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Solving constrained Markovian evolution in QCD with the help of the non-Markovian Monte Carlo

We present the constrained Monte Carlo (CMC) algorithm for the QCD evolution. The constraint resides in that the total longitudinal energy of the emissions in the MC and in the underlying QCD evolution is predefined (constrained). This CMC implements exactly the full DGLAP evolution of the parton di...

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Autores principales: Jadach, S., Skrzypek, M.
Lenguaje:eng
Publicado: 2005
Materias:
Acceso en línea:https://dx.doi.org/10.1016/j.cpc.2006.06.004
http://cds.cern.ch/record/834184
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author Jadach, S.
Skrzypek, M.
author_facet Jadach, S.
Skrzypek, M.
author_sort Jadach, S.
collection CERN
description We present the constrained Monte Carlo (CMC) algorithm for the QCD evolution. The constraint resides in that the total longitudinal energy of the emissions in the MC and in the underlying QCD evolution is predefined (constrained). This CMC implements exactly the full DGLAP evolution of the parton distributions in the hadron with respect to the logarithm of the energy scale. The algorithm of the CMC is referred to as the non-Markovian type. The non-Markovian MC algorithm is defined as the one in which the multiplicity of emissions is chosen randomly as the first variable and not the last one, as in the Markovian MC algorithms. The former case resembles that of the fixed-order matrix element calculations. The CMC algorithm can serve as an alternative to the so-called backward evolution Markovian algorithm of Sjostrand, which is used for modelling the initial-state parton shower in modern QCD MC event generators. We test practical feasibility and efficiency of our CMC implementation in a series of numerical exercises, comparing its results with those from other MC and non-MC programs, in a wide range of Q and x, down to the 0.1% precision level. In particular, satisfactory numerical agreement is found with the results of the Markovian MC program of our own and the other non-MC program. The efficiency of the new constrained MC is found to be quite good.
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spelling cern-8341842023-10-04T06:05:48Zdoi:10.1016/j.cpc.2006.06.004http://cds.cern.ch/record/834184engJadach, S.Skrzypek, M.Solving constrained Markovian evolution in QCD with the help of the non-Markovian Monte CarloParticle Physics - PhenomenologyWe present the constrained Monte Carlo (CMC) algorithm for the QCD evolution. The constraint resides in that the total longitudinal energy of the emissions in the MC and in the underlying QCD evolution is predefined (constrained). This CMC implements exactly the full DGLAP evolution of the parton distributions in the hadron with respect to the logarithm of the energy scale. The algorithm of the CMC is referred to as the non-Markovian type. The non-Markovian MC algorithm is defined as the one in which the multiplicity of emissions is chosen randomly as the first variable and not the last one, as in the Markovian MC algorithms. The former case resembles that of the fixed-order matrix element calculations. The CMC algorithm can serve as an alternative to the so-called backward evolution Markovian algorithm of Sjostrand, which is used for modelling the initial-state parton shower in modern QCD MC event generators. We test practical feasibility and efficiency of our CMC implementation in a series of numerical exercises, comparing its results with those from other MC and non-MC programs, in a wide range of Q and x, down to the 0.1% precision level. In particular, satisfactory numerical agreement is found with the results of the Markovian MC program of our own and the other non-MC program. The efficiency of the new constrained MC is found to be quite good.We present the constrained Monte Carlo (CMC) algorithm for the QCD evolution. The constraint resides in that the total longitudinal energy of the emissions in the MC and in the underlying QCD evolution is predefined (constrained). This CMC implements exactly the full DGLAP evolution of the parton distributions in the hadron with respect to the logarithm of the energy scale. The algorithm of the CMC is referred to as the non-Markovian type. The non-Markovian MC algorithm is defined as the one in which the multiplicity of emissions is chosen randomly as the first variable and not the last one, as in the Markovian MC algorithms. The former case resembles that of the fixed-order matrix element calculations. The CMC algorithm can serve as an alternative to the so-called backward evolution Markovian algorithm of Sjostrand, which is used for modelling the initial-state parton shower in modern QCD MC event generators. We test practical feasibility and efficiency of our CMC implementation in a series of numerical exercises, comparing its results with those from other MC and non-MC programs, in a wide range of Q and x, down to the 0.1% precision level. In particular, satisfactory numerical agreement is found with the results of the Markovian MC program of our own and the other non-MC program. The efficiency of the new constrained MC is found to be quite good.hep-ph/0504263IFJPAN-V-04-07CERN-PH-TH-2005-066CERN-PH-TH-2005-066IFJPAN-V-2004-07oai:cds.cern.ch:8341842005-04-27
spellingShingle Particle Physics - Phenomenology
Jadach, S.
Skrzypek, M.
Solving constrained Markovian evolution in QCD with the help of the non-Markovian Monte Carlo
title Solving constrained Markovian evolution in QCD with the help of the non-Markovian Monte Carlo
title_full Solving constrained Markovian evolution in QCD with the help of the non-Markovian Monte Carlo
title_fullStr Solving constrained Markovian evolution in QCD with the help of the non-Markovian Monte Carlo
title_full_unstemmed Solving constrained Markovian evolution in QCD with the help of the non-Markovian Monte Carlo
title_short Solving constrained Markovian evolution in QCD with the help of the non-Markovian Monte Carlo
title_sort solving constrained markovian evolution in qcd with the help of the non-markovian monte carlo
topic Particle Physics - Phenomenology
url https://dx.doi.org/10.1016/j.cpc.2006.06.004
http://cds.cern.ch/record/834184
work_keys_str_mv AT jadachs solvingconstrainedmarkovianevolutioninqcdwiththehelpofthenonmarkovianmontecarlo
AT skrzypekm solvingconstrainedmarkovianevolutioninqcdwiththehelpofthenonmarkovianmontecarlo