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  • richardmitnick 11:21 am on May 5, 2020 Permalink | Reply
    Tags: "Four years of calculations lead to new insights into muon anomaly", , , Mira an IBM Blue Gene Q supercomputer at the Argonne Leadership Computing Facility a Department of Energy user facility   

    From Argonne National Laboratory: “Four years of calculations lead to new insights into muon anomaly” 

    Argonne Lab
    News from From Argonne National Laboratory

    May 5, 2020
    Christina Nunez

    Using Argonne’s supercomputer Mira, researchers have come up with newly precise calculations aimed at understanding a key disconnect between physics theory and experimental measurements.

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

    Two decades ago, an experiment at the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory pinpointed a mysterious mismatch between established particle physics theory and actual lab measurements. When researchers gauged the behavior of a subatomic particle called the muon, the results did not agree with theoretical calculations, posing a potential challenge to the Standard Model — our current understanding of how the universe works.

    Ever since then, scientists around the world have been trying to verify this discrepancy and determine its significance. The answer could either uphold the Standard Model, which defines all of the known subatomic particles and how they interact, or introduce the possibility of an entirely undiscovered physics. A multi-institutional research team (including Brookhaven, Columbia University, and the universities of Connecticut, Nagoya and Regensburg, RIKEN) have used Argonne National Laboratory’s Mira supercomputer to help narrow down the possible explanations for the discrepancy, delivering a newly precise theoretical calculation that refines one piece of this very complex puzzle. The work, funded in part by the DOE’s Office of Science through its Office of High Energy Physics and Advanced Scientific Computing Research programs, has been published in the journal Physical Review Letters.

    A muon is a heavier version of the electron and has the same electric charge. The measurement in question is of the muon’s magnetic moment, which defines how the particle wobbles when it interacts with an external magnetic field. The earlier Brookhaven experiment, known as Muon g-2 [since moved to FNAL], examined muons as they interacted with an electromagnet storage ring 50 feet in diameter. The experimental results diverged from the value predicted by theory by an extremely small amount measured in parts per million, but in the realm of the Standard Model, such a difference is big enough to be notable.

    FNAL Muon g-2 studio

    Standard Model of Particle Physics, Quantum Diaries

    “If you account for uncertainties in both the calculations and the measurements, we can’t tell if this is a real discrepancy or just a statistical fluctuation,” said Thomas Blum, a physicist at the University of Connecticut who co-authored the paper. ​“So both experimentalists and theorists are trying to improve the sharpness of their results.”

    As Taku Izubuchi, a physicist at Brookhaven Lab who is a co-author on the paper, noted, ​“Physicists have been trying to understand the anomalous magnetic moment of the muon by comparing precise theoretical calculations and accurate experiments since the 1940s. This sequence of work has led to many discoveries in particle physics and continues to expand the limits of our knowledge and capabilities in both theory and experiment.”

    If the discrepancy between experimental results and theoretical predictions is indeed real, that would mean some other factor — perhaps some yet-to-be discovered particle — is causing the muon to behave differently than expected, and the Standard Model would need to be revised.

    The team’s work centered on a notoriously difficult aspect of the anomaly involving the strong interaction, which is one of four basic forces in nature that govern how particles interact, along with weak, electromagnetic, and gravitational interactions. The biggest uncertainties in the muon calculations come from particles that interact through the strong force, known as hadronic contributions. These hadronic contributions are defined by a theory called quantum chromodynamics (QCD).

    The researchers used a method called lattice QCD to analyze a type of hadronic contribution, light-by-light scattering. ​“To do the calculation, we simulate the quantum field in a small cubic box that contains the light-by-light scattering process we are interested in,” said Luchang Jin, a physicist at the University of Connecticut and paper co-author. ​“We can easily end up with millions of points in time and space in the simulation.”

    That’s where Mira came in. The team used the supercomputer, housed at the Argonne Leadership Computing Facility (ALCF), to solve the complex mathematical equations of QCD, which encode all possible strong interactions with the muon. The ALCF, a DOE Office of Science User Facility, recently retired Mira to make room for the more powerful Aurora supercomputer, an exascale system scheduled to arrive in 2021.

    “Mira was ideally suited for this work,” said James Osborn, a computational scientist with the ALCF and Argonne’s Computational Science division. ​“With nearly 50,000 nodes connected by a very fast network, our massively parallel system enabled the team to run large simulations very efficiently.”

    After four years of running calculations on Mira, the researchers produced the first-ever result for the hadronic light-by-light scattering contribution to the muon anomalous magnetic moment, controlling for all errors.

