Stowell, J.P., Pickering, L., Wret, C. et al. (10 more authors) (2017) NUISANCE: a neutrino cross-section generator tuning and comparison framework. Journal of Instrumentation, 12. P01016.
Abstract
NUISANCE is an open source C++ framework which facilitates detailed studies of neutrino interaction cross-section models implemented in Monte Carlo neutrino event generators. It provides a host of automated methods to perform comparisons of multiple generators to published cross-section measurements and each other. External reweighting libraries are used to allow the end-user to evaluate the impact of model parameters variations in the generators with data, or to tune the generator predictions to arbitrary dataset combinations. The design is modular and focusses on ease-of-use to allow new datasets and more generators to be added without requiring detailed understanding of the entire NUISANCE package. We discuss the motivation for the NUISANCE framework and suggested usage cases, alongside a description of its core structure.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 IOP Publishing Ltd and Sissa Medialab srl. This is an author produced version of a paper subsequently published in Journal of Instrumentation. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Software architectures (event data models, frameworks and databases); Analysis and statistical methods; Simulation methods and programs; Data processing methods |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) > Department of Physics and Astronomy (Sheffield) |
Funding Information: | Funder Grant number SCIENCE AND TECHNOLOGY FACILITIES COUNCIL ST/K001337/1 SCIENCE AND TECHNOLOGY FACILITIES COUNCIL ST/M002667/1 SCIENCE AND TECHNOLOGY FACILITIES COUNCIL ST/N000277/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 01 Mar 2017 09:52 |
Last Modified: | 20 Jan 2018 01:38 |
Published Version: | https://doi.org/10.1088/1748-0221/12/01/P01016 |
Status: | Published |
Publisher: | IOP Publishing: arXiv |
Refereed: | Yes |
Identification Number: | 10.1088/1748-0221/12/01/P01016 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:112886 |