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Events at Physics

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Events During the Week of November 1st through November 7th, 2020

Monday, November 2nd, 2020

Plasma Physics (Physics/ECE/NE 922) Seminar
Magnetic Reconnection and the Acceleration of Electrons in Macroscale Systems
Time: 12:00 pm
Place: ZOOM Meeting
Speaker: Dr. Marc Swisdak, University of Maryland
Abstract: Magnetic reconnection is a ubiquitous process that transfers energy from the magnetic field to the surrounding plasma. It is believed to trigger such energetic events as tokamak sawtooth crashes, magnetospheric substorms, and solar and astrophysical flares. I will first outline the current understanding of this phenomenon and then focus particularly on the production of non-thermal (energetic) particles. In the case of solar flares, the spectra of energetic electrons take the form of power laws that extend decades in energy and can account for half of the released magnetic energy. New simulations, based on a recently developed model that marries MHD and kinetic physics, will be discussed that have produced the first self-consistent power-law distributions in a macroscale system. The drive mechanism is Fermi reflection in growing and merging magnetic flux ropes. A strong guide field is found to suppress the production of nonthermal electrons by increasing the radius of curvature of reconnected field lines and therefore weakening the Fermi drive mechanism. The results are benchmarked with the hard x-ray, radio and extreme ultra-violet (EUV) observations of the X8.2-class solar flare on September 10, 2017.

Connection information:

Join Zoom Meeting
https://uwmadison.zoom.us/j/99156107574?pwd=RnA0ZnJHbDdlOHN1dkpFYUVYcWZpUT09

Meeting ID: 991 5610 7574
Passcode: 883688
Host: Paul Terry
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Tuesday, November 3rd, 2020

Academic Calendar
Election Day, including same-day registration
Time: 7:00 am
Place:
Abstract: Election for President, US Rep., State legislature, DA, County Clerk, Treasurer, and Reg of Deeds.. Election for President, U.S. Representative, State Senate, State Assembly, District Attorney, County Clerk, County Treasurer, and Register of Deeds. Go to MyVote.wi.gov to find your assigned polling place, see what is on your ballot, and check your registration. If you are not registered at your current address, you can register at your polling place on Election Day. See vote.wisc.edu for information on registration and voter ID. CONTACT: malischke@yahoo.com URL: https://myvote.wi.gov
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Wednesday, November 4th, 2020

Wisconsin Quantum Institute
QuantHEP Seminar
APPLICATION OF QUANTUM MACHINE LEARNING TO HIGH ENERGY PHYSICS ANALYSIS AT LHC USING QUANTUM COMPUTER SIMULATORS AND QUANTUM COMPUTER HARDWARE
Time: 10:00 am
Place: Livestreaming on QuantHEP Seminar YouTube channel: https://www.youtube.com/channel/UC44_wEmSKR55S2RM
Speaker: Sau Lan Wu, UW–Madison Physics, CERN
Abstract: Machine learning enjoys widespread success in High Energy Physics (HEP) analysis at LHC. However the ambitious HL-LHC program will require much more computing resources in the next two decades. Quantum computing may offer speed-up for HEP physics analysis at HL-LHC, and can be a new computational paradigm for big data analysis in High Energy Physics.

We have successfully employed Variational Quantum Classifier (VQC) method, Quantum Support Vector Machine Kernel (QSVM-kernel) method and Quantum Neural Network (QNN) method for two LHC flagship analyses: ttH (Higgs production in association with two top quarks) and H->mumu (Higgs decay to two muons, the second generation fermions).

We will present our experiences and results of a study on LHC High Energy Physics data analysis with IBM Quantum Simulator and Quantum Hardware (using IBM Qiskit framework), Google Quantum Simulator (using Google Cirq framework), and Amazon Quantum Simulator (using Amazon Braket cloud service). The work is in the context of a Qubit platform. Taking into account the present limitation of hardware access, different quantum machine learning methods are studied on simulators and the results are compared with classical machine learning methods (BDT, classical Support Vector Machine and classical Neural Network). Furthermore, we do apply quantum machine learning on IBM quantum hardware to compare performance between quantum simulator and quantum hardware.

