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  • richardmitnick 2:13 pm on October 20, 2020 Permalink | Reply
    Tags: , , Fermilab, , ,   

    From Symmetry: “The many paths of muon math” 

    Symmetry Mag
    From Symmetry<

    10/20/20
    Daniel Garisto

    1
    Illustration by Sandbox Studio, Chicago with Ariel Davis.

    Here’s how physicists calculate g-2, the value that will determine whether the muon is giving us a sign of new physics.

    Like racecars on a track, thousands of particles called muons zip around an experiment’s giant 50-foot circular magnet at 99.9% of the speed of light. After making a few hundred laps in less than a millisecond, the muons decay and are soon replaced by another bunch.

    FNAL Muon g-2 studio.

    The goal of the experiment, Fermilab Muon g-2, is to better understand the properties of muons, which are essentially heavier versions of electrons, and use them to probe the limitations of the Standard Model of particle physics. Specifically, physicists want to know about the muons’ “magnetic moment”—that is, how much do they rotate on their axes in a powerful magnetic field— as they race around the magnet?

    In 2001, an experiment at the US Department of Energy’s Brookhaven National Lab found that the muons turned more than theory predicted.

    Brookhaven Muon g-2 ring.

    FNAL G-2 magnet from Brookhaven Lab finds a new home in the FNAL Muon G-2 experiment.

    The result surprised the physics community: If there really were a discrepancy, it could be a hint of new physics, like some as-yet-unknown particle influencing the muon. Two decades later, physicists hope to resolve the matter. Fermilab Muon g-2 aims to quadruple the precision of the 2001 finding and determine whether experiment really disagrees with theory.

    There’s another side to the search though—one that’s carried out not with particle accelerators and giant magnets, but with equations on blackboards and computer simulations. Since 2016, another group of physicists has been trying to update the theoretical prediction of the muon’s magnetic moment by combining the efforts of several groups.

    In June, the Muon g-2 Theory Initiative, which comprises 132 physicists across 82 institutions, published its first prediction: They calculated the muon’s anomalous magnetic moment, or αµ, to be 116,591,810×10-11. The value differs subtly, but significantly from the 2001 experiment, which found αµ to be 116,592,089×10-11. (That’s a difference of 279 parts in a million, for those keeping score at home.)

    “This is the first time that the entire community has come together and reached a consensus on the Standard Model prediction of this quantity,” says Aida X. El-Khadra, a physicist at the University of Illinois Urbana-Champaign and cofounder of the Theory Initiative. Previously, individual groups produced their own predictions of αµ, which differed slightly from one another.

    By combining their efforts, physicists in the Theory Initiative hope that they’ll be able to come up with an ultra-precise prediction to complement the forthcoming result from the Fermilab Muon g-2 experiment. Both the experiment and the theory initiative receive support from DOE’s Office of Science.

    But just how do physicists predict something like the muon’s magnetic moment, and why does it take 132 of them?

    The path to g-2

    The first calculations of particle magnetic moments came in the 1920s, when physicists were just beginning to develop relativistic quantum mechanics. British theoretical physicist Paul Dirac, building on the work of Llewellyn Thomas and others, found the ultimate equation describing the electron and its spin—then conceived of as the electron’s internal rotation—and its magnetic moment. Dirac predicted this number, called “g,” to be exactly 2.

    But atomic spectroscopy experiments soon found that g differed from that prediction by about 0.1%—a so-called “anomalous” magnetic moment, αe. In 1947, Julian Schwinger developed a theoretical explanation: The electron could emit and then reabsorb a virtual photon, which slightly changed its interaction with a magnetic field.

    “Every way that something can happen in nature will happen,” says Tom Blum, a theoretical physicist at the University of Connecticut. “If a particle starts from here and gets to there, it can take all possible paths to get from there to there. And what quantum field theory tells us is how to weight those paths.”

    The emission and absorption of a single virtual photon is just the most straightforward of these possible particle paths. Since Schwinger, physicists have been working to calculate increasingly unlikely possible paths that a particle can take. Ironically, the way they think about these paths is with a tool of Schwinger’s rival, Richard Feynman. To illustrate the paths and calculate their probabilities, Feynman developed his eponymously named diagrams.

