crave more exotic tastes from time to time.

    LHC

    CERN map


    CERN LHC Tunnel

    CERN LHC particles

    On Wednesday, 25 July, for the very first time, operators injected not just atomic nuclei but lead “atoms” containing a single electron into the LHC. This was one of the first proof-of-principle tests for a new idea called the Gamma Factory, part of CERN’s Physics Beyond Colliders project.

    “We’re investigating new ideas of how we could broaden the present CERN research programme and infrastructure,” says Michaela Schaumann, an LHC Engineer in Charge. “Finding out what’s possible is the first step.”

    During normal operation, the LHC produces a steady stream of proton–proton collisions, then smashes together atomic nuclei for about four weeks just before the annual winter shutdown. But for a handful of days a year, accelerator physicists get to try something completely new during periods of machine development. Previously, they accelerated xenon nuclei in the LHC and tested other kinds of partially stripped lead ions in the SPS accelerator.

    “This special LHC run was really the last step in a series of tests,” says physicist Witold Krasny, who is coordinating a study group of about 50 scientists to develop new ways to produce high-energy gamma rays.

    Accelerating lead nuclei with one remaining electron can be challenging because of how delicate these atoms are. “It’s really easy to accidentally strip off the electron,” explains Schaumann. “When that happens, the nucleus crashes into the wall of the beam pipe because its charge is no longer synchronised with the LHC’s magnetic field.”

    During the first run, operators injected 24 bunches of “atoms” and achieved a low-energy stable beam inside the LHC for about an hour. They then ramped the LHC up to its full power and maintained the beam for about two minutes before it was ejected into the beam dump. “If too many particles go off course, the LHC automatically dumps the beam,” states Schaumann. “Our main priority is to protect the LHC and its magnets.”

    After running the magnets through the restart cycle, Schaumann and her colleagues tried again, this time with only six bunches. They kept the beam circulating for two hours before intentionally dumping it.

    “We predicted that the lifetime of this special kind of beam inside the LHC would be at least 15 hours,” says Krasny. “We were surprised to learn the lifetime could be as much as about 40 hours. Now the question is whether we can preserve the same beam lifetime at a higher intensity by optimising the collimator settings, which were still set-up for protons during this special run.”

    Physicists are doing these tests to see if the LHC could one day operate as a gamma-ray factory. In this scenario, scientists would shoot the circulating “atoms” with a laser, causing the electron to jump into a higher energy level. As the electron falls back down, it spits out a particle of light. In normal circumstances, this particle of light would not be very energetic, but because the “atom” is already moving at close to the speed of light, the energy of the emitted photon is boosted and its wavelength is squeezed (due to the Doppler effect).

    These gamma rays would have sufficient energy to produce normal “matter” particles, such as quarks, electrons and even muons. Because matter and energy are two sides of the same coin, these high-energy gamma rays would transform into massive particles and could even morph into new kinds of matter, such as dark matter. They could also be the source for new types of particle beams, such as a muon beam.

    Even though this is still a long way off, the tests this week were an important first step in seeing what is possible.

    See the full article here.


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    Meet CERN in a variety of places:

    Quantum Diaries
    QuantumDiaries

    Cern Courier

    THE FOUR MAJOR PROJECT COLLABORATIONS

    ATLAS
    CERN ATLAS New

    ALICE
    CERN ALICE New

    CMS
    CERN CMS New

    LHCb
    CERN LHCb New II

    LHC

    CERN map

    CERN LHC Grand Tunnel

    CERN LHC particles

    OTHER PROJECTS AT CERN

    CERN AEGIS

    CERN ALPHA

    CERN ALPHA

    CERN AMS

    CERN ACACUSA

    CERN ASACUSA

    CERN ATRAP

    CERN ATRAP

    CERN AWAKE

    CERN AWAKE

    CERN CAST

    CERN CAST Axion Solar Telescope

    CERN CLOUD

    CERN CLOUD

    CERN COMPASS

    CERN COMPASS

    CERN DIRAC

    CERN DIRAC

    CERN ISOLDE

    CERN ISOLDE

    CERN LHCf

    CERN LHCf

    CERN NA62

    CERN NA62

    CERN NTOF

    CERN TOTEM

    CERN UA9

     
  • richardmitnick 5:34 pm on July 25, 2018 Permalink | Reply
    Tags: Accelerator Science, , , EIC-Electron-Ion Collider in development, , , , ,   

