Energy-dependent gamma-ray morphology estimation tool in Gammapy
Feijen K, Terrier R, Khélifi B, Sinha A, Donath A, Mitchell A, Remy Q (2025)
Publication Language: English
Publication Type: Journal article
Publication year: 2025
Journal
Book Volume: 701
Article Number: A4
DOI: 10.1051/0004-6361/202555208
Abstract
Context. An understanding of the energy dependence of gamma-ray sources can yield important information on the underlying emission mechanisms. However, despite the detection of energy-dependent morphologies in many TeV sources, we lack a proper quantification of such measurements. Aims. We introduce an estimation tool within the Gammapy landscape, an open-source Python package for the analysis of gamma-ray data, for quantifying the energy-dependent morphology of a gamma-ray source. Methods. The proposed method fits the spatial morphology in a global fit across all energy slices (null hypothesis) and compares this to separate fits for each energy slice (alternative hypothesis). These are modelled using forward-folding methods, and the significance of the variability is quantified by comparing the test statistics of the two hypotheses. Results. We present a general tool for probing changes in the spatial morphology with energy, employing a full forward-folding approach with a 3D likelihood. We present its usage on a real dataset from H.E.S.S. and on a simulated dataset to quantify the significance of the energy dependence for sources of different sizes. In the first example, which utilises a subset of data from HESS J1825 137, we observe extended emission at lower energies that becomes more compact at higher energies. The tool indicates a very significant variability (9.8I) in the case of the largely extended emission. In the second example, a source with a smaller extent (~0.1), simulated using the CTAO response, shows the tool can still provide a statistically significant variation (9.7I) on small scales.
Authors with CRIS profile
Involved external institutions
University of Paris 7 - Denis Diderot / Université Paris VII Denis Diderot
France (FR)
Tata Institute of Fundamental Research (TIFR)
India (IN)
Smithsonian Institution
United States (USA) (US)
Max-Planck-Institut für Kernphysik (MPIK) / Max Planck Institute for Nuclear Physics
Germany (DE)
France (FR)
Tata Institute of Fundamental Research (TIFR)
India (IN)
Smithsonian Institution
United States (USA) (US)
Max-Planck-Institut für Kernphysik (MPIK) / Max Planck Institute for Nuclear Physics
Germany (DE)
How to cite
APA:
Feijen, K., Terrier, R., Khélifi, B., Sinha, A., Donath, A., Mitchell, A., & Remy, Q. (2025). Energy-dependent gamma-ray morphology estimation tool in Gammapy. Astronomy & Astrophysics, 701. https://doi.org/10.1051/0004-6361/202555208
MLA:
Feijen, K., et al. "Energy-dependent gamma-ray morphology estimation tool in Gammapy." Astronomy & Astrophysics 701 (2025).
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