    Here, the Feynman diagram represents a muon (the Greek letter mu) moving left to right in a magnetic field (the squiggly line, which also denotes a photon).

    3

    The Feynman diagram for Schwinger’s path is slightly more complicated—this time there’s a squiggly blue line, the virtual photon being emitted and absorbed by the muon. This contributes approximately 0.00116 to αµ. This is the vast majority of muon’s anomalous magnetic moment.

    4

    To make the task manageable, the Theory Initiative segmented the task of calculating the muon’s magnetic moment into each component. To get down to a precision of about 100 parts in a billion, physicists have had to calculate a lot more than just a single virtual photon.

    “Contributions to the anomalous magnetic moment come from the three different interactions— the strong interaction, the weak interaction and quantum electrodynamics all contribute,” Blum says.

    There was at one point some thought that gravity would have an impact, but further investigation proved its role was too small.

    Quantum electrodynamics, or QED, covers all the possible ways a photon can interact with a muon. To get better precision, physicists can account for more virtual photons. Each additional virtual photon has about 1/137th the chance of being produced and reabsorbed, so a Feynman diagram with two virtual photons contributes about 1 / 137 * 137 to αµ, three virtual photons contribute 1 / 137 * 137 * 137, and so on. Physicists have even gone all the way to five virtual photons.

    With five virtual photons, there are more than 10,000 possible paths, so there are a corresponding number of Feynman diagrams to calculate. Possibilities abound because virtual photons can split into a virtual electron and a virtual positron (the antimatter counterpart to an electron). This virtual pair can then annihilate back into a virtual photon. Describing these complex paths requires loops and squiggles that arc over each other. Five-photon Feynman diagrams look less like a traditional particle physics schematic and more like abstract art.

    6

    The weak force and the strong force

    The weak force, which governs the radioactive decay of nuclei, also plays a role in influencing the muon’s magnetic moment. Unlike QED, which is mediated by the massless photon, the weak force is mediated by the massive W and Z bosons, which each weigh about 90 times the mass of a proton. The fact that the bosons are heavy makes it extremely unlikely that the muon would emit and absorb a virtual W or Z boson. But occasionally, it does happen.

    7

    Both QED and the contribution from the weak force can be calculated to extremely high precision. The process is arduous, but physicists can calculate a good deal of the interactions simply by hand. That’s not the case with contributions from particles bound together by the strong force called hadrons, which represent the majority of uncertainty in the calculation of the muon’s anomalous magnetic moment.

    Gluons, the particles that mediate the strong force, are described by the rules of quantum chromodynamics, or QCD. Unlike photons in QED, gluons can interact with one another. Trying to calculate QCD processes by hand is effectively impossible, because the self-interacting gluons throw everything out of whack.

    “The reason why we need a collaborative effort is because the hadronic corrections cannot be calculated from first principle QCD on a blackboard,” says El-Khadra.

    There are two main types of hadronic corrections: “vacuum polarization” corrections and “light by light” corrections. In vacuum polarization, the muon emits a virtual photon, which decays into a quark and antiquark. These quarks and antiquarks exchange gluons, turning into a frothing blob of hadronic matter such as pions and kaons. Finally, the virtual blob of hadronic matter ends when a quark and antiquark annihilate back into a virtual photon, which is finally absorbed by the muon.

    8

    Light by light contributions are perhaps some of the strangest. From the outside, it looks as if two virtual photons are emitted by a muon, interact, and are then absorbed. What’s going on here?

    “When we look around us… the reason why we can see very well is because photons—to a large degree—don’t interact with each other,” says Christoph Lehner, a physicist at Brookhaven National Lab and cofounder of the Theory Initiative.

    But if the two virtual photons get caught in a quark loop, each converting to a virtual quark and virtual antiquark, they can form a blob of hadronic matter. If the virtual quarks and virtual antiquarks annihilate back into virtual photons, the two will appear to have bounced off of one another, interacting in a forbidden way.

