First combined studies on Lorentz Invariance Violation from observations of astrophysical sources

TL;DR

This paper presents the first combined analysis of astrophysical observations from multiple Cherenkov Telescope collaborations to search for Lorentz Invariance Violation effects, aiming to improve sensitivity and systematic control.

Contribution

It introduces a joint maximum likelihood analysis method combining data from H.E.S.S., MAGIC, and VERITAS to enhance LIV search sensitivity and address systematic uncertainties.

Findings

First combined maximum likelihood analysis of LIV using multiple telescopes

Improved sensitivity to LIV effects across different sources and redshifts

Strategies developed for multi-instrument data integration

Abstract

Imaging Atmospheric Cherenkov Telescopes study the highest energy (up to tens of TeV) photon emission coming from nearby and distant astrophysical sources, thus providing valuable results from searches for Lorentz Invariance Violation (LIV) effects. Highly variable, energetic and distant sources such as Pulsars and AGNs are the best targets for the Time-of-Flight LIV studies. However, the limited number of observations of AGN flares or of high-energy pulsed emission greatly restricts the potential of such studies, especially any potential LIV effects as a function of redshift. To address these issues, an inter-experiment working group has been established by the three major collaborations taking data with Imaging Atmospheric Cherenkov Telescopes (H.E.S.S., MAGIC and VERITAS) with the aim to increase sensitivity to any effects of LIV, together with an improved control of systematic uncertainties, by sharing data samples and developing joint analysis methods. This will allow an increase in the number of available sources and to perform a sensitive search for redshift dependencies. This presentation reviews the first combined maximum likelihood method analyses using simu- lations of published source observations done in the past with H.E.S.S., MAGIC and VERITAS. The results from analyses based on combined maximum likelihood methods, the strategies to deal with data from different types of sources and instruments, as well as future plans will be presented.