Topic model for four-top at the LHC

Autores
Alvarez, Ezequiel; Lamagna, Federico Agustín; Szewc, Manuel
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
We study the implementation of a Topic Model algorithm in four-top searches at the LHC as a test-probe of a not ideal system for applying this technique. We study this Topic Model behavior as its different hypotheses such as mutual reducibility and equal distribution in all samples shift from true. The four-top final state at the LHC is not only relevant because it does not fulfill these conditions, but also because it is a difficult and inefficient system to reconstruct and current Monte Carlo modeling of signal and backgrounds suffers from non-negligible uncertainties. We implement this Topic Model algorithm in the Same-Sign lepton channel where S/B is of order one and all backgrounds cannot have more than two b-jets at parton level. We define different mixtures according to the number of b- jets and we use the total number of jets to demix. Since only the background has an anchor bin, we find that we can reconstruct the background in the signal region independently of Monte Carlo. We propose to use this information to tune the Monte Carlo in the signal region and then compare signal prediction with data. We also explore Machine Learning techniques applied to this Topic Model algorithm and find slight improvements as well as potential roads to investigate. Although our findings indicate that still with the full LHC run 3 data the implementation would be challenging, we pursue through this work to find ways to reduce the impact of Monte Carlo simulations in four-top searches at the LHC.
Fil: Alvarez, Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología. Centro Internacional de Estudios Avanzados; Argentina
Fil: Lamagna, Federico Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comisión Nacional de Energía Atómica. Gerencia del Área de Energía Nuclear. Instituto Balseiro; Argentina. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología. Centro Internacional de Estudios Avanzados; Argentina. Comisión Nacional de Energía Atómica. Centro Atómico Bariloche; Argentina
Fil: Szewc, Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología. Centro Internacional de Estudios Avanzados; Argentina
Materia
FOUR-TOP-PRODUCTION
HADRON-HADRON SCATTERING (EXPERIMENTS)
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/168321
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Topic model for four-top at the LHCAlvarez, EzequielLamagna, Federico AgustínSzewc, ManuelFOUR-TOP-PRODUCTIONHADRON-HADRON SCATTERING (EXPERIMENTS)https://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1We study the implementation of a Topic Model algorithm in four-top searches at the LHC as a test-probe of a not ideal system for applying this technique. We study this Topic Model behavior as its different hypotheses such as mutual reducibility and equal distribution in all samples shift from true. The four-top final state at the LHC is not only relevant because it does not fulfill these conditions, but also because it is a difficult and inefficient system to reconstruct and current Monte Carlo modeling of signal and backgrounds suffers from non-negligible uncertainties. We implement this Topic Model algorithm in the Same-Sign lepton channel where S/B is of order one and all backgrounds cannot have more than two b-jets at parton level. We define different mixtures according to the number of b- jets and we use the total number of jets to demix. Since only the background has an anchor bin, we find that we can reconstruct the background in the signal region independently of Monte Carlo. We propose to use this information to tune the Monte Carlo in the signal region and then compare signal prediction with data. We also explore Machine Learning techniques applied to this Topic Model algorithm and find slight improvements as well as potential roads to investigate. Although our findings indicate that still with the full LHC run 3 data the implementation would be challenging, we pursue through this work to find ways to reduce the impact of Monte Carlo simulations in four-top searches at the LHC.Fil: Alvarez, Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología. Centro Internacional de Estudios Avanzados; ArgentinaFil: Lamagna, Federico Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comisión Nacional de Energía Atómica. Gerencia del Área de Energía Nuclear. Instituto Balseiro; Argentina. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología. Centro Internacional de Estudios Avanzados; Argentina. Comisión Nacional de Energía Atómica. Centro Atómico Bariloche; ArgentinaFil: Szewc, Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología. Centro Internacional de Estudios Avanzados; ArgentinaSpringer2020-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/168321Alvarez, Ezequiel; Lamagna, Federico Agustín; Szewc, Manuel; Topic model for four-top at the LHC; Springer; Journal of High Energy Physics; 49; 1-2020; 1-241029-84791126-6708CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1007/JHEP01(2020)049info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007/JHEP01(2020)049info:eu-repo/semantics/altIdentifier/arxiv/https://arxiv.org/abs/1911.09699info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:35:16Zoai:ri.conicet.gov.ar:11336/168321instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:35:16.559CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Topic model for four-top at the LHC