    Traditionally, hadronic corrections to αµ were calculated using so-called “dispersion relations.” Physicists modeling the virtual blob of hadronic matter would turn to experiments where real blobs of hadronic matter were created. Real blobs are produced in experiments where electrons collide with positrons, creating a spray of hadronic matter. Experiments like BaBar, KLOE and now Belle II all provide this kind of data, which physicists have scoured to better understand the virtual blobs.

    A contribution from supercomputing

    Recently, another method for calculating messy hadronic blobs has become viable, thanks to increasingly powerful computers and improved algorithms. Lattice QCD is a method for essentially simulating the blob from the ground up. Physicists write in the properties of the particles and the forces that govern them, set up a giant sandbox (a lattice) that the system can evolve in, and let it run. Lattice QCD is hugely computationally intensive—to produce a precise simulation, supercomputers have to calculate all of the gluon interchanges, a task that was impossible by hand.

    Because it’s a simulation of the real world from first principles, “it’s in that sense very similar to an experiment,” according to Lehner.

    One benefit is that physicists can be confident that their approach provides an answer to the question. The downsides, as in any experiment, are systematic errors—and the amount of resources required. Finding computer time is easier said than done, but at the end of the day, lattice QCD is approaching the precision of the dispersion relation method.

    Contribution—————————————–Value (x10-11)
    QED ———————————————116,584,718.931±.104
    Weak force——————————————-153.6±1.0
    Hadronic vacuum polarization (dispersive)————6,845±40
    NOT USED (Lattice hadronic vacuum polarization)——7116±184
    Hadronic light-by-light (dispersive+lattice)———92±18
    Total Standard Model Value ————————–116,591,810±43
    Difference from 2001 experiment———————-279±76

    Putting it all together

    In February, a lattice QCD group claimed to have a result for hadronic contributions in serious conflict with the predictions of dispersive relations. Almost immediately, a flurry of other publications discussing and challenging the result followed. The June paper from the Theory Initiative does not address the potential inconsistency, but lattice QCD researchers are hard at work trying to replicate the result.

    At the end of the day, when the experimentalists finish analyzing the data from the Muon g-2 experiment, they’ll compare against the theoretical value to see if there’s still a significant discrepancy. The hope, for many, is that they continue to disagree, opening a window for new physics.

    See the full article here .


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

    Please help promote STEM in your local schools.


    Stem Education Coalition

    Symmetry is a joint Fermilab/SLAC publication.


     
  • richardmitnick 7:46 pm on May 29, 2018 Permalink | Reply
    Tags: Adaptive Input/Output System (ADIOS) and the BigData Express (BDE), Fermilab, , ,   

    From Fermilab and OLCF: “ADIOS and BigData Express offer new data streaming capabilities” 

    FNAL II photo

    FNAL Art Image
    FNAL Art Image by Angela Gonzales

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

    1

    Projects large enough to run on high-performance computing (HPC) resources pack data—and a lot of it. Transferring this data between computational and experimental facilities is a challenging but necessary part of projects that rely on experiments to validate computational models.

    Staff at two U.S. Department of Energy (DOE) Office of Science User Facilities — the Oak Ridge Leadership Computing Facility (OLCF) and Fermi National Accelerator Laboratory — facilitated this process by executing the integration of the Adaptive Input/Output System (ADIOS) and the BigData Express (BDE) high-speed data transfer service.

    Now ADIOS and BDE developers are changing the way researchers can transport and analyze data by incorporating a new methodology into the tool that allows for compressing and streaming of data coming out of simulations in real time. The methodology is being tested by OLCF user C. S. Chang, a plasma physics researcher at Princeton Plasma Physics Laboratory (PPPL) who studies the properties of the plasmas that exist in giant fusion devices called tokamaks.

    PPPL NSTX -U at Princeton Plasma Physics Lab, Princeton, NJ,USA

    Chang seeks an understanding of the power needed to run ITER and the heat load to the material wall that will surround its plasma, both of which are key to fusion’s viability.

    ITER Tokamak in Saint-Paul-lès-Durance, which is in southern France

    ITER is an international collaboration working to design, construct, and assemble a burning plasma experiment that can demonstrate the scientific and technological feasibility of fusion power for the commercial power grid. ITER, which counts DOE’s Oak Ridge National Laboratory (ORNL) among its partners, is currently under construction in southern France.

