Bulletin of the American Physical Society
Joint Fall 2017 Meeting of the Texas Section of the APS, Texas Section of the AAPT, and Zone 13 of the Society of Physics Students
Volume 62, Number 16
Friday–Saturday, October 20–21, 2017; The University of Texas at Dallas, Richardson, Texas
Session K2: Particle III |
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Chair: Joe Izen, University of Texas at Dallas Room: DGAC 1.102B |
Saturday, October 21, 2017 10:30AM - 10:54AM |
K2.00001: The Higgs Boson's Most Favorite Thing Is Beautiful Invited Speaker: Stephen Sekula The Higgs Boson, the primogenitor of mass in the known fundamental particles, was discovered in 2012 and, so far, has been consistent with what was predicted in the standard model of particle of physics. Since that discovery, physicists at the two large multi-purpose experiments at the Large Hadron Collider, the ATLAS and CMS Collaborations, have been searching for what should be its most prominent feature: the conversion of its mass-energy into a pair of bottom quarks, the second-heaviest fundamental matter particle. In this talk, I will discuss the importance of studying the interaction of the Higgs Boson with the bottom quark, recent direct evidence for this existence of this process, and future directions this study may lead us toward a better understanding of fundamental interactions in nature. [Preview Abstract] |
Saturday, October 21, 2017 10:54AM - 11:06AM |
K2.00002: Muon Neutrino Disappearance Measurements at MINOS+ Will Flanagan From September 2013, the MINOS+ collaboration collected data from the Medium Energy NuMI neutrino beam at Fermilab. MINOS+ operated for three years, and improved upon the world-leading measurements of neutrino oscillations using muon neutrino disappearance made by the MINOS experiment, yielding precision measurements of the oscillation parameters $\sin^2\theta_{23}$ and $\Delta m^2_{32}$. This talk will present results from MINOS+ based on the first two years of data. An overview of the analysis, a comparison to previous MINOS results, and future sensitivities using the full MINOS+ dataset will be presented. [Preview Abstract] |
Saturday, October 21, 2017 11:06AM - 11:18AM |
K2.00003: Searching for 1$+$3 Sterile Neutrinos with IceCube Timothy Watson, Ben Jones Located at the South Pole, the IceCube neutrino observatory consists of a gigaton scale ice-Cherenkov neutrino detector instrumented with 5,160 digital optical modules providing sensitivity to neutrino events with energies ranging from the few GeV to several PeV scale. Within this range, IceCube's exceptional sensitivity to the matter-resonant depletion of the anti-muon neutrino flux in atmospheric neutrinos has led to the world-leading limits on the existence of sterile neutrinos consistent with the 3$+$1 model. Here I present the status of our latest sterile neutrino search applied to the 1$+$3 hypothesis with 1 year of IC86 data. [Preview Abstract] |
Saturday, October 21, 2017 11:18AM - 11:30AM |
K2.00004: The search for high mass WIMPs at SuperCDMS Soudan Robert Calkins A large portion of the mass in the universe remains unaccounted for and is hypothesized to exist in the form of dark matter, of which, one popular hypothesis is the Weakly Interacting Massive Particle (WIMP). We present the result of a blinded search, optimized for high mass WIMPs, using approximately 1700 kg days of SuperCDMS Soudan exposure. A single event in the signal region was observed after unblinding, which is consistent with background expectations. Since no excess of events was observed, we set an upper limit on the spin-independent WIMP-nucleon cross section for germanium of $1.4×10^{−44}$ cm$^2$ at 46 $\mathrm{GeV}/\mathrm{c}^2$. We combine the results of this search with the germanium result from CDMS-II and set a combined limit of $1.0 \times 10^{-44} \mathrm{cm}^2$ for a 46 $\mathrm{GeV}/\mathrm{c}^2$ WIMP. [Preview Abstract] |
Saturday, October 21, 2017 11:30AM - 11:42AM |
K2.00005: The LArIAT Experiment and Deep Learning Particle Classification Dalton Sessumes The Liquid Argon In A Testbeam (LArIAT) experiment is designed to characterize Hadron-Argon cross-sections, provide input for the calibration of Liquid Argon Time Projection Chambers (LArTPC), and contribute to detector R{\&}D using a LArTPC placed in a charged particle beamline at the Fermilab National Accelerator Laboratory's Test Beam Facility (FNAL FTBF). This talk will cover the installation, commissioning, and data acquisition of the most recent run of the LArIAT experiment, which took data at different wire pitches to explore the effects of the wire spacing on reconstruction performance, and it explores the possibility of using Deep Learning techniques as a primary identification method for particles detected in the LArTPC. The goal of this method is to upgrade the current classification efficiency and eliminate the need for human resources when sorting through detector data by introducing a new technique to intelligently and autonomously classify particles based on raw data from the LArTPC. [Preview Abstract] |
Saturday, October 21, 2017 11:42AM - 11:54AM |
K2.00006: Fast Data Readout with Microcontrollers For High Energy Physics. Akshat Tripathi One of the prominent ways of conducting neutrino experiments is using Liquid Argon Time Projection Chambers (LArTPCs). When charged particles interact with the liquid argon both ionization charge and scintillation light are produced, leaving a detailed trace of the type of charged particle and its trajectory. To detect both the charge and the light, many different detectors are employed which require making high speed analog measurements and converting them to a digital signal. In this presentation I will show work done to find an economical and scalable way of reading out these detectors using commercial microcontrollers and microprocessors (e.g. Raspberry Pi and Arduino). The successful use of these low-cost options have been demonstrated in the cryogenic liquid argon lab at the University of Texas at Arlington and offer the ability to decrease operation costs while maintaining our ability to store and analyze the data from various LArTPC detector components. [Preview Abstract] |
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