The Monte Carlo replica method: investigating the effects of non-linearity

This paper presents an in-depth mathematical analysis of the Monte Carlo replica method, commonly used in global fitting studies within the high-energy physics theory field. For the first time, we offer a rigorous derivation of the parameter distributions resulting from this method, demonstrating that, while they align with Bayesian posteriors in linear models, they deviate in non-linear cases. We then numerically assess this discrepancy in a phenomenologically important context: fitting SMEFT Wilson coefficients. Our findings reveal that when non-linearity plays a significant role, the uncertainty estimates for key quantities differ between the two approaches.

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Publication Details

Published
2024-12-27
DOI
https://doi.org/10.22323/1.469.0052
Primary Topic
Markov Chains and Monte Carlo Methods
Type
article
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article

The Monte Carlo replica method: investigating the effects of non-linearity

Mark N. Costantini
Markov Chains and Monte Carlo Methods
article

The Monte Carlo replica method: investigating the effects of non-linearity

Mark N. Costantini
article en

Abstract

This paper presents an in-depth mathematical analysis of the Monte Carlo replica method, commonly used in global fitting studies within the high-energy physics theory field. For the first time, we offer a rigorous derivation of the parameter distributions resulting from this method, demonstrating that, while they align with Bayesian posteriors in linear models, they deviate in non-linear cases. We then numerically assess this discrepancy in a phenomenologically important context: fitting SMEFT Wilson coefficients. Our findings reveal that when non-linearity plays a significant role, the uncertainty estimates for key quantities differ between the two approaches.

Openalex Percentile: Top 75%
Markov Chains and Monte Carlo Methods
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The Monte Carlo replica method: investigating the effects of non-linearity — Mark N. Costantini · (2024) | TGRS Research Map | TGRS