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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...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , |
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Lenguaje: | eng |
Publicado: |
2022
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.21468/SciPostPhysCore.6.1.007 http://cds.cern.ch/record/2813958 |
_version_ | 1780973427304169472 |
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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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