    “For a long time, many people thought this contribution, because it was so challenging, would explain the discrepancy,” Blum said. ​“But we found previous estimates were not far off, and that the real value cannot explain the discrepancy.”

    Meanwhile, a new version of the Muon g-2 experiment is underway at Fermi National Accelerator Laboratory [above], aiming to reduce uncertainty on the experimental side by a factor of four. Those results will add more insight to the theoretical work being done now.

    “As far as we know, the discrepancy still stands,” Blum said. ​“We are waiting to see whether the results together point to new physics, or whether the current Standard Model is still the best theory we have to explain nature.”

    See the full article here .

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    Please help promote STEM in your local schools.

    Stem Education Coalition

    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.

    The Advanced Photon Source at Argonne National Laboratory is one of five national synchrotron radiation light sources supported by the U.S. Department of Energy’s Office of Science to carry out applied and basic research to understand, predict, and ultimately control matter and energy at the electronic, atomic, and molecular levels, provide the foundations for new energy technologies, and support DOE missions in energy, environment, and national security. To learn more about the Office of Science X-ray user facilities, visit http://science.energy.gov/user-facilities/basic-energy-sciences/.

    Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science

    Argonne Lab Campus

     
  • richardmitnick 1:38 pm on December 5, 2018 Permalink | Reply
    Tags: , Astronomical magnetism, , Mira an IBM Blue Gene Q supercomputer at the Argonne Leadership Computing Facility a Department of Energy user facility, NASA’s Pleiades supercomputer, Nick Featherstone- University of Colorado Boulder   

    From ASCR Discovery: “Astronomical magnetism” 

    From ASCR Discovery
    ASCR – Advancing Science Through Computing

    Modeling solar and planetary magnetic fields is a big job that requires a big code.

    1
    Convection models of the sun, with increasing amounts of rotation from left to right. Warm flows (red) rise to the surface while others cool (blue). These simulations are the most comprehensive high-resolution models of solar convection so far. See video here.

    Image courtesy of Nick Featherstone, University of Colorado Boulder.

    It’s easy to take the Earth’s magnetic field for granted. It’s always on the job, shielding our life-giving atmosphere from the corrosive effects of unending solar radiation. Its constant presence also gives animals – and us — clues to find our way around.

    This vital force has protected the planet since long before humans evolved, yet its source – the giant generator of a heat-radiating, electricity-conducting liquid iron core swirling as the planet rotates – still holds mysteries. Understanding the vast and complex turbulent features of Earth’s dynamo – and that of other planets and celestial bodies – has challenged physicists for decades.

    “You can always do the problem you want to, but just a little bit,” says Nick Featherstone, research associate at the University of Colorado Boulder. Thanks to his efforts, however, researchers now have a computer code that lets them come closer than ever to simulating these features in detail across a whole planet or star. The program, known as Rayleigh, is open-source and available to anyone.

    To demonstrate the power of Rayleigh’s algorithms, a research team has simulated the dynamics of the sun, Jupiter and Earth in unprecedented detail. The project has been supported with a Department of Energy Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program allocation of 260 million processor hours on Mira, an IBM Blue Gene Q supercomputer at the Argonne Leadership Computing Facility, a Department of Energy user facility.

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

    2
    Earth’s liquid metal core produces a complex combination of outward (red) and inward (blue) flows in this dynamo simulation. Image courtesy of Rakesh Yadav, Harvard University.

    This big code stemmed from Featherstone’s research in solar physics. Previously scientists had used computation to model solar features on as many as a few hundred processor cores simultaneously, or in parallel. But Featherstone wanted to tackle larger problems that were intractable using available technology. “I spent a lot of time actually looking at the parallel algorithms that were used in that code and seeing where I could change things,” he says.

    When University of California, Los Angeles geophysicist Jonathan Aurnou saw Featherstone present his work at a conference in 2012, he was immediately impressed. “Nick has built this huge, huge capability,” says Aurnou, who leads the Geodynamo Working Group in the Computational Infrastructure for Geodynamics (CIG) based at the University of California, Davis. Though stars and planets can behave very differently, the dynamo in these bodies can be modeled with adjustments to the same fundamental algorithms.

    Aurnou soon recruited Featherstone to develop a community code – one researchers could share and improve – based on his earlier algorithms. The team initially performed simulations on up to 10,000 cores of NASA’s Pleiades supercomputer.

