Performance of the joint LST-1 and MAGIC observations evaluated with Crab Nebula data
H. Abe, K. Abe, S. Abe, V. A. Acciari, A. Aguasca-Cabot, I. Agudo, N., Alvarez Crespo, T. Aniello, S. Ansoldi, L. A. Antonelli, C. Aramo, A., Arbet-Engels, C. Arcaro, M. Artero, K. Asano, P. Aubert, D. Baack, A., Babi\'c, A. Baktash, A. Bamba, A. Baquero Larriva, L. Baroncelli

TL;DR
This study evaluates the combined performance of LST-1 and MAGIC telescopes using Crab Nebula data, demonstrating improved sensitivity and spectrum measurement in gamma-ray observations between 60 GeV and 10 TeV.
Contribution
It introduces a joint analysis pipeline for LST-1 and MAGIC, showing enhanced detection capabilities and background rejection compared to individual systems.
Findings
30% increased sensitivity to weaker fluxes
Improved collection area and background rejection
Crab Nebula spectrum consistent with previous results
Abstract
Aims. LST-1, the prototype of the Large-Sized Telescope for the upcoming Cherenkov Telescope Array Observatory, is concluding its commissioning in Observatorio del Roque de los Muchachos on the island of La Palma. The proximity of LST-1 (Large-Sized Telescope 1) to the two MAGIC (Major Atmospheric Gamma Imaging Cherenkov) telescopes permits observations of the same gamma-ray events with both systems. Methods. We describe the joint LST-1+MAGIC analysis pipeline and use simultaneous Crab Nebula observations and Monte Carlo simulations to assess the performance of the three-telescope system. The addition of the LST-1 telescope allows the recovery of events in which one of the MAGIC images is too dim to survive analysis quality cuts. Results. Thanks to the resulting increase in the collection area and stronger background rejection, we find a significant improvement in sensitivity, allowing…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
