Bulletin of the American Physical Society
APS April Meeting 2023
Volume 68, Number 6
Minneapolis, Minnesota (Apr 15-18)
Virtual (Apr 24-26); Time Zone: Central Time
Session B16: Undergraduate Research IUndergrad Friendly
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Sponsoring Units: APS SPS Chair: Alexis Knaub, American Association of Physics Teachers Room: Marquette VII - 2nd Floor |
Saturday, April 15, 2023 10:45AM - 10:57AM |
B16.00001: Computation of dark matter-nucleus scattering rates in direct detection experiments Stanislaw Rakowski, Michal Zdziennicki, Jakub Trzaska Dark matter is one of the main topics of intensive worldwide research in cosmology and particle physics. The concept of dark matter is strongly indicated by vast astronomical and cosmological data. In this talk, we present how to compute the event rate in direct detection experiments for a given microscopic model. Empirically given constraints on impact velocities of interacting particles and their masses indicate that dark matter particles do not have enough energy to brake the nuclei bonds. It is then reasonable to take into account only DM-nuclei interactions. Scattering rates between DM and nuclei were studied by Cirelli, Del Nobile, and Panci (2013) for contact and long-range interactions. We extend the study of Cirelli et al. to interactions mediated by intermediate-mass particle. By applying effective non-relativistic scattering operators, we explore the mediator-mass dependence of scattering rates. This talk provides a framework for understanding the ways in which dark matter interacts with standard model particles, and offers insight for further study of these interactions. |
Saturday, April 15, 2023 10:57AM - 11:09AM |
B16.00002: Development of a Cable Checkout Board for the SuperCDMS Experiment Oleksandra Lukina, Ruslan Podviianiuk Dark matter is an invisible form of matter that is inferred from its gravitational effects on visible objects to account for 85% of the matter in the universe. One of the leading hypotheses of the nature of dark matter is that it is composed of weakly interacting massive particles (WIMPs). The Super Cryogenic Dark Matter Search (SuperCDMS) experiment is designed to search for WIMPs that elastically scatter off of nuclei. We present the results of a research and development project to check SuperCDMS readout cables for possible defects before deployment. |
Saturday, April 15, 2023 11:09AM - 11:21AM |
B16.00003: Measuring the Radial Component of the Magnetic Field in the Muon g-2 Experiment Fatima A Rodriguez A leading systematic error in the muon electric dipole moment (EDM) analysis at the Muon g-2 Experiment is the presence of radial magnetic fields because they cause indistinguishable effects to the muon spin precession plane from a true EDM measurement. Measuring a non-zero muon EDM would be evidence of CP-violation, indicating new physics beyond the Standard Model. The radial field occurs due to imperfections in the materials and alignment of magnetic elements, and is mostly offset by an applied radial field generated by surface correction coils (SCC). We determine an optimal SCC setting that best minimizes the background radial field by performing a scan at different electro-static quadrupole settings and studying the relationship between the vertical beam position and applied radial field. In this talk I will present our results and describe our efforts to design an apparatus outfitted with Hall probes and tilt sensors to directly measure the radial magnetic field as a function of azimuth. |
Saturday, April 15, 2023 11:21AM - 11:33AM |
B16.00004: Using RECAST to set an upper limit on the BSM Higgs decay channel H→ll+MET with the ATLAS experiment Enzo D Brandani, Tae M Hong, Benjamin T Carlson Beyond the Standard Model (BSM) Higgs with a same-flavor, opposite-charge dilepton plus Missing Transverse Energy (MET) final state are predicted by many models, including extensions of supersymmetry with an additional scalar. Such models are motivated by phenomenological issues with the Standard Model, such as the hierarchy problem, and by astrophysical observations such as the excess of gamma-ray radiation in the Milky Way galactic center. Conveniently, the proposed signal decay partially overlaps with that of the signal region of a published ATLAS search for gauginos in a compressed-mass scenario at the LHC, allowing us to take advantage of the analysis preservation and reinterpretation framework (RECAST) to investigate constraining the production of this additional scalar. |
Saturday, April 15, 2023 11:33AM - 11:45AM |
B16.00005: Searching for Extreme Events in Multi-lepton Data from the LHC Xinyue Wu The Standard Model particles cannot represent the complete set of nature's constituents, but there's no guarantee that new particles to be discovered would be light enough to be produced on-shell at the LHC. Thus, indirect methods of probing higher mass scales become increasingly interesting in the search for new physics at the energy frontier. Effective Field Theory (EFT) is an example of such an indirect probe, which offers a model-independent method of extending the discovery reach of the LHC. As part of the EFT analyses, data from the CMS detector is explored. The full Run 2 data is preselected to be top production events with multiple leptons in their final states. The multi-lepton data are then classified in dataframe according to several characteristics (e.g. jet multiplicity). Top high-energy events in each class were searched. The observed data were compared with the simulation data of the EFT model qualitatively. A processor is written under the Coffea framework to run large quantities of data at scale using distributed batch system HTCondor with several hundreds of cores concurrently. A bottleneck of the computation performance is identified as the data transfer of input files (XRootD servers). |
Saturday, April 15, 2023 11:45AM - 11:57AM |
B16.00006: Search for single vector-like B -> tW decays in a single-lepton final state Kyle M Howey, Julie Hogan We present a search for a single vector-like B quark that decays to a top quark and W boson. In the single lepton final state, the B quark can be reconstructed from the lepton, missing transverse momentum, and one large-radius jet. The deep network algorithm called ParticleNet is used to identify the parent particle of the large-radius jet and provides an important boost in sensitivity with respect to prior searches. Several neural network architectures have been studied to improve discrimination between signal and background. The search strategy and current status will be presented. |
Saturday, April 15, 2023 11:57AM - 12:09PM |
B16.00007: Particle Discovery Lab: CMS Open Data in undergraduate physics courses Kalin Johnson, Julie Hogan High energy physics data analysis can provide a valuable learning experience in undergraduate physics courses. We present a "Particle Discovery Lab", in which students learn to analyze and interpret data as they discover a fundamental particle. The exercise is primarily targeted for intermediate-level modern physics courses, but now also includes a "Higgs Boson expansion". CMS Run 1 data from the CERN Open Data Portal was analyzed using cloud computing tools to produce a 4-lepton dataset in which students can rediscover the Higgs boson. This option is available for the intermediate-level lab exercise, and a more comprehensive analysis exercise has been developed for upper-level experimental courses. The Particle Discovery Lab, including the Higgs Boson expansion, is accessible to instructors via the Open Data Portal. |
Saturday, April 15, 2023 12:09PM - 12:21PM |
B16.00008: Refining MC-based Jet Energy Scale Calibrations with Machine Learning at the ATLAS Experiment Garrett S Linney Hadronic jets are important for many measurements and searches for new physics at the LHC. Current procedures for calibrating the energy of hadronic jets for the ATLAS Experiment require multiple, time-intensive stages and are restricted in the number of parameters that can be considered. This talk presents results on a mixture density neural network-based approach using Monte Carlo simulations of QCD processes, allowing studies into an expanded parameter space and consideration of correlations between parameters. The machine learning approach is expected to be able to combine several steps in the calibration and to improve the robustness of the calibration to pile-up from additional proton-proton collisions. |
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