Evaluating Modifications to Classifiers for Identification of Higgs Bosons

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Hauptverfasser: Nelakurti, Rishivarshil, Hill, Christopher
Format: Preprint
Veröffentlicht: 2024
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author Nelakurti, Rishivarshil
Hill, Christopher
author_facet Nelakurti, Rishivarshil
Hill, Christopher
contents The Higgs boson, discovered back in 2012 through collision data at the Large Hadron Collider (LHC) by ATLAS and CMS experiments, marked a significant inflection point in High Energy Physics (HEP). Today, it's crucial to precisely measure Higgs production processes with LHC experiments in order to gain insights into the universe and find any invisible physics. To analyze the vast data that LHC experiments generate, classical machine learning has become an invaluable tool. However, classical classifiers often struggle with detecting higgs production processes, leading to incorrect labeling of Higgs Bosons. This paper aims to tackle this classification problem by investigating the use of quantum machine learning (QML).
format Preprint
id arxiv_https___arxiv_org_abs_2409_10902
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Evaluating Modifications to Classifiers for Identification of Higgs Bosons
Nelakurti, Rishivarshil
Hill, Christopher
High Energy Physics - Experiment
High Energy Physics - Phenomenology
Quantum Physics
The Higgs boson, discovered back in 2012 through collision data at the Large Hadron Collider (LHC) by ATLAS and CMS experiments, marked a significant inflection point in High Energy Physics (HEP). Today, it's crucial to precisely measure Higgs production processes with LHC experiments in order to gain insights into the universe and find any invisible physics. To analyze the vast data that LHC experiments generate, classical machine learning has become an invaluable tool. However, classical classifiers often struggle with detecting higgs production processes, leading to incorrect labeling of Higgs Bosons. This paper aims to tackle this classification problem by investigating the use of quantum machine learning (QML).
title Evaluating Modifications to Classifiers for Identification of Higgs Bosons
topic High Energy Physics - Experiment
High Energy Physics - Phenomenology
Quantum Physics
url https://arxiv.org/abs/2409.10902