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A standard convention for particle-level Monte Carlo event-variation weights

Streams of event weights in particle-level Monte Carlo event generators are a convenient and immensely CPU-efficient approach to express systematic uncertainties in phenomenology calculations, providing systematic variations on the nominal prediction within a single event sample. But the lack of a c...

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Autores principales: Bothmann, Enrico, Buckley, Andy, Gütschow, Christian, Prestel, Stefan, Schönherr, Marek, Skands, Peter, Andersen, Jeppe R., Bhattacharya, Saptaparna, Butterworth, Jonathan Mark, Chahal, Gurpreet Singh, Corpe, Louie, Gellersen, Leif, Gignac, Matthew, Höche, Stefan, Kar, Deepak, Krauss, Frank, Kretzschmar, Jan, Lönnblad, Leif, McFayden, Josh, Papaefstathiou, Andreas, Plätzer, Simon, Schumann, Steffen, Seymour, Michael H., Siegert, Frank, Siódmok, Andrzej
Lenguaje:eng
Publicado: 2022
Materias:
Acceso en línea:https://dx.doi.org/10.21468/SciPostPhysCore.6.1.007
http://cds.cern.ch/record/2813958
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author Bothmann, Enrico
Buckley, Andy
Gütschow, Christian
Prestel, Stefan
Schönherr, Marek
Skands, Peter
Andersen, Jeppe R.
Bhattacharya, Saptaparna
Butterworth, Jonathan Mark
Chahal, Gurpreet Singh
Corpe, Louie
Gellersen, Leif
Gignac, Matthew
Höche, Stefan
Kar, Deepak
Krauss, Frank
Kretzschmar, Jan
Lönnblad, Leif
McFayden, Josh
Papaefstathiou, Andreas
Plätzer, Simon
Schumann, Steffen
Seymour, Michael H.
Siegert, Frank
Siódmok, Andrzej
author_facet Bothmann, Enrico
Buckley, Andy
Gütschow, Christian
Prestel, Stefan
Schönherr, Marek
Skands, Peter
Andersen, Jeppe R.
Bhattacharya, Saptaparna
Butterworth, Jonathan Mark
Chahal, Gurpreet Singh
Corpe, Louie
Gellersen, Leif
Gignac, Matthew
Höche, Stefan
Kar, Deepak
Krauss, Frank
Kretzschmar, Jan
Lönnblad, Leif
McFayden, Josh
Papaefstathiou, Andreas
Plätzer, Simon
Schumann, Steffen
Seymour, Michael H.
Siegert, Frank
Siódmok, Andrzej
author_sort Bothmann, Enrico
collection CERN
description Streams of event weights in particle-level Monte Carlo event generators are a convenient and immensely CPU-efficient approach to express systematic uncertainties in phenomenology calculations, providing systematic variations on the nominal prediction within a single event sample. But the lack of a common standard for labelling these variation streams across different tools has proven to be a major limitation for event-processing tools and analysers alike. Here we propose a well-defined, extensible community standard for the naming, ordering, and interpretation of weight streams that will serve as the basis for semantically correct parsing and combination of such variations in both theoretical and experimental studies.
id cern-2813958
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2022
record_format invenio
spelling cern-28139582023-08-24T02:43:47Zdoi:10.21468/SciPostPhysCore.6.1.007http://cds.cern.ch/record/2813958engBothmann, EnricoBuckley, AndyGütschow, ChristianPrestel, StefanSchönherr, MarekSkands, PeterAndersen, Jeppe R.Bhattacharya, SaptaparnaButterworth, Jonathan MarkChahal, Gurpreet SinghCorpe, LouieGellersen, LeifGignac, MatthewHöche, StefanKar, DeepakKrauss, FrankKretzschmar, JanLönnblad, LeifMcFayden, JoshPapaefstathiou, AndreasPlätzer, SimonSchumann, SteffenSeymour, Michael H.Siegert, FrankSiódmok, AndrzejA standard convention for particle-level Monte Carlo event-variation weightshep-phParticle Physics - PhenomenologyStreams of event weights in particle-level Monte Carlo event generators are a convenient and immensely CPU-efficient approach to express systematic uncertainties in phenomenology calculations, providing systematic variations on the nominal prediction within a single event sample. But the lack of a common standard for labelling these variation streams across different tools has proven to be a major limitation for event-processing tools and analysers alike. Here we propose a well-defined, extensible community standard for the naming, ordering, and interpretation of weight streams that will serve as the basis for semantically correct parsing and combination of such variations in both theoretical and experimental studies.Streams of event weights in particle-level Monte Carlo event generators are a convenient and immensely CPU-efficient approach to express systematic uncertainties in phenomenology calculations, providing systematic variations on the nominal prediction within a single event sample. But the lack of a common standard for labelling these variation streams across different tools has proven to be a major limitation for event-processing tools and analysers alike. Here we propose a well-defined, extensible community standard for the naming, ordering, and interpretation of weight streams that will serve as the basis for semantically correct parsing and combination of such variations in both theoretical and experimental studies.arXiv:2203.08230MCNET-22-03MCNET-22-00FERMILAB-PUB-22-945-Toai:cds.cern.ch:28139582022-03-15
spellingShingle hep-ph
Particle Physics - Phenomenology
Bothmann, Enrico
Buckley, Andy
Gütschow, Christian
Prestel, Stefan
Schönherr, Marek
Skands, Peter
Andersen, Jeppe R.
Bhattacharya, Saptaparna
Butterworth, Jonathan Mark
Chahal, Gurpreet Singh
Corpe, Louie
Gellersen, Leif
Gignac, Matthew
Höche, Stefan
Kar, Deepak
Krauss, Frank
Kretzschmar, Jan
Lönnblad, Leif
McFayden, Josh
Papaefstathiou, Andreas
Plätzer, Simon
Schumann, Steffen
Seymour, Michael H.
Siegert, Frank
Siódmok, Andrzej
A standard convention for particle-level Monte Carlo event-variation weights
title A standard convention for particle-level Monte Carlo event-variation weights
title_full A standard convention for particle-level Monte Carlo event-variation weights
title_fullStr A standard convention for particle-level Monte Carlo event-variation weights
title_full_unstemmed A standard convention for particle-level Monte Carlo event-variation weights
title_short A standard convention for particle-level Monte Carlo event-variation weights
title_sort standard convention for particle-level monte carlo event-variation weights
topic hep-ph
Particle Physics - Phenomenology
url https://dx.doi.org/10.21468/SciPostPhysCore.6.1.007
http://cds.cern.ch/record/2813958
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