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Bibliographic Details
Main Authors: Brianti, Greta, Iuppa, Roberto, Cristoforetti, Marco
Format: Preprint
Published: 2023
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Online Access:https://arxiv.org/abs/2312.06245
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author Brianti, Greta
Iuppa, Roberto
Cristoforetti, Marco
author_facet Brianti, Greta
Iuppa, Roberto
Cristoforetti, Marco
contents Machine Learning is a rapidly expanding field with a wide range of applications in science. In the field of physics, the Large Hadron Collider, the world's largest particle accelerator, utilizes Neural Networks for various tasks, including flavour tagging. Flavour tagging is the process of identifying the flavour of the hadron that initiates a jet in a collision event, and it is an essential aspect of many Standard Model and Beyond the Standard Model research. Graph Neural Networks are currently the primary machine-learning tool used for flavour tagging. Here, we present the AUTOGRAPH pipeline, a completely customizable tool designed with a user-friendly interface to provide easy access to the Graph Neural Networks algorithm used for flavour tagging.
format Preprint
id arxiv_https___arxiv_org_abs_2312_06245
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Pipeline for performance evaluation of flavour tagging dedicated Graph Neural Network algorithms
Brianti, Greta
Iuppa, Roberto
Cristoforetti, Marco
High Energy Physics - Experiment
Machine Learning is a rapidly expanding field with a wide range of applications in science. In the field of physics, the Large Hadron Collider, the world's largest particle accelerator, utilizes Neural Networks for various tasks, including flavour tagging. Flavour tagging is the process of identifying the flavour of the hadron that initiates a jet in a collision event, and it is an essential aspect of many Standard Model and Beyond the Standard Model research. Graph Neural Networks are currently the primary machine-learning tool used for flavour tagging. Here, we present the AUTOGRAPH pipeline, a completely customizable tool designed with a user-friendly interface to provide easy access to the Graph Neural Networks algorithm used for flavour tagging.
title Pipeline for performance evaluation of flavour tagging dedicated Graph Neural Network algorithms
topic High Energy Physics - Experiment
url https://arxiv.org/abs/2312.06245