    “If users can separate out the most important pieces of data and move those to another processor that can recognize the intended prioritization and reduce the data, it can provide them with feedback that they may need to stop a simulation if necessary,” said Scott Klasky, leader of the ADIOS framework and group leader for ORNL’s Scientific Data Group.

    Wenji Wu, principal investigator of the BDE project and principal network research investigator of Fermilab’s Core Computing Division, added, “The new approach leverages the software-defining network [SDN] capabilities for resource scheduling and the high-performance data streaming capabilities of BDE.”

    SDN allows users to dynamically control network resources rather than manually request to connect.

    “This combination enables real-time data streaming with guaranteed quality of service, whether it be over short or long distances,” Wu said. “In addition, this approach yields small memory footprints.”

    Although the project is still in the development phase, preliminary tests allowed Chang and his team to successfully transfer fusion data between the OLCF — located at ORNL — and PPPL.

    “With this new methodology, users can stream data on the network without ever touching the file system and request network resources on the fly,” said ADIOS and BDE researcher Qing Liu, who has a joint appointment with the New Jersey Institute of Technology and ORNL.

    Without streaming capabilities, scientists can perform only after-the-fact analyses for many experiments, such as KSTAR, the Korean Superconducting Tokamak Advanced Research.

    KSTAR Korean Superconducting Tokamak Advanced Research

    But with simulations and experiments increasing in size, near–real-time monitoring and control are becoming necessary. The new ADIOS–BDE integration could also play a major role in large experimental projects, such as the fusion project Chang is leading and the Square Kilometer Array, an effort involving dozens of institutions to build the world’s largest radio telescope.

    SKA Square Kilometer Array

    The new streaming capabilities could more easily enable the capture of short-lived events such as pulsars — neutron stars that emit electromagnetic radiation — that the telescope aims to record.

    “KSTAR wants to transfer their data as the experiment is happening, to process their data during the experiment,” Klasky said. “These additions to ADIOS will enable both sides to quickly perform data analysis and visualization in real time.”

    Seo-Young Noh, director of the Global Science Experimental Data Hub Center at the Korea Institute of Science and Technology Information, leads a group that has contributed significantly to the BDE project.

    “Our work has made cross-Pacific, real-time data streaming possible,” Noh said.

    Klasky, Liu, and their collaborators will give a best paper plenary talk related to these new capabilities—titled “Understanding and Modeling Lossy Compression Schemes on HPC Scientific Data” — at the 32nd IEEE International Parallel and Distributed Processing Symposium. The team noted that the new ADIOS methodology will allow scientists to efficiently select the type of compression that will best fit their scientific and research needs, affording them the ability to analyze their data faster than ever before.

    Liang Zhang, the developer of BDE data streaming capabilities, is working with Liu to enhance and test the tool. They expect the tool’s new capabilities to be fully tested and deployed by late 2019. This work also involves ADIOS researcher Jason Wang and BDE researchers Nageswara Rao, Phil DeMar, Qiming Lu, Sajith Sasidharan, S. A. R. Shah, Jin Kim, and Huizhang Luo.

    ORNL is managed by UT-Battelle for the Department of Energy’s Office of Science, the single largest supporter of basic research in the physical sciences in the United States. DOE’s Office of Science is working to address some of the most pressing challenges of our time. For more information, please visit science.energy.gov.

    See the full article here .


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

    stem

    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

     
  • richardmitnick 3:18 pm on April 29, 2018 Permalink | Reply
    Tags: , Fermilab, Length contraction: the real explanation,   

    From Don Lincoln at Fermilab: “Length contraction: the real explanation” Video 

    FNAL II photo

    FNAL Art Image
    FNAL Art Image by Angela Gonzales

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

    FNAL’s Don Lincoln

    Relativity has many mind-bending consequences, but one of the weirdest is the idea that objects in motion get shorter. Bizarre or not, Fermilab’s Dr. Don Lincoln explains just how it works. You’ll be a believer.

    See the full article here .

    Please help promote STEM in your local schools.

    STEM Icon

    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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