    From MIT News- “3Q: Richard Milner on a new U.S. particle accelerator” 

    MIT News
    MIT Widget

    From MIT News

    July 24, 2018
    Jennifer Chu

    1
    In an Electron-Ion Collider, a beam of electrons (e-) would scatter off a beam of protons or atomic nuclei, generating virtual photons (λ) — particles of light that penetrate the proton or nucleus to tease out the structure of the quarks and gluons within. Image: Brookhaven National Laboratory

    Proposal for powerful particle collider gets National Academies’ go-ahead.

    The case for an ambitious new particle accelerator to be built in the United States has just gotten a major boost.

    Today, the National Academies of Sciences, Engineering, and Medicine have endorsed the development of the Electron Ion Collider, or EIC. The proposed facility, consisting of two intersecting accelerators, would smash together beams of protons and electrons traveling at nearly the speed of light. In the aftermath of each collision, scientists should see “snapshots” of the particles’ inner structures, much like a CT scan for atoms. From these images, scientists hope to piece together a multidimensional picture, with unprecedented depth and clarity, of the quarks and gluons that bind together protons and all the visible matter in the universe.

    The EIC, if built, would significantly advance the field of quantum chromodynamics, which seeks to answer fundamental questions in physics, such as how quarks and gluons produce the strong force — the “glue” that holds all matter together. If constructed, the EIC would be the largest accelerator facility in the U.S. and, worldwide, second only to the Large Hadron Collider at CERN. MIT physicists, including Richard Milner, professor of physics at MIT, have been involved from the beginning in making the case for the EIC.

    MIT News checked in with Milner, a member of the Laboratory for Nuclear Science, about the need for a new particle collider and its prospects going forward.

    Q: Tell us a bit about the history of this design. What has it taken to make the case for this new particle accelerator?

    A: The development of both the scientific and technical case for the EIC has been in progress for about two decades. With the development of quantum chromodynamics (QCD) in the 1970s by MIT physics Professor Frank Wilczek and others, nuclear physicists have long sought to bridge the gap between QCD and the successful theory of nuclei based on experimentally observable particles, where the fundamental constituents are the undetectable quarks and gluons.

    A high-energy collider with the ability to collide electrons with the full range of nuclei at high rates and to have the electrons and nucleons polarized was identified as the essential tool to construct this bridge. High-energy electron scattering from the proton was how quarks were experimentally discovered at SLAC in the late 1960s (by MIT physics faculty Henry Kendall and Jerome Friedman and colleagues), and it is the accepted technique to directly probe the fundamental quark and gluon structure of matter.

    Significant initial impetus for the EIC came from nuclear physicists at the university user-facilities at the University of Indiana and MIT as well as from physicists seeking to understand the origin of the proton’s spin, at laboratories and universities in the U.S. and Europe. Over the last three long-range planning exercises by U.S. nuclear physicists in 2002, 2007, and 2015, the case for the EIC has matured and strengthened. After the 2007 exercise, the two U.S. flagship nuclear facilities, namely the Relativistic Heavy Ion Collider at Brookhaven National Laboratory and the Continuous Electron Beam Accelerator Facility at Jefferson Laboratory, took a leadership role in coordinating EIC activities across the broad U.S. QCD community.

    BNL RHIC Campus


    BNL/RHIC

    Jlab CEBAF


    JLab campus

    This led to the production in 2012 of a succinct summary of the science case, “Electron-Ion Collider: The Next QCD Frontier (Understanding the glue that binds us all).”

    The 2015 planning exercise established the EIC as the highest priority for new facility construction in U.S. nuclear physics after present commitments are fulfilled. This led to the formation of a committee by the U.S. National Academy of Sciences (NAS) to assess the EIC science case. The NAS committee deliberated for about a year and the report has been publicly released this month.

    Q: Give us an idea of how powerful this new collider will be and what kind of new interactions it will produce. What kinds of phenomena will it help to explain?

    A: The EIC will be a powerful and unique new accelerator that will offer an unprecedented window into the fundamental structure of matter. The electron-ion collision rate at the EIC will be high, more than two orders of magnitude greater than was possible at the only previous electron-proton collider, namely HERA, which operated at the DESY laboratory in Hamburg, Germany, from 1992 to 2007.

