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Search for Higgsinos in Compressed Mass Spectra Using Neural Networks in the Atlas Detector and Design Verification of the AMAC ASIC for the ITk Upgrade Sicong Lu
- Format:
- Book
- Thesis/Dissertation
- Author/Creator:
- Lu, Sicong, author.
- Language:
- English
- Subjects (All):
- Physics.
- Particle physics.
- High temperature physics.
- Computational physics.
- 0605.
- 0798.
- 0597.
- 0216.
- Local Subjects:
- Physics.
- Particle physics.
- High temperature physics.
- Computational physics.
- 0605.
- 0798.
- 0597.
- 0216.
- Physical Description:
- 1 electronic resource (375 pages)
- Contained In:
- Dissertations Abstracts International 86-07B
- Place of Publication:
- Ann Arbor : ProQuest Dissertations and Theses, 2024
- Language Note:
- English
- Summary:
- This dissertation presents two major projects undertaken during my PhD in the Penn ATLAS group, addressing challenges in high-energy physics analysis and detector development to advance our understanding of the universe.The first project focuses on the search for Higgsinos in compressed mass spectra, a promising scenario in Supersymmetry (SUSY) that addresses the hierarchy problem and provides a viable dark matter candidate. Nearly mass-degenerate Higgsinos with splittings of O(1 GeV) have been challenging to detect due to their elusive signals and overwhelming backgrounds. Using 140 fb−1 of proton-proton collision data at √ s = 13 TeV collected by the ATLAS detector, a novel analysis targeted events with a high-pT jet, significant missing transverse momentum, and a low-momentum displaced pion track. My work utilizes fully connected neural networks and an improved semi-data-driven background estimation method, achieving exclusions of Higgsino masses up to 190 GeV with splittings between 0.3 to 1.1 GeV, significantly extending sensitivity beyond the LEP limit of 95 GeV. The results show excellent agreement with Standard Model predictions, demonstrating the robustness of the analysis.The second project involves the design verification of an Application-Specific Integrated Circuit (ASIC), the Autonomous Monitoring and Control (AMAC) chip, developed for the Inner Tracker (ITk) in the ATLAS Upgrade for the High-Luminosity LHC (HL-LHC). My contributions include developing an automated analog-function testing framework, a workflow for chip characterization, identifying critical prototype design flaws, and a cocotb-based design simulation routine. Simulations and prototype testing confirmed the ASICs robustness against radiation-induced single-event effects (SEE) and compliance with specifications, enabling the transition to production. These efforts ensure the reliable operation of the ITk detector under HL-LHC conditions, supporting the pursuit of new physics discoveries.Collectively, these projects advanced experimental particle physics, providing tools for probing Beyond Standard Model theories, including SUSY, while laying the foundation for future discoveries at the HL-LHC.
- Notes:
- Source: Dissertations Abstracts International, Volume: 86-07, Section: B.
- Advisors: Kroll, I. Joseph Committee members: Thomson, Evelyn; Rankin, Dylan; Heckman, Jonathan; Mele, Eugene; Kroll, I. Joseph
- Ph.D. University of Pennsylvania 2024
- Local Notes:
- School code: 0175
- ISBN:
- 9798302185471
- Access Restriction:
- Restricted for use by site license
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