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arXiv · 2210.15167

Statistical Patterns of Theory Uncertainties

Aishik Ghosh·Benjamin Nachman·Tilman Plehn·Lily Shire·Tim M. P. Tait·Daniel Whiteson
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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.

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Aishik Ghosh, Benjamin Nachman, Tilman Plehn, Lily Shire, Tim M. P. Tait, Daniel Whiteson. 2023-05-05. Statistical Patterns of Theory Uncertainties. https://arxiv.org/abs/2210.15167

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