title Topic model for four-top at the LHC
spellingShingle Topic model for four-top at the LHC
Alvarez, Ezequiel
FOUR-TOP-PRODUCTION
HADRON-HADRON SCATTERING (EXPERIMENTS)
title_short Topic model for four-top at the LHC
title_full Topic model for four-top at the LHC
title_fullStr Topic model for four-top at the LHC
title_full_unstemmed Topic model for four-top at the LHC
title_sort Topic model for four-top at the LHC
dc.creator.none.fl_str_mv Alvarez, Ezequiel
Lamagna, Federico Agustín
Szewc, Manuel
author Alvarez, Ezequiel
author_facet Alvarez, Ezequiel
Lamagna, Federico Agustín
Szewc, Manuel
author_role author
author2 Lamagna, Federico Agustín
Szewc, Manuel
author2_role author
author
dc.subject.none.fl_str_mv FOUR-TOP-PRODUCTION
HADRON-HADRON SCATTERING (EXPERIMENTS)
topic FOUR-TOP-PRODUCTION
HADRON-HADRON SCATTERING (EXPERIMENTS)
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv We study the implementation of a Topic Model algorithm in four-top searches at the LHC as a test-probe of a not ideal system for applying this technique. We study this Topic Model behavior as its different hypotheses such as mutual reducibility and equal distribution in all samples shift from true. The four-top final state at the LHC is not only relevant because it does not fulfill these conditions, but also because it is a difficult and inefficient system to reconstruct and current Monte Carlo modeling of signal and backgrounds suffers from non-negligible uncertainties. We implement this Topic Model algorithm in the Same-Sign lepton channel where S/B is of order one and all backgrounds cannot have more than two b-jets at parton level. We define different mixtures according to the number of b- jets and we use the total number of jets to demix. Since only the background has an anchor bin, we find that we can reconstruct the background in the signal region independently of Monte Carlo. We propose to use this information to tune the Monte Carlo in the signal region and then compare signal prediction with data. We also explore Machine Learning techniques applied to this Topic Model algorithm and find slight improvements as well as potential roads to investigate. Although our findings indicate that still with the full LHC run 3 data the implementation would be challenging, we pursue through this work to find ways to reduce the impact of Monte Carlo simulations in four-top searches at the LHC.
Fil: Alvarez, Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología. Centro Internacional de Estudios Avanzados; Argentina
Fil: Lamagna, Federico Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comisión Nacional de Energía Atómica. Gerencia del Área de Energía Nuclear. Instituto Balseiro; Argentina. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología. Centro Internacional de Estudios Avanzados; Argentina. Comisión Nacional de Energía Atómica. Centro Atómico Bariloche; Argentina
Fil: Szewc, Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología. Centro Internacional de Estudios Avanzados; Argentina
description We study the implementation of a Topic Model algorithm in four-top searches at the LHC as a test-probe of a not ideal system for applying this technique. We study this Topic Model behavior as its different hypotheses such as mutual reducibility and equal distribution in all samples shift from true. The four-top final state at the LHC is not only relevant because it does not fulfill these conditions, but also because it is a difficult and inefficient system to reconstruct and current Monte Carlo modeling of signal and backgrounds suffers from non-negligible uncertainties. We implement this Topic Model algorithm in the Same-Sign lepton channel where S/B is of order one and all backgrounds cannot have more than two b-jets at parton level. We define different mixtures according to the number of b- jets and we use the total number of jets to demix. Since only the background has an anchor bin, we find that we can reconstruct the background in the signal region independently of Monte Carlo. We propose to use this information to tune the Monte Carlo in the signal region and then compare signal prediction with data. We also explore Machine Learning techniques applied to this Topic Model algorithm and find slight improvements as well as potential roads to investigate. Although our findings indicate that still with the full LHC run 3 data the implementation would be challenging, we pursue through this work to find ways to reduce the impact of Monte Carlo simulations in four-top searches at the LHC.
publishDate 2020
dc.date.none.fl_str_mv 2020-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/168321
Alvarez, Ezequiel; Lamagna, Federico Agustín; Szewc, Manuel; Topic model for four-top at the LHC; Springer; Journal of High Energy Physics; 49; 1-2020; 1-24
1029-8479
1126-6708
CONICET Digital
CONICET
url http://hdl.handle.net/11336/168321
identifier_str_mv Alvarez, Ezequiel; Lamagna, Federico Agustín; Szewc, Manuel; Topic model for four-top at the LHC; Springer; Journal of High Energy Physics; 49; 1-2020; 1-24
1029-8479
1126-6708
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1007/JHEP01(2020)049
info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007/JHEP01(2020)049
info:eu-repo/semantics/altIdentifier/arxiv/https://arxiv.org/abs/1911.09699
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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