Statistical patterns of theory uncertainties
Aishik Ghosh, Benjamin Nachman, Tilman Plehn, Lily Shire, Tim M. P. Tait, Daniel Whiteson
SciPost Phys. Core 6, 045 (2023) · published 20 June 2023
- doi: 10.21468/SciPostPhysCore.6.2.045
- Submissions/Reports
Abstract
A comprehensive uncertainty estimation is vital for the precision program of the LHC. While experimental uncertainties are often described by stochastic processes and well-defined nuisance parameters, theoretical uncertainties lack such a description. We study uncertainty estimates for cross-section predictions based on scale variations across a large set of processes. We find patterns similar to a stochastic origin, with accurate uncertainties for processes mediated by the strong force, but a systematic underestimate for electroweak processes. We propose an improved scheme, based on the scale variation of reference processes, which reduces outliers in the mapping from leading order to next-to-leading-order in perturbation theory.
Cited by 3
Authors / Affiliations: mappings to Contributors and Organizations
See all Organizations.- 1 2 Aishik Ghosh,
- 1 3 Benjamin Nachman,
- 4 Tilman Plehn,
- 2 Lily Shire,
- 2 Tim M. P. Tait,
- 2 Daniel Whiteson
- 1 Lawrence Berkeley National Laboratory [LBNL]
- 2 University of California, Irvine [UCI]
- 3 University of California, Berkeley [UCBL]
- 4 Ruprecht-Karls-Universität Heidelberg / Heidelberg University