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pyBumpHunter: A model independent bump hunting tool in Python for High Energy Physics analyses

by Louis Vaslin, Samuel Calvet, Vincent Barra, Julien Donini

Submission summary

Authors (as registered SciPost users): Louis Vaslin
Submission information
Preprint Link:  (pdf)
Code repository:
Date accepted: 2023-06-15
Date submitted: 2023-04-06 14:18
Submitted by: Vaslin, Louis
Submitted to: SciPost Physics Codebases
Ontological classification
Academic field: Physics
  • High-Energy Physics - Experiment
Approach: Experimental


The BumpHunter algorithm is widely used in the search for new particles in High Energy Physics analysis. This algorithm offers the advantage of evaluating the local and global p-values of a localized deviation in the observed data without making any hypothesis on the supposed signal. The increasing popularity of the Python programming language motivated the development of a new public implementation of this algorithm in Python, called pyBumpHunter, together with several improvements and additional features. It is the first public implementation of the BumpHunter algorithm to be added to Scikit-HEP. This paper presents in detail the BumpHunter algorithm as well as all the features proposed in this implementation. All these features have been tested in order to demonstrate their behaviour and performance.

Author comments upon resubmission

This version includes a minor modification following the recommendations of the reviewers.

Published as SciPost Phys. Codebases 15-r0.4 (2023) , SciPost Phys. Codebases 15 (2023)

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