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PreprintarXiv licencearXiv

A method for enhanced gamma-proton discrimination with imaging atmospheric Cherenkov telescopes

Abstract

Purpose: Very-high-energy gamma-ray astronomy is an important window to study the extreme astrophysical processes in the universe, and how to effectively distinguish between gamma photons and background signals (mainly protons) is a key technical challenge to realize very-high-energy gamma-ray detection. Spaceborne calorimeters record secondary particle spatial distributions, achieving a background rejection power of 10000-100000 near 1 TeV. Ground-based imaging Cherenkov telescopes measure Cherenkov photon angular distributions, yet they only reach a rejection factor of about 10 in this energy range, leaving substantial room for optimization. Methods: We use CORSIKA and sim_telarray to simulate H.E.S.S. detector responses. Photon emission positions are reconstructed from Cherenkov shower images. Inspired by analysis techniques for space-borne calorimeter, we propose new observables derived from the transverse distribution of Cherenkov photon emission positions to separate gamma-ray signals from proton backgrounds. We employ a likelihood-ratio method to combine single-telescope variables across multiple telescopes and compare its performance with conventional Hillas-based analysis. Results: The results show that observables built from the transverse distribution of Cherenkov photon emission positions are less sensitive to Cherenkov image size and outperform the Hillas width parameter for single-telescope gamma-proton discrimination. Furthermore, the likelihood ratio combining width yields substantially better performance than the conventional mean reduced scaled width: the improvement reaches roughly one order of magnitude near 1 TeV, and this enhancement remains above 50% for energies above 10 TeV.

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BibTeX
@misc{liu2026method,
  title = {{A method for enhanced gamma-proton discrimination with imaging atmospheric Cherenkov telescopes}},
  author = {Jianling Liu and Hu Liu},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2609.21635},
  eprint = {2609.21635},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.21635},
}
RIS
TY  - UNPB
TI  - A method for enhanced gamma-proton discrimination with imaging atmospheric Cherenkov telescopes
AU  - Jianling Liu
AU  - Hu Liu
PY  - 2026
DA  - 2026/09/18
PB  - arXiv
DO  - 10.48550/arxiv.2609.21635
UR  - https://arxiv.org/abs/2609.21635
AB  - Purpose: Very-high-energy gamma-ray astronomy is an important window to study the extreme astrophysical processes in the universe, and how to effectively distinguish between gamma photons and background signals (mainly protons) is a key technical challenge to realize very-high-energy gamma-ray detection. Spaceborne calorimeters record secondary particle spatial distributions, achieving a background rejection power of 10000-100000 near 1 TeV. Ground-based imaging Cherenkov telescopes measure Cherenkov photon angular distributions, yet they only reach a rejection factor of about 10 in this energy range, leaving substantial room for optimization. Methods: We use CORSIKA and sim_telarray to simulate H.E.S.S. detector responses. Photon emission positions are reconstructed from Cherenkov shower images. Inspired by analysis techniques for space-borne calorimeter, we propose new observables derived from the transverse distribution of Cherenkov photon emission positions to separate gamma-ray signals from proton backgrounds. We employ a likelihood-ratio method to combine single-telescope variables across multiple telescopes and compare its performance with conventional Hillas-based analysis. Results: The results show that observables built from the transverse distribution of Cherenkov photon emission positions are less sensitive to Cherenkov image size and outperform the Hillas width parameter for single-telescope gamma-proton discrimination. Furthermore, the likelihood ratio combining width yields substantially better performance than the conventional mean reduced scaled width: the improvement reaches roughly one order of magnitude near 1 TeV, and this enhancement remains above 50% for energies above 10 TeV.
ER  -