    DESY HERA , 1992 to 2007

    With the EIC, physicists will be able to image the virtual quarks and gluons that make up protons, neutrons, and nuclei, with unprecedented spatial resolution and shutter speed. A goal is to provide images of the fundamental structure of the microcosm that can be appreciated broadly by humanity: to answer questions such as, what does a proton look like? And what does a nucleus look like?

    There are three central scientific issues that can be addressed by an electron-ion collider. The first goal is to understand in detail the mechanisms within QCD by which the mass of protons and neutrons, and thus the mass of all the visible matter in the universe, is generated. The problem is that while gluons have no mass, and quarks are nearly massless, the protons and neutrons that contain them are heavy, making up most of the visible mass of the universe. The total mass of a nucleon is some 100 times greater than the mass of the various quarks it contains.

    The second issue is to understand the origin of the intrinsic angular momentum, or spin, of nucleons, a fundamental property that underlies many practical applications, including magnetic resonance imaging (MRI). How the angular momentum, both intrinsic as well as orbital, of the internal quarks and gluons gives rise to the known nucleon spin is not understood. And thirdly, the nature of gluons in matter — that is, their arrangements or states — and the details of how they hold matter together, is not well-known. Gluons in matter are a little like dark matter in the universe: unseen but playing a crucial role. An electron-ion collider would potentially reveal new states resulting from the close packing of many gluons within nucleons and nuclei. These issues are fundamental to our understanding of the matter in the universe.

    Q: What role will MIT have in this project going forward?

    A: At present, more than a dozen MIT physics department faculty lead research groups in the Laboratory for Nuclear Science that work directly on understanding the fundamental structure of matter as described by QCD. It is the largest university-based group in the U.S. working on QCD. Theoretical research is focused at the Center for Theoretical Physics, and experimentalists rely heavily on the Bates Research and Engineering Center for technical support.

    MIT theorists are carrying out important calculations using the world’s most powerful computers to understand fundamental aspects of QCD. MIT experimental physicists are conducting experiments at existing facilities, such as BNL, CERN, and Jefferson Laboratory, to reach new insight and to develop new techniques that will be used at the EIC. Further, R&D into new polarized sources, detectors, and innovative data-acquisition schemes by MIT scientists and engineers is in progress. It is anticipated that these efforts will ramp up as the realization of the EIC approaches.

    It is anticipated that the U.S. Department of Energy Office of Science will initiate in the near future the official process for EIC by which the U.S. government approves, funds, and constructs new, large scientific facilities. Critical issues are the selection of the site for EIC and the participation of international users. An EIC user group has formed with the participation of more than 700 PhD scientists from over 160 laboratories and universities around the world. If the realization of EIC follows a schedule comparable to that of past large facilities, it should be doing science by about 2030. MIT has a long history of providing leadership in U.S. nuclear physics and will continue to play a significant role as we proceed along the path to EIC.

    See the full article here .


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    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.

    MIT Campus

     
  • richardmitnick 10:27 am on July 24, 2018 Permalink | Reply
    Tags: Accelerator Science, , FNAL INTENSE exchange program, , , , RISE-The Marie Sklodowska-Curie Actions under Research and Innovation Staff Exchange program   

    From Fermilab: “INTENSE exchange program draws international group of scientists to Fermilab” 

    FNAL II photo

    FNAL Art Image
    FNAL Art Image by Angela Gonzales

    From Fermilab , an enduring source of strength for the US contribution to scientific research world wide.

    July 23, 2018
    No writer credit

    Rare-physics experiments at Fermilab recently received an international boost.

    In June, the INTENSE research-exchange program started up at the Department of Energy’s Fermi National Accelerator Laboratory. It is the third program to be implemented at Fermilab through the Marie Sklodowska-Curie Actions under Research and Innovation Staff Exchange, or RISE program. INTENSE researchers’ contributions will total 400 months of work over four years. The full contributed research time is an equivalent of about $10 million in salaried work.

    The University of Pisa in Italy is leading the effort. Those participating in INTENSE include institutions in Belgium, France, Israel, Italy, Switzerland and the UK.

