SciPost Submission Page
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 | |
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| Preprint Link: | https://arxiv.org/abs/2208.14760v4 (pdf) |
| Code repository: | https://github.com/lovaslin/pyBH-test |
| Date accepted: | June 15, 2023 |
| Date submitted: | April 6, 2023, 2:18 p.m. |
| Submitted by: | Louis Vaslin |
| Submitted to: | SciPost Physics Codebases |
| Ontological classification | |
|---|---|
| Academic field: | Physics |
| Specialties: |
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| Approach: | Experimental |
Abstract
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
Published as SciPost Phys. Codebases 15 (2023) , SciPost Phys. Codebases 15-r0.4 (2023)