The work is performed by an international and interdisciplinary collaboration with the Department of Physics and Department of Computer Sciences of University of Wisconsin, CERN Quantum Technology Initiative, IBM Research Zurich, Fermilab Quantum Institute, BNL Computational Science Initiative, State University of New York at Stony Brook, and Quantum Computing and AI Research of Amazon Web Services.

This work pioneers a close collaboration of academic institutions with industrial corporations in a High Energy Physics analysis effort.

Although the era of efficient quantum computing may still be years away, we have made promising progress and obtained preliminary results in applying quantum machine learning to High Energy Physics. A PROOF OF PRINCIPLE.
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NPAC (Nuclear/Particle/Astro/Cosmo) Forum
QuantHEP – Quantum Computing Solutions for High-Energy Physics
Time: 10:00 am
Place: https://quanthep-seminar.org/session/session-2/
Speaker: Prof. Sau Lan Wu, University of Wisconsin - Madison
Abstract: APPLICATION OF QUANTUM MACHINE LEARNING TO HIGH ENERGY PHYSICS ANALYSIS AT LHC USING QUANTUM COMPUTER SIMULATORS AND QUANTUM COMPUTER HARDWARE

https://quanthep-seminar.org/session/session-2/
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Physics ∩ ML Seminar
Flow-based likelihoods for non-Gaussian inference
Time: 11:00 am
Place: Online Seminar: Please sign up for our mailing list at www.physicsmeetsml.org for zoom link
Speaker: Ana Diaz Rivero, Harvard University
Abstract: We investigate the use of data-driven likelihoods to bypass a key assumption made in many scientific analyses, which is that the true likelihood of the data is Gaussian. In particular, we suggest using the optimization targets of flow-based generative models, a class of models that can capture complex distributions by transforming a simple base distribution through layers of nonlinearities. We call these flow-based likelihoods (FBL). We analyze the accuracy and precision of the reconstructed likelihoods on mock Gaussian data, and show that simply gauging the quality of samples drawn from the trained model is not a sufficient indicator that the true likelihood has been learned. We nevertheless demonstrate that the likelihood can be reconstructed to a precision equal to that of sampling error due to a finite sample size. We then apply FBLs to mock weak lensing convergence power spectra, a cosmological observable that is significantly non-Gaussian (NG). We find that the FBL captures the NG signatures in the data extremely well, while other commonly-used data-driven likelihoods, such as Gaussian mixture models and independent component analysis, fail to do so. This suggests that works that have found small posterior shifts in NG data with data-driven likelihoods such as these could be underestimating the impact of non-Gaussianity in parameter constraints. By introducing a suite of tests that can capture different levels of NG in the data, we show that the success or failure of traditional data-driven likelihoods can be tied back to the structure of the NG in the data. Unlike other methods, the flexibility of the FBL makes it successful at tackling different types of NG simultaneously. Because of this, and consequently their likely applicability across datasets and domains, we encourage their use for inference when sufficient mock data are available for training.
Host: Gary Shiu
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Department Meeting
Time: 12:15 pm
Place: Virtual see "abstract" for connection info
Speaker: Sridhara Dasu, Department Chair, UW-Madison
Meeting Coordinates: Meeting number: 120 392 9242 Password: Q5EjaTz3Pk3 (75352893 from phones) https://uwmadison.webex.com/uwmadison/j.php?MTID=m4be4e8a6254fdcd033b6c946ffeee6c8 Join by video system Dial 1203929242@uwmadison.webex.com You can also dial 173.243.2.68 and enter your meeting number. Join by phone +1-415-655-0001 US Toll +1-312-535-8110 United States Toll (Chicago) Access code: 120 392 9242
Host: Sridhara Dasu, Department Chair
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Thursday, November 5th, 2020

Cosmology Journal Club
Time: 12:00 pm
Place:
Abstract: Cosmology Journal Club is back! We will be having virtual meetings this semester.

Each week, we start with a couple scheduled 15 minute talks about one's research, or an arXiv paper. The last 30 minutes will typically be open to the group for anyone to discuss an arXiv paper.