    The RISE program, funded through the European Commission H2020 program, aims to promote international collaboration through the exchange of scientific research and personnel. (The European Commission is the executive body of the European Union.) European researchers get to travel to host institutions outside Europe to conduct research there, and the host institutions in return receive personnel to advance their experiments. The resulting growth and strengthening of scientific networks are global benefits.

    Through INTENSE, European scientists will visit Fermilab to work on experiments at the so-called intensity frontier — experiments looking for hypothesized, rare occurrences in the subatomic realm. Such particle-accelerator-based experiments require intense particle beams, hence, “the intensity frontier” of particle physics.

    Having the additional personnel work on Fermilab experiments is a clear benefit for the lab. INTENSE researchers — who will come to Fermilab to help develop particle detectors for the Mu2e experiment, currently under construction, and the Short-Baseline Neutrino Program, which comprises three experiments: the Short-Baseline Neutrino Detector and ICARUS (both under construction) and MicroBooNE, which began taking data in 2015.

    FNAL Mu2e solenoid


    FNAL Mu2e facility

    FNAL Short baseline neutrino detector

    FNAL/ICARUS

    FNAL/MicroBooNE

    3
    MicroBooNE is one of three experiments that are part of the Fermilab Short-Baseline Neutrino program, in which INTENSE researchers participate. Pictured here is the interior of the MicroBooNE detector. Photo: Reidar Hahn

    The Short-Baseline Neutrino Program is looking for a phenomenon — the existence of a sterile neutrino — that has been hinted at by at least one other neutrino experiment. Scientists know of three types of neutrino. A fourth, sterile neutrino would suggest a complexity behind this subtle particle not previously understood.

    Mu2e is looking for a theorized but never observed transformation of a particle called a muon directly into its more familiar, lightweight cousin, the electron. The common decay mode of a muon is into an electron plus two neutrinos. The direct transformation would have the muon changing into an electron without the two neutrinos. Catching this transformation in the act could help scientists better understand the laws that govern elementary particles.

    As they help develop the Mu2e detector, INTENSE collaborators will also research ways to use muon beams for fields outside particle physics, specifically geophysics and archaeology. These muographical studies, as they’re called, use muons in cosmic rays to image geological and geographical sites such as volcanoes, glaciers and archaeological digs.

    4
    Cryogenic tests for Fermilab’s Mu2e experiment will take place here. Mu2e is one of the experiments that will benefit from INTENSE researchers. Photo: Reidar Hahn

    “We can all appreciate the breadth of this program,” said Fermilab scientist Emanuela Barzi, Fermilab’s coordinator for hosting researchers who receive INTENSE funding. “We all benefit. As a partner, Fermilab benefits from our global friends’ cooperation as well as the tighter scientific network that results from this exchange.”

    The INTENSE grant comes with an outreach component. Scientists in the INTENSE program may, for example, participate in the Italian Summer School at Fermilab, during which students from European universities come to Fermilab to work on Mu2e and the Short-Baseline Neutrino Program.

    “The grant elevates all the ways we do science — basic research, physics applications, outreach,” said University of Pisa scientist Simone Donati, INTENSE coordinator. “Having a small slice of the global particle physics community at Fermilab reminds us of the meaning of collaboration.”

    In addition to the INTENSE program, the H2020 Marie Sklodowska-Curie Research and Innovation Staff Exchange support two other activities: MUSE and NEWS. Learn more.

    See the full article here .


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    FNAL Icon

    Fermi National Accelerator Laboratory (Fermilab), located just outside Batavia, Illinois, near Chicago, is a US Department of Energy national laboratory specializing in high-energy particle physics. Fermilab is America’s premier laboratory for particle physics and accelerator research, funded by the U.S. Department of Energy. Thousands of scientists from universities and laboratories around the world
    collaborate at Fermilab on experiments at the frontiers of discovery.


