Cyann Plard | Searcharxiv

arXiv2026

Lorentz invariance violation search with flaring active galactic nuclei observations of the first Large-Sized Telescope of CTAO

The rapid variability observed in very-high-energy (VHE) sources-such as pulsars, gamma-ray bursts (GRBs), and flares from active galactic nuclei (AGN)-can be used to detect or constrain a potential violation of Lorentz invariance (LIV). These effects can be investigated by measuring time lags in the arrival of VHE photons. However, an important source of uncertainty arises from intrinsic processes within the sources themselves that may induce photon delays unrelated to LIV. To address this challenge, we aim to combine observations of different sources, located at different redshifts. In this study, we present the results of a standardized analysis applied to all AGN observations conducted by the first Large-Sized Telescope of the upcoming Cherenkov Telescope Array Observatory. Our analysis includes a systematic search for intra-night variability in archival data from nights with significant excess detections for target candidates. By combining these observations, we derive constraints on the characteristic energy scales at which LIV deterministic or stochastic effects are expected to manifest.

astro-ph.HE↗

arXiv2024

Deep Learning and IACT: Bridging the gap between Monte-Carlo simulations and LST-1 data using domain adaptation

The Cherenkov Telescope Array Observatory (CTAO) is the next generation of observatories employing the imaging air Cherenkov technique for the study of very high energy gamma rays. The deployment of deep learning methods for the reconstruction of physical attributes of incident particles has evinced promising outcomes when conducted on simulations. However, the transition of this approach to observational data is accompanied by challenges, as deep learning-based models are susceptible to domain shifts. In this paper, we integrate domain adaptation in the physics-based context of the CTAO and shed light on the gain in performance that these techniques bring using LST-1 real acquisitions.

astro-ph.IM↗