Xsec: the cross-section evaluation code

Buckley, A. , Kvellestad, A., Raklev, A., Scott, P., Sparre, J. V., Van den Abeele, J. and Vazquez-Holm, I. A. (2020) Xsec: the cross-section evaluation code. European Physical Journal C, 80(12), 1106. (doi: 10.1140/epjc/s10052-020-08635-y)

Abstract

Abstract: The evaluation of higher-order cross-sections is an important component in the search for new physics, both at hadron colliders and elsewhere. For most new physics processes of interest, total cross-sections are known at next-to-leading order (NLO) in the strong coupling αs, and often beyond, via either higher-order terms at fixed powers of αs, or multi-emission resummation. However, the computation time for such higher-order cross-sections is prohibitively expensive, and precludes efficient evaluation in parameter-space scans beyond two dimensions. Here we describe the software tool xsec, which allows for fast evaluation of cross-sections based on the use of machine-learning regression, using distributed Gaussian processes trained on a pre-generated sample of parameter points. This first version of the code provides all NLO Minimal Supersymmetric Standard Model strong-production cross-sections at the LHC, for individual flavour final states, evaluated in a fraction of a second. Moreover, it calculates regression errors, as well as estimates of errors from higher-order contributions, from uncertainties in the parton distribution functions, and from the value of αs. While we focus on a specific phenomenological model of supersymmetry, the method readily generalises to any process where it is possible to generate a sufficient training sample.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Buckley, Professor Andy
• Authors: Buckley, A., Kvellestad, A., Raklev, A., Scott, P., Sparre, J. V., Van den Abeele, J., and Vazquez-Holm, I. A.
• College/School: College of Science and Engineering > School of Physics and Astronomy
• Journal Name: European Physical Journal C
• Publisher: Springer
• ISSN: 1434-6044
• ISSN (Online): 1434-6052
• Published Online: 02 December 2020
• Copyright Holders: Copyright © 2020 The Authors
• First Published: First published in European Physical Journal C 80(12): 1106
• Publisher Policy: Reproduced under a Creative Commons License

Project Code	Award No	Project Name	Principal Investigator	Funder's Name	Funder Ref	Lead Dept
300260		New physics studies with heavy flavour at the LHC	Andrew Buckley	The Royal Society (ROYSOC)	UF160548	P&S - Physics & Astronomy