    FNAL/MINERvA

    FNAL DAMIC

    FNAL Muon g-2 studio

    FNAL Short-Baseline Near Detector under construction

    FNAL Mu2e solenoid

    Dark Energy Camera [DECam], built at FNAL

    FNAL DUNE Argon tank at SURF

    FNAL/MicrobooNE

    FNAL Don Lincoln

    FNAL/MINOS

    FNAL Cryomodule Testing Facility

    FNAL Minos Far Detector

    FNAL LBNF/DUNE from FNAL to SURF, Lead, South Dakota, USA

    FNAL/NOvA experiment map

    FNAL NOvA Near Detector

    FNAL ICARUS

    FNAL Holometer

     
  • richardmitnick 10:02 am on July 24, 2018 Permalink | Reply
    Tags: Accelerating superconducting technology, Accelerator Science, , , , , ,   

    From Fermilab: “Fermilab gets ready to upgrade accelerator complex for more powerful particle beams” 

    FNAL II photo

    FNAL Art Image
    FNAL Art Image by Angela Gonzales

    From Fermilab , an enduring source of strength for the US contribution to scientific research world wide.

    More powerful particle beams

    July 24, 2018
    Andre Salles,
    Fermilab Office of Communication
    asalles@fnal.gov
    630-840-6733

    Fermilab’s accelerator complex has achieved a major milestone: The U.S. Department of Energy formally approved Fermi National Accelerator Laboratory to proceed with its design of PIP-II, an accelerator upgrade project that will provide increased beam power to generate an unprecedented stream of neutrinos — subatomic particles that could unlock our understanding of the universe — and enable a broad program of physics research for many years to come.

    The PIP-II (Proton Improvement Plan II) accelerator upgrades are integral to the Fermilab-hosted Deep Underground Neutrino Experiment (DUNE), which is the largest international science experiment ever to be conducted on U.S. soil.

    FNAL LBNF/DUNE from FNAL to SURF, Lead, South Dakota, USA


    FNAL DUNE Argon tank at SURF


    Surf-Dune/LBNF Caverns at Sanford



    SURF building in Lead SD USA

    DUNE requires enormous quantities of neutrinos to study the mysterious particle in exquisite detail and, with the latest approval for PIP-II, Fermilab is positioned to be the world leader in accelerator-based neutrino research. The Long-Baseline Neutrino Facility (LBNF), which will also support DUNE, had its groundbreaking ceremony in July 2017.

    The opportunity to contribute to PIP-II has drawn scientists and engineers from around the world to Fermilab: PIP-II is the first accelerator project on U.S. soil that will have significant contributions from international partners. Fermilab’s PIP-II partnerships include institutions in India, Italy, France and the UK, as well as the United States.

    PIP-II capitalizes on recent particle accelerator advances developed at Fermilab and other institutions that will allow its accelerators to generate particle beams at higher powers than previously available. The high-power particle beams will in turn create intense neutrino beams, providing scientists with an abundance of these subtle particles.

    “PIP-II’s high-power accelerators and its national and multinational partnerships reinforce Fermilab’s position as the accelerator-based neutrino physics capital of the world,” said DOE Undersecretary for Science Paul Dabbar. “LBNF/DUNE, the Fermilab-based megascience experiment for neutrino research, has already attracted more than 1,000 collaborators from 32 countries. With the accelerator side of the experiment ramping up in the form of PIP-II, not only does Fermilab attract collaborators worldwide to do neutrino science, but U.S. particle physics also gets a powerful boost.”

    The Department of Energy’s Argonne and Lawrence Berkeley national laboratories are also major PIP-II participants.

    1
    This architectural rendering shows the buildings that will house the new PIP-II accelerators. Architectural rendering: Gensler. Image: Diana Brandonisio

    A major milestone

    The DOE milestone is formally called Critical Decision 1 approval, or CD-1. In granting CD-1, DOE approves Fermilab’s approach and cost range. The milestone marks the completion of the project definition phase and the conceptual design. The next step is to move the project toward establishing a performance baseline.

    “We think of PIP-II as the heart of Fermilab: a platform that provides multiple capabilities and enables broad scientific programs, including the most powerful accelerator-based neutrino source in the world,” said Fermilab PIP-II Project Director Lia Merminga. “With the go-ahead to refine our blueprint, we can focus designing the PIP-II accelerator complex to be as powerful and flexible as it can possibly be.”

    PIP-II’s powerful neutrino stream

    Neutrinos are ubiquitous yet fleeting particles, the most difficult to capture of all of the members of the subatomic particle family. Scientists capture them by sending neutrino beams generated from particle accelerators to large, stories-high detectors. The greater the number of neutrinos sent to the detectors, the greater the chances the detectors will catch them, and the more opportunity there is to study these subatomic escape artists.

