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Specialized minimal PDFs for optimized LHC calculations

We present a methodology for the construction of parton distribution functions (PDFs) designed to provide an accurate representation of PDF uncertainties for specific processes or classes of processes with a minimal number of PDF error sets: specialized minimal PDF sets, or SM-PDFs. We construct the...

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Autores principales: Carrazza, Stefano, Forte, Stefano, Kassabov, Zahari, Rojo, Juan
Lenguaje:eng
Publicado: 2016
Materias:
Acceso en línea:https://dx.doi.org/10.1140/epjc/s10052-016-4042-8
http://cds.cern.ch/record/2128277
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author Carrazza, Stefano
Forte, Stefano
Kassabov, Zahari
Rojo, Juan
author_facet Carrazza, Stefano
Forte, Stefano
Kassabov, Zahari
Rojo, Juan
author_sort Carrazza, Stefano
collection CERN
description We present a methodology for the construction of parton distribution functions (PDFs) designed to provide an accurate representation of PDF uncertainties for specific processes or classes of processes with a minimal number of PDF error sets: specialized minimal PDF sets, or SM-PDFs. We construct these SM-PDFs in such a way that sets corresponding to different input processes can be combined without losing information, specifically on their correlations, and that they are robust upon smooth variations of the kinematic cuts. The proposed strategy never discards information, so that the SM-PDF sets can be enlarged by the addition of new processes, until the prior PDF set is eventually recovered for a large enough set of processes. We illustrate the method by producing SM-PDFs tailored to Higgs, top quark pair, and electroweak gauge boson physics, and determine that, when the PDF4LHC15 combined set is used as the prior, around 11, 4 and 11 Hessian eigenvectors respectively are enough to fully describe the corresponding processes.
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institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2016
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spelling cern-21282772022-08-13T02:14:52Zdoi:10.1140/epjc/s10052-016-4042-8http://cds.cern.ch/record/2128277engCarrazza, StefanoForte, StefanoKassabov, ZahariRojo, JuanSpecialized minimal PDFs for optimized LHC calculationsParticle Physics - PhenomenologyWe present a methodology for the construction of parton distribution functions (PDFs) designed to provide an accurate representation of PDF uncertainties for specific processes or classes of processes with a minimal number of PDF error sets: specialized minimal PDF sets, or SM-PDFs. We construct these SM-PDFs in such a way that sets corresponding to different input processes can be combined without losing information, specifically on their correlations, and that they are robust upon smooth variations of the kinematic cuts. The proposed strategy never discards information, so that the SM-PDF sets can be enlarged by the addition of new processes, until the prior PDF set is eventually recovered for a large enough set of processes. We illustrate the method by producing SM-PDFs tailored to Higgs, top quark pair, and electroweak gauge boson physics, and determine that, when the PDF4LHC15 combined set is used as the prior, around 11, 4 and 11 Hessian eigenvectors respectively are enough to fully describe the corresponding processes.We present a methodology for the construction of parton distribution functions (PDFs) designed to provide an accurate representation of PDF uncertainties for specific processes or classes of processes with a minimal number of PDF error sets: specialized minimal PDF sets, or SM-PDFs. We construct these SM-PDFs in such a way that sets corresponding to different input processes can be combined without losing information, specifically as regards their correlations, and that they are robust upon smooth variations of the kinematic cuts. The proposed strategy never discards information, so that the SM-PDF sets can be enlarged by the addition of new processes, until the prior PDF set is eventually recovered for a large enough set of processes. We illustrate the method by producing SM-PDFs tailored to Higgs, top-quark pair, and electroweak gauge boson physics, and we determine that, when the PDF4LHC15 combined set is used as the prior, around 11, 4, and 11 Hessian eigenvectors, respectively, are enough to fully describe the corresponding processes.We present a methodology for the construction of parton distribution functions (PDFs) designed to provide an accurate representation of PDF uncertainties for specific processes or classes of processes with a minimal number of PDF error sets: specialized minimal PDF sets, or SM-PDFs. We construct these SM-PDFs in such a way that sets corresponding to different input processes can be combined without losing information, specifically on their correlations, and that they are robust upon smooth variations of the kinematic cuts. The proposed strategy never discards information, so that the SM-PDF sets can be enlarged by the addition of new processes, until the prior PDF set is eventually recovered for a large enough set of processes. We illustrate the method by producing SM-PDFs tailored to Higgs, top quark pair, and electroweak gauge boson physics, and determine that, when the PDF4LHC15 combined set is used as the prior, around 11, 4 and 11 Hessian eigenvectors respectively are enough to fully describe the corresponding processes.arXiv:1602.00005CERN-PH-TH-2015-243TIF-UNIMI-2015-13OUTP-15-24PCERN-PH-TH-2015-243TIF-UNIMI-2015-13OUTP-15-24Poai:cds.cern.ch:21282772016-01-29
spellingShingle Particle Physics - Phenomenology
Carrazza, Stefano
Forte, Stefano
Kassabov, Zahari
Rojo, Juan
Specialized minimal PDFs for optimized LHC calculations
title Specialized minimal PDFs for optimized LHC calculations
title_full Specialized minimal PDFs for optimized LHC calculations
title_fullStr Specialized minimal PDFs for optimized LHC calculations
title_full_unstemmed Specialized minimal PDFs for optimized LHC calculations
title_short Specialized minimal PDFs for optimized LHC calculations
title_sort specialized minimal pdfs for optimized lhc calculations
topic Particle Physics - Phenomenology
url https://dx.doi.org/10.1140/epjc/s10052-016-4042-8
http://cds.cern.ch/record/2128277
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