Searching for Lorentz invariance violation with artificial neural networks

Fuente: arXiv
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Main Authors: Terzić, Tomislav, Mrakovčić, Karlo
Format: Preprint
Published: 2025
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author Terzić, Tomislav
Mrakovčić, Karlo
author_facet Terzić, Tomislav
Mrakovčić, Karlo
contents Lorentz invariance violation (LIV) can have multiple consequences on very-high energy gamma rays' emission, propagation, and detection, such as energy-dependent photon group velocity, photon instability, vacuum birefringence, and modified electromagnetic interaction. Depending on the underlying theoretical model, several of these effects can coexist. Nevertheless, in experimental tests of LIV, each effect is tested separately and independently. Here, we are performing a search for traces of several coexisting effects in a single analysis. We present our analysis method based on artificial neural networks and put our very first results in the context of experimental searches for LIV.
format Preprint
id arxiv_https___arxiv_org_abs_2509_14818
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Searching for Lorentz invariance violation with artificial neural networks
Terzić, Tomislav
Mrakovčić, Karlo
High Energy Astrophysical Phenomena
High Energy Physics - Experiment
High Energy Physics - Phenomenology
Lorentz invariance violation (LIV) can have multiple consequences on very-high energy gamma rays' emission, propagation, and detection, such as energy-dependent photon group velocity, photon instability, vacuum birefringence, and modified electromagnetic interaction. Depending on the underlying theoretical model, several of these effects can coexist. Nevertheless, in experimental tests of LIV, each effect is tested separately and independently. Here, we are performing a search for traces of several coexisting effects in a single analysis. We present our analysis method based on artificial neural networks and put our very first results in the context of experimental searches for LIV.
title Searching for Lorentz invariance violation with artificial neural networks
topic High Energy Astrophysical Phenomena
High Energy Physics - Experiment
High Energy Physics - Phenomenology
url https://arxiv.org/abs/2509.14818