    That’s where PIP-II comes in.

    Fermilab’s upgraded PIP-II accelerator complex will generate proton beams of significantly greater power than is currently available. The increase in beam power translates into more neutrinos that can be sent to the lab’s various neutrino experiments. The result will be the world’s most intense high-energy neutrino beam.

    The goal of PIP-II is to produce a proton beam of more than 1 megawatt, about 60 percent higher than the existing accelerator complex supplies. Eventually, enabled by PIP-II, Fermilab could upgrade the accelerator to double that power to more than 2 megawatts.

    “At that power, we can just flood the detectors with neutrinos,” said DUNE co-spokesperson and University of Chicago physicist Ed Blucher. “That’s what so exciting. Every neutrino that stops in our detectors adds a bit of information to our picture of the universe. And the more neutrinos that stop, the closer we get to filling in the picture.”

    The largest and most ambitious of these detectors are those in DUNE, which is scheduled to start up in the mid-2020s. DUNE will use two detectors separated by a distance of 800 miles (1,300 kilometers) — one at Fermilab and a second, much larger detector situated one mile underground in South Dakota at the Sanford Underground Research Facility. Prototypes of those technologically advanced neutrino detectors are now under construction at the European particle physics laboratory CERN, which is a major partner in LBNF/DUNE, and are expected to take data later this year.

    Fermilab’s accelerators, enhanced according to the PIP-II plan, will send a beam of neutrinos to the DUNE detector at Fermilab. The beam will continue its path straight through Earth’s crust to the detector in South Dakota. Scientists will study the data gathered by both detectors, comparing them to get a better handle on how neutrino properties change over the long distance.

    The detector located in South Dakota, known as the DUNE far detector, is enormous. It will stand four stories high and occupy an area equivalent to a soccer field. With its supporting platform LBNF, DUNE is designed to handle a neutrino deluge.

    And, with the cooperation of international partners, PIP-II is designed to deliver it.

    2
    The PIP-II project will supply powerful neutrino beams for the LBNF/DUNE experiment. Image: Diana Brandonisio

    Partners in PIP-II

    The development of a major particle accelerator with international participation represents a new paradigm in U.S. accelerator projects: PIP-II is the first U.S.-based accelerator project with multinational partners. Currently these include laboratories in India (BARC, IUAC, RRCAT, VECC) and institutions funded in Italy by the National Institute for Nuclear Physics (INFN), France (CEA and IN2P3), and in the UK by the Science and Technology Facilities Council (STFC).

    In an agreement with India, four Indian Department of Atomic Energy institutions are authorized to contribute equipment, with details to be formalized in advance of the start of construction.

    “The international scientific community brings world-leading expertise and capabilities to the project. Their engagement and shared sense of ownership in the project’s success are among the most compelling strengths of PIP-II,” Merminga said.

    PIP-II partners contribute accelerator components, pursuing their development jointly with Fermilab through regular exchanges of scientists and engineers. The collaboration is mutually beneficial. For some international partners, this collaboration presents an opportunity for development of their own facilities and infrastructure as well as local accelerator industry.

    3
    Fermilab is currently developing the front end of the PIP-II linear accelerator for tests of the relevant technology. Photo: Reidar Hahn

    Accelerating superconducting technology

    The centerpiece of the PIP-II project is the construction of a new superconducting radio-frequency (SRF) linear accelerator, which will become the initial stage of the upgraded Fermilab accelerator chain. It will replace the current Fermilab Linac.

    4
    This is a view of the high energy end of the linac

    5
    This is an aerial view showing the smaller machines in the Fermilab accelerator complex.There is a good view of the Pre-accelerator (Cockroft-Walton), the Linac, the Booster ring, and the Antiproton source (Accumulator and Debuncher).Courtesy Fermilab Visual media services.

    6
    This is a schematic of FNAL accelerator complex; the arrows give a sense of how the beams (proton or anti proton) move from one machine to the next. Courtesy Fermilab Visual media services
    (“Linac” is a common abbreviation for “linear accelerator,” in which the particle beam proceeds along a straight path.) The plan is to install the SRF linac under 25 feet of dirt in the infield of the now decommissioned Tevatron ring.

