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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
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Submission summary
Authors (as registered SciPost users): | Louis Vaslin |
Submission information | |
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Preprint Link: | https://arxiv.org/abs/2208.14760v3 (pdf) |
Code repository: | https://github.com/lovaslin/pyBH-test |
Date submitted: | March 6, 2023, 4:23 p.m. |
Submitted by: | Vaslin, Louis |
Submitted to: | SciPost Physics Core |
Ontological classification | |
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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.
List of changes
Added the modification requested by the editorial report.
Current status:
Reports on this Submission
Report #1 by Mohamed Rameez (Referee 1) on 2023-3-28 (Invited Report)
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Requested changes
The author says "Using a mean+-68% interval (1 sigma) would indeed make more sense and this feature will be added to future releases of pyBumpHunter.
However we decided to keep this description in the paper since it corresponds to what the current stable release of pyBumpHunter does."
Perhaps this should be emphasized in text? That a nonstandard definition of uncertainties is being used.
Author: Louis Vaslin on 2023-04-06 [id 3560]
(in reply to Report 1 by Mohamed Rameez on 2023-03-28)Thank you again for your feedback.
We agree that one the main purpose of this paper is to present in details the features proposed in the pyBumpHunter package.
If it is more pertinent to have it in SciPost Physics codebases, we have no objections.
Concerning the nonstandard definition of uncertainties in section 2, we added a sentence in the caption of figure 4 :
"This is a nonstandard definition of uncertainties that will be modified in future release to cover a 68% confidence interval corresponding to 1σ."
Here is the link to the last version on arXiv : https://arxiv.org/abs/2208.14760v4
Best regards,
Louis Vaslin, for the authors