TY - JOUR
T1 - A standard convention for particle-level Monte Carlo event-variation weights
AU - Andersen, Jeppe R.
AU - Bhattacharya, Saptaparna
AU - Butterworth, Jonathan
AU - Chahal, Gurpreet Singh
AU - Corpe, Louie
AU - Gellersen, Leif
AU - Gignac, Matthew
AU - Höche, Stefan
AU - Kar, Deepak
AU - Krauss, Frank
AU - Kretzschmar, Jan
AU - Lönnblad, Leif
AU - McFayden, Josh
AU - Papaefstathiou, Andreas
AU - Plätzer, Simon
AU - Schumann, Steffen
AU - Seymour, Michael H.
AU - Siegert, Frank
AU - Siódmok, Andrzej
AU - The MCnet Community
A2 - Bothmann, Enrico
A2 - Buckley, Andy
A2 - Gütschow, Christian
A2 - Prestel, Stefan
A2 - Schönherr, Marek
A2 - Skands, Peter
N1 - Funding Information:
This work was supported in part by the European Union as part of the Marie Sklodowska-Curie Innovative Training Network MCnetITN3 (grant agreement no. 722104). Of the editors, AB thanks the Royal Society for University Research Fellowship grant UF160548; AB and CG thank STFC for funding through the UK experimental particle physics consolidated grants programme; CG also thanks STFC for supporting the SWIFT-HEP project (grant ST/V002627/1); SP would like to acknowledge funding from the Swedish Research Council (Vetenskapsrådet), contract numbers 2016-05996 and 2020-04303; MS is funded by the Royal Society through a University Research Fellowship (URF\R1\180549) and an Enhancement Award (RGF\EA\181033 and CEC19\100349), and supported by the STFC under grant agreement ST/P001246/1.
PY - 2023/2/8
Y1 - 2023/2/8
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85151844808&partnerID=8YFLogxK
U2 - 10.21468/SciPostPhysCore.6.1.007
DO - 10.21468/SciPostPhysCore.6.1.007
M3 - Article
AN - SCOPUS:85151844808
SN - 2666-9366
VL - 6
JO - SciPost Physics Core
JF - SciPost Physics Core
IS - 1
M1 - 007
ER -