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Jet substructure observables for jet quenching in Quark Gluon Plasma: a Machine Learning driven analysis
by Miguel Crispim Romão, José Guilherme Milhano, Marco van Leeuwen
This Submission thread is now published as
Submission summary
| Authors (as registered SciPost users): | Miguel Crispim Romao |
| Submission information | |
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| Preprint Link: | https://arxiv.org/abs/2304.07196v2 (pdf) |
| Code repository: | https://gitlab.com/lip_ml/jet-substructure-observables-ml-analysis |
| Data repository: | https://zenodo.org/record/7808000 |
| Date accepted: | 2023-12-21 |
| Date submitted: | 2023-12-13 09:26 |
| Submitted by: | Crispim Romao, Miguel |
| Submitted to: | SciPost Physics |
| Ontological classification | |
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| Academic field: | Physics |
| Specialties: |
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| Approach: | Phenomenological |
Abstract
We present a survey of a comprehensive set of jet substructure observables commonly used to study the modifications of jets resulting from interactions with the Quark Gluon Plasma in Heavy Ion Collisions. The \jewel{} event generator is used to produce simulated samples of quenched and unquenched jets. Three distinct analyses using Machine Learning techniques on the jet substructure observables have been performed to identify both linear and non-linear relations between the observables, and to distinguish the Quenched and Unquenched jet samples. We find that most of the observables are highly correlated, and that their information content can be captured by a small set of observables. We also find that the correlations between observables are resilient to quenching effects and that specific pairs of observables exhaust the full sensitivity to quenching effects. The code, the datasets, and instructions on how to reproduce this work are also provided.
Author comments upon resubmission
We would like to thank the referees for the positive and constructive feedback. We have followed their suggestions and applied the minor corrections and suggestions proposed to us.
Best regards,
Miguel Crispim Romao, for the authors
List of changes
Applied all minor corrections and suggestions from the referee.
In particular: changed robust to resilient across the text, extended the discussion on the dataset splits sizes, extended the discussion on the separation of observable types by the PCA, added an explanation of the ROC curve and how to interpret it.
The changes are better seen in the latexdiff provided to the referees in the comments.
Published as SciPost Phys. 16, 015 (2024)