TY  - JOUR
PB  - SciPost Foundation
DO  - 10.21468/SciPostPhysCore.6.2.045
TI  - Statistical patterns of theory uncertainties
PY  - 2023/06/20
UR  - https://www.scipost.org/SciPostPhysCore.6.2.045
JF  - SciPost Physics Core
JA  - SciPost Phys. Core
VL  - 6
IS  - 2
SP  - 045
A1  - Ghosh, Aishik
AU  - Nachman, Benjamin
AU  - Plehn, Tilman
AU  - Shire, Lily
AU  - Tait, Tim M. P.
AU  - Whiteson, Daniel
AB  - 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.
ER  -

@Article{10.21468/SciPostPhysCore.6.2.045,
	title={{Statistical patterns of theory uncertainties}},
	author={Aishik Ghosh and Benjamin Nachman and Tilman Plehn and Lily Shire and Tim M. P. Tait and Daniel Whiteson},
	journal={SciPost Phys. Core},
	volume={6},
	pages={045},
	year={2023},
	publisher={SciPost},
	doi={10.21468/SciPostPhysCore.6.2.045},
	url={https://scipost.org/10.21468/SciPostPhysCore.6.2.045},
}