{"id":{"repo_id":"baylor","oai_identifier":"oai:baylor-ir.tdl.org:2104/14090"},"canonical_url":"https://search.dev.ndltd.org/etd/baylor/oai:baylor-ir.tdl.org:2104/14090","repository":{"repo_id":"baylor","name":"Baylor University","base_url":"https://baylor-ir.tdl.org/server/oai/request"},"display":{"title":"Search for boosted Higgs boson decays to a pair of spin-0 particle in the 4b final state.","abstract":"This dissertation presents a new technique in calibration, efficiency estimation, and uncertainty calculation of 4-body AK8 jet taggers, as well as the training and assessment of ParticleNet mass decorrelated regressors, then outlines their usage in the search for boosted Higgs boson decays to a pair of spin-0 particles in the b¯bb¯b final state using CMS Run 2 data. The spin-0 particle mass examined in this analysis ranged from 11 –62.5 GeV. The Higgs production mode considered was gluon-gluon fusion. Both the calibration and analysis is performed on data from proton-proton collisions at the center of mass energy of 13TeV, collected in 2016-2018, corresponding to an integrated luminosity of 138 f b−1. Lastly, the dissertation also describes the study on using statistical tests and machine learning techniques in anomaly detection for the Compact Muon Solenoid Data Quality Monitoring.","abstract_html":"This dissertation presents a new technique in calibration, efficiency estimation, and uncertainty calculation of 4-body AK8 jet taggers, as well as the training and assessment of ParticleNet mass decorrelated regressors, then outlines their usage in the search for boosted Higgs boson decays to a pair of spin-0 particles in the b¯bb¯b final state using CMS Run 2 data. The spin-0 particle mass examined in this analysis ranged from 11 –62.5 GeV. The Higgs production mode considered was gluon-gluon fusion. Both the calibration and analysis is performed on data from proton-proton collisions at the center of mass energy of 13TeV, collected in 2016-2018, corresponding to an integrated luminosity of 138 f b−1. Lastly, the dissertation also describes the study on using statistical tests and machine learning techniques in anomaly detection for the Compact Muon Solenoid Data Quality Monitoring.","abstract_has_math":false,"creators":["Sutantawibul, Chosila, 1996-"],"institution":"Baylor University.","degree_name":"Ph.D.","degree_level":"Doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Brinkerhoff, Andrew."],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-12","date_published":"2025-12","updated_at":"2026-07-24T01:08:13Z","subjects":["Machine learning.","High energy physics.","Tagger calibration."],"languages":["en"],"rights":["Baylor University works are protected by copyright. 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