    FNAL/Tevatron map

    The new SRF linac will provide a big boost to its particle beam from the get-go, doubling the beam energy of its predecessor from 400 million to 800 million electronvolts. That boost will enable the Fermilab accelerator complex to achieve megawatt-scale beam power.

    Superconducting materials carry zero electrical resistance, so current sails through them effortlessly. By taking advantage of superconducting components, accelerators minimize the amount of power they draw from the power grid, channeling more of it to the beam. Beams thus achieve higher energies at less cost than in normal-conducting accelerators, such as Fermilab’s current Linac.

    In the linac, superconducting components called accelerating cavities will impart energy to the particle beam. The cavities, which look like strands of jumbo, silver pearls, are made of niobium and will be lined up end to end. The particle beam will accelerate down the axis of one cavity after another, picking up energy as it goes.

    “Fermilab is one of the pioneers in superconducting accelerator technology,” Merminga said. “Many of the advances developed here are going into the PIP-II SRF linac.”

    The linac cavities will be encased in 25 cryomodules, which house cryogenics to keep the cavities cold (to maintain superconductivity).

    Many current and future particle accelerators are based on superconducting technology, and the advances that help scientists study neutrinos have multiplying effects outside fundamental science. Researchers are developing superconducting accelerators for medicine, environmental cleanup, quantum computing, industry and national security.

    The beam scheme

    In PIP-II, a beam of protons will be injected into the linac. Over the course of its 176 meters — six-and-a-half Olympic-size pool lengths — the beam will accelerate to an energy of 800 million electronvolts. Once it passes through the superconducting linac, it will enter the rest of Fermilab’s current accelerator chain — a further three accelerators — which will also undergo significant upgrades over the next few years to handle the higher-energy beam from the new linac. By the time the beam exits the final accelerator, it will have an energy of up to 120 billion electronvolts and more than 1 megawatt of power.

    After the proton beam exits the chain, it will strike a segmented cylinder of carbon. The beam-carbon collision will create a shower of other particles, which will be routed to various Fermilab experiments. Some of these post-collision particles will become — will “decay into,” in physics lingo — neutrinos, which will by this point already be on the path toward their detectors.

    PIP-II’s initial proton beam — which scientists will be able to distribute between LBNF/DUNE and other experiments — can be delivered in pulses or as a continuous proton stream.

    The front-end components for PIP-II — those upstream from the superconducting linac — are already developed and undergoing testing.

    “We are very happy to have been able to design PIP-II to meet the requirements of the neutrino program while providing flexibility for future development of the Fermilab experimental program in any number of directions,” said Fermilab’s Steve Holmes, former PIP-II project director.

    Fermilab expects to complete the project by the mid-2020s, in time for the startup of LBNF/DUNE.

    “Many people worked tirelessly to design the best machine for the science we want to do,” Merminga said. “The recognition of their excellent work through CD-1 approval is encouraging for us. We look forward to building this forefront accelerator.”

    Department of Energy funding for the project is provided through DOE’s Office of Science.

    See the full article here .


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

    Please help promote STEM in your local schools.

    Stem Education Coalition

    FNAL Icon

    Fermi National Accelerator Laboratory (Fermilab), located just outside Batavia, Illinois, near Chicago, is a US Department of Energy national laboratory specializing in high-energy particle physics. Fermilab is America’s premier laboratory for particle physics and accelerator research, funded by the U.S. Department of Energy. Thousands of scientists from universities and laboratories around the world
    collaborate at Fermilab on experiments at the frontiers of discovery.


    FNAL/MINERvA

    FNAL DAMIC

    FNAL Muon g-2 studio

    FNAL Short-Baseline Near Detector under construction

    FNAL Mu2e solenoid

    Dark Energy Camera [DECam], built at FNAL

    FNAL DUNE Argon tank at SURF

    FNAL/MicrobooNE

    FNAL Don Lincoln

    FNAL/MINOS

    FNAL Cryomodule Testing Facility

    FNAL Minos Far Detector

    FNAL LBNF/DUNE from FNAL to SURF, Lead, South Dakota, USA

    FNAL/NOvA experiment map

    FNAL NOvA Near Detector

    FNAL ICARUS

    FNAL Holometer

     
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