https://doi.org/10.1051/epjconf/202531906001
Using artificial neural networks in searches for Lorentz invariance violation
University of Rijeka, Faculty of Physics, Rijeka 51000, Croatia
* e-mail: tterzic@uniri.hr
Published online: 6 March 2025
Lorentz invariance violation (LIV) in gamma rays can have multiple consequences, such as energy-dependent photon group velocity, photon instability, vacuum birefringence, and modified electromagnetic interaction. Depending on how LIV is introduced, several of these effects can occur simultaneously. Nevertheless, in experimental tests of LIV, each effect is tested separately and independently. For the first time, we are attempting to test for two effects in a single analysis: modified gamma-ray absorption and energy-dependent photon group velocity. In doing so, we are using artificial neural networks. In this contribution, we discuss our experiences with using machine learning for this purpose and present our very first results.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