All are welcome and all fields of cosmology are appropriate.

Contact Ross Cawthon, cawthon@wisc, for more information.
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NPAC (Nuclear/Particle/Astro/Cosmo) Forum
Study of triple heavy boson production at the LHC
Time: 3:00 pm
Place: Zoom : https://uwmadison.zoom.us/j/91932930074?pwd=ZWJHaU02K2pHZCswZXJHdWx1Y2Vzdz09
Speaker: Hannsjörg Weber, Fermilab
Host: Sridhara Dasu
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Astronomy Colloquium
The Experiment for Cryogenic Large-aperture Intensity Mapping (EXCLAIM)
Time: 3:30 pm
Place: Zoom meeting(see Abstract ) Coffee and tea 3:30pm, Talk 3:45pm
Speaker: Eric Switzer, NASA/Goddard
Abstract: The EXperiment for Cryogenic Large-Aperture Intensity Mapping (EXCLAIM) is a cryogenic balloon-borne instrument that will survey galaxy and star formation history over cosmological time scales. Rather than identifying individual objects, EXCLAIM will be a pathfinder to demonstrate an intensity mapping approach, which measures the cumulative redshifted line emission. EXCLAIM will operate at 420-540 GHz with a spectral resolution R=512 to measure the integrated CO and [CII] in redshift windows spanning 0 < z < 3.5. CO and [CII] line emissions are key tracers of the gas phases in the interstellar medium involved in star-formation processes. EXCLAIM will shed light on questions such as why the star formation rate declines at z < 2, despite continued clustering of the dark matter. The instrument will employ an array of six superconducting integrated grating-analog spectrometers (micro-spec) coupled to microwave kinetic inductance detectors (MKIDs). I will present an overview of the EXCLAIM instrument design and status.

The Zoom Link:

https://us02web.zoom.us/j/88513896776?pwd=Y1JtRE1KZllxWkFTamJBSGtGdm9yQT09
Host: Peter Timbe, UW Physics Dept
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Friday, November 6th, 2020

Graduate Introductory Seminar (Physics 701)
The Energy Frontier at the LHC
Time: 12:05 pm
Place: BBCollaborate
Speaker: Kevin Black, UW Madison Department of Physics
Host: Sridhara Dasu
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Theory Seminar (High Energy/Cosmology)
Heavy Neutrinos and Where to Find Them
Time: 2:00 pm
Place: For zoom link, sign up at: https://groups.google.com/a/g-groups.wisc.edu/d/forum/theoryseminars/join
Speaker: Kevin Kelly, Fermilab
Abstract: The discovery of neutrino oscillations led to a new understanding that neutrinos have mass, which requires physics beyond the Standard Model. One well-motivated and well-studied solution is that right handed neutrinos exist and interact in a way that generates light neutrino masses. Moreover, if these new neutrinos are “Heavy”, there is potential for explaining why the Standard Model neutrinos are so much lighter than the charged leptons and quarks. I will summarize current searches for these heavy neutrinos across a wide range of masses and then focus on a particular regime of interest — GeV-scale Heavy Neutrinos. I will demonstrate how neutrino oscillation experiments can serve as a great environment to find these hypothetical particles in the coming decade. If we are lucky enough to discover these particles, then understanding them will become of paramount importance to the particle physics community. I will show strategies for exploring two specific characteristics of these heavy neutrinos by studying their decays: whether or not Lepton number is conserved (or whether they are Dirac or Majorana fermions), and what types of particle/particles mediate their interactions.
Host: Lars Aalsma
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Department Coffee Hour
Time: 3:30 pm
Place: https://cern.zoom.us/j/98625439661?pwd=NmNMeit4aGNLOSs3eHl0RHk0ZHRKUT09
Abstract: Join us weekly for an informal virtual coffee hour! Catch up with others in the department, tell us how things are going, and impress everyone with your Zoom background skills. Coffee Hour is open to any and all faculty, staff, and students in the department. Sometimes we have a topic, and we'll try to get that topic posted here in advance or sent out by email before each coffee hour.
Host: Department
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