    NASA SGI Intel Advanced Supercomputing Center Pleiades Supercomputer

    But the scientists wanted to go bigger. Previous codes are like claw hammers, but “this code – it’s a 30-pound sledge,” Aurnou says. “That changes what you can swing at.”

    In 2014 Aurnou, Featherstone and their colleagues proposed three big INCITE projects focusing on three bodies in our solar system: the sun, a star; Jupiter, a gas giant planet; and Earth, a rocky planet. Mira’s 786,000 processor cores let the team scale up their calculations by a factor of 100, Featherstone says. Adds Aurnou, “You can think of Mira as a place to let codes run wild, a safari park for big codes.”

    The group focused on one problem each year, starting with Featherstone’s specialty: the sun. In its core, hydrogen atoms fuse to form helium, releasing high-energy photons that bounce around a dense core for thousands of years. They eventually diffuse to an outer convecting layer, where they warm plasma pockets, causing them to rise to the surface. Finally, the energy reaches the surface, the photosphere, where it can escape, reaching Earth as light within minutes. Like planets, the sun rotates, producing chaotic forces and its own magnetic poles that reverse every 11 years. The processes that cause this magnetic reversal remain largely unknown.

    Featherstone broke down this complex mixture of activity into components across the whole star. “What I’ve been able to do with the INCITE program is to start modeling convection in the sun both with and without rotation turned on and at very, very high resolution,” Featherstone says. The researchers plan to incorporate magnetism into the models next.

    The team then moved on to Jupiter, aiming to predict and model the results of NASA’s Juno probe, which orbits that planet. In Jupiter’s core – the innermost 95 percent – hydrogen is compressed so tightly that the electrons pop off. The mass behaves like a metal ball, Aurnou says. Its core also releases heat in an amount equal to what the planet receives from the sun. All that convective turbulence also rotates, creating a potent planetary magnetic field, he says.

    Until recent results from Juno, scientists didn’t know that surface jets on Jupiter extend deep – thousands of kilometers – into the planet. Juno’s images reveal clusters of geometric turbulence – pentagons, octagons and more – grouped around the Jovian poles.

    3
    A model of interacting vortices simulating turbulent jets that resemble those observed on Jupiter. Yellow features are rotating counterclockwise, while blue features rotate clockwise. Image courtesy of Moritz Heimpel, University of Alberta.

    Even before the Juno results were published in March, the CIG team had simulated deep jets and their interactions with Jupiter’s surface and magnetic core. The team is well-poised to help physicists better understand these unusual stormy features, Aurnou adds. “We’re going to be using our big simulations and the analysis that we’re now carrying out to try to understand the Juno data.”

    In its third year the team modeled the behavior of Earth’s magnetic field, a system where they had far more data from observations. Nonetheless, our home still harbors geophysical puzzles. Earth has an outer core of molten iron and a hard rocky crust that contains it. The magnetic poles drift – and can even flip – but the process takes a few hundred thousand years and doesn’t occur on a regular schedule. “Earth’s magnetic field is complex – messy – both in time and space,” Aurnou says. “That mess is where all the fun is.”

    Turbulence is difficult to simulate because it includes the cumulative effects of minuscule changes coupled with processes that are occurring over large parts of a planet.

    “[In our Earth model] we’ve made, in a sense, as messy a dynamo simulation as possible,” Aurnou says. Previous researchers modeling Earth have argued that tweaks to physics were needed to explain features such as the constant magnetic-pole shifts. “We’ve actually found with our Mira runs, that, no, we don’t need any extra ingredients. We just need turbulence.”

    With these results, the team hopes to pare down simulations to incorporate the simplest set of inputs needed to understand our complex terrestrial system.

    The INCITE project results are fueling new research opportunities already. Based on the team’s solar findings, in 2017 Featherstone received a $1 million grant from NASA’s Heliophysics Grand Challenge program, which supports research into solar physics problems that require both theory and observation.

    The project shows how federal funding can dovetail to help important science reach its potential, Aurnou says. CIG originally hired Featherstone using National Science Foundation funds, which led to the INCITE grant, followed by this NASA project, which will model even more of the sun’s fundamental physics. That information could help protect astronauts from solar radiation and shield our electrical grids from damage and outages during periods of high solar activity.

    Eventually the team would like to model the reversal of magnetic poles on Earth, which requires accounting for daily rotation over hundreds of thousands of years. “That’s going to cost us,” Aurnou says. “We need to get a more efficient code for that and faster computers.”

    See the full article here.


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    Please help promote STEM in your local schools.

    Stem Education Coalition

    ASCRDiscovery is a publication of The U.S. Department of Energy

     
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