Application of graph networks to background rejection in Imaging Air Cherenkov Telescopes - Glombitza, Jonas; Joshi, Vikas; Bruno, Benedetta; Funk, Stefan (Journal of Cosmology and Astroparticle Physics, 2023)
Imaging Air Cherenkov Telescopes (IACTs) are essential to ground-based observations of gamma rays in the GeV to TeV regime. One particular challenge of ground-based gamma-ray astronomy is an effective rejection of the hadronic background. We propose a new deep-learning-based algorithm for classifying images measured using single or multiple Imaging Air Cherenkov Telescopes. We interpret the detected images as a collection of triggered sensors that can be represented by graphs and analyzed by graph convolutional networks. For images cleaned of the light from the night sky, this allows for an efficient algorithm design that bypasses the challenge of sparse images in deep learning approaches based on computer vision techniques such as convolutional neural networks. We investigate different graph network architectures and find a promising performance with improvements to previous machine-learning and deep-learning-based methods.
CRIS-Team Scopus Importer:2023-12-01
Keywords: cosmic rays detectors; gamma ray detectors; Machine learning

Application of graph networks to γ/hadron separation in IACT image analyses - Glombitza, Jonas; Joshi, Vikas; Bruno, Benedetta; Funk, Stefan (Proceedings of Science, 2024)
Imaging Atmospheric Cherenkov Telescopes (IACTs) enable precise ground-based observations of the gamma-ray sky by imaging the distribution of Cherenkov light emitted during the development of air showers. Nowadays, many reconstruction algorithms rely on an elliptical high-level parameterization of these IACT images — the Hillas parameterization — and exploit their correlations. To overcome the limitations of the elliptical modeling, besides sophisticated analytical or template-based models, the advent of deep learning allows for reconstruction techniques that showed first promising results. By interpreting the detected images as a collection of triggered sensors that graphs can represent, we propose an algorithm based on graph networks for stereoscopic IACT image analyses. For images cleaned from background noise, this allows for an efficient algorithm design that bypasses the challenge of sparse images that occur in deep learning approaches based on convolutional neural networks. We investigate graph network architectures to two different stereoscopic data sets, simulated for the H.E.S.S. experiment. The algorithm enables an excellent γ/hadron separation with improvements to classical machine learning. Further, we find that the algorithm offers promising prospects for stereoscopic reconstructions also for telescopes featuring different camera geometries.
CRIS-Team Scopus Importer:2025-02-04

Constraints on the Intergalactic Magnetic Field Using Fermi-LAT and H.E.S.S. Blazar Observations - Aharonian, F.; Aschersleben, J.; Backes, M.; Martins, V. Barbosa; Batzofin, R.; Becherini, Y.; Berge, D.; Bi, B.; Bouyahiaoui, M.; Breuhaus, M.; Brose, R.; Brun, F.; et al. (Astrophysical Journal Letters, 2023)

Detection of extended γ -ray emission around the Geminga pulsar with H.E.S.S. - Aharonian, F.; Ait Benkhali, F.; Aschersleben, J.; Ashkar, H.; Backes, M.; Barbosa Martins, V.; Batzofin, R.; Becherini, Y.; Berge, D.; Bernlöhr, K.; Bi, B.; Böttcher, M.; et al. (Astronomy & Astrophysics, 2023)
Geminga is an enigmatic radio-quiet γ-ray pulsar located at a mere 250 pc distance from Earth. Extended very-high-energy γ-ray emission around the pulsar was discovered by Milagro and later confirmed by HAWC, which are both water Cherenkov detector-based experiments. However, evidence for the Geminga pulsar wind nebula in gamma rays has long evaded detection by imaging atmospheric Cherenkov telescopes (IACTs) despite targeted observations. The detection of γ-ray emission on angular scales ≳2° poses a considerable challenge for the background estimation in IACT data analysis. With recent developments in understanding the complementary background estimation techniques of water Cherenkov and atmospheric Cherenkov instruments, the H.E.S.S. IACT array can now confirm the detection of highly extended γ-ray emission around the Geminga pulsar with a radius of at least 3° in the energy range 0.5-40 TeV. We find no indications for statistically significant asymmetries or energy-dependent morphology. A flux normalisation of (2.8 ± 0.7)×10-12 cm-2 s-1 TeV-1 at 1 TeV is obtained within a 1° radius region around the pulsar. To investigate the particle transport within the halo of energetic leptons around the pulsar, we fitted an electron diffusion model to the data. The normalisation of the diffusion coefficient obtained of D0 = 7.6-1.2+1.5×1027 cm2 s-1, at an electron energy of 100 TeV, is compatible with values previously reported for the pulsar halo around Geminga, which is considerably below the Galactic average.
CRIS-Team Scopus Importer:2023-06-16
Keywords: Acceleration of particles; Diffusion; Gamma rays: general; Pulsars: general

HESS J1809-193: A halo of escaped electrons around a pulsar wind nebula? - Aharonian, F.; Ait Benkhali, F.; Aschersleben, J.; Ashkar, H.; Backes, M.; Barbosa Martins, V.; Batzofin, R.; Becherini, Y.; Berge, D.; Boettcher, M.; Boisson, C.; Bolmont, J.; et al. (Astronomy & Astrophysics, 2023)
Context. HESS J1809-193 is an unassociated very-high-energy gamma-ray source located on the Galactic plane. While it has been connected to the nebula of the energetic pulsar PSR J1809-1917, supernova remnants and molecular clouds present in the vicinity also constitute possible associations. Recently, the detection of gamma-ray emission up to energies of similar to 100 TeV with the HAWC observatory has led to renewed interest in HESS J1809-193.Aims. We aim to understand the origin of the gamma-ray emission of HESS J1809-193.Methods. We analysed 93.2 h of data taken on HESS J1809-193 above 0.27 TeV with the High Energy Stereoscopic System (H.E.S.S.), using a multi-component, three-dimensional likelihood analysis. In addition, we provide a new analysis of 12.5 yr of Fermi-LAT data above 1 GeV within the region of HESS J1809-193. The obtained results are interpreted in a time-dependent modelling framework.Results. For the first time, we were able to resolve the emission detected with H.E.S.S. into two components: an extended component (modelled as an elongated Gaussian with a 1-sigma semi-major and semi-minor axis of similar to 0.62 degrees and similar to 0.35 degrees, respectively) that exhibits a spectral cutoff at similar to 13 TeV, and a compact component (modelled as a symmetric Gaussian with a 1-sigma radius of similar to 0.1 degrees) that is located close to PSR J1809-1917 and shows no clear spectral cutoff. The Fermi-LAT analysis also revealed extended gamma-ray emission, on scales similar to that of the extended H.E.S.S. component.Conclusions. Our modelling indicates that based on its spectrum and spatial extent, the extended H.E.S.S. component is likely caused by inverse Compton emission from old electrons that form a halo around the pulsar wind nebula. The compact component could be connected to either the pulsar wind nebula or the supernova remnant and molecular clouds. Due to its comparatively steep spectrum, modelling the Fermi-LAT emission together with the H.E.S.S. components is not straightforward.
CRIS-Team WoS Importer:2023-05-05