A search for non-resonant HH -> bbbb at sqrt(s) = 13 TeV with the ATLAS detector -or- 2b, and then another 2b ... now that's the thesis question
Abstract/Contents
- Abstract
- The Standard Model (SM) characterizes the fundamental building blocks of nature, with its experimental characterization culminating with the discovery of the Higgs boson a decade ago. While subsequent Higgs measurements have thus far confirmed the SM predictions, a critical test for our understanding of electroweak symmetry breaking is to study the shape of the Higgs potential by measuring the Higgs self-coupling — which can be probed by searching for events with two Higgs bosons (HH). This thesis presents a search for HH production with each Higgs subsequently decaying into two b-quarks. The extremely small predicted HH signal, coupled with a complex background that cannot be effectively simulated, makes this analysis an ideal test bed for machine learning applications. This thesis also presents the developments in novel algorithms for b-quark jet identification and background estimation that build on recent advancements in machine learning (including deep sets, neural reweighting methods, and normalizing flows) that have been crucial to the HH analysis. The HH -> 4b analysis sets an observed (expected) upper limit on the HH SM cross-section of 5.4 (8.1), a 30% improvement on the previous analysis strategy. We additionally constrain the Higgs self-coupling in the kappa framework with observed (expected) limits of [-3.9, 11.1] ( [-4.6, 10.8] ).
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2022; ©2022 |
| Publication date | 2022; 2022 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Hartman, Nicole Michelle |
|---|---|
| Degree supervisor | Su, Dong, (Computer scientist) |
| Thesis advisor | Su, Dong, (Computer scientist) |
| Thesis advisor | Burchat, P. (Patricia) |
| Thesis advisor | Kagan, Michael |
| Thesis advisor | Peskin, Michael Edward, 1951- |
| Degree committee member | Burchat, P. (Patricia) |
| Degree committee member | Kagan, Michael |
| Degree committee member | Peskin, Michael Edward, 1951- |
| Associated with | Stanford University, Department of Physics |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Nicole Hartman. |
|---|---|
| Note | Submitted to the Department of Physics. |
| Thesis | Thesis Ph.D. Stanford University 2022. |
| Location | https://purl.stanford.edu/dd512hg5884 |
Access conditions
- Copyright
- © 2022 by Nicole Michelle Hartman
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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