Validation of open-source science tools and background model construction in γ-ray astronomy

Abstract

In classical analyses of γ-ray data from imaging atmospheric Cherenkov telescopes (IACTs), such as the High Energy Stereoscopic System (H.E.S.S.), aperture photometry, or photon counting, is applied in a (typically circular) region of interest (RoI) encompassing the source. A key element in the analysis is to estimate the amount of background in the RoI due to residual cosmic ray-induced air showers in the data. Various standard background estimation techniques have been developed in the last decades, most of them rely on a measurement of the background from source-free regions within the observed field of view. However, in particular in the Galactic plane, source analysis and background estimation are hampered by the large number of, sometimes overlapping, γ-ray sources and large-scale diffuse γ-ray emission. For complicated fields of view, a three-dimensional (3D) likelihood analysis shows the potential to be superior to classical analysis. In this analysis technique, a spectromorphological model, consisting of one or multiple source components and a background component, is fitted to the data, resulting in a complete spectral and spatial description of the field of view. For the application to IACT data, the major challenge of such an approach is the construction of a robust background model. In this work, we apply the 3D likelihood analysis to various test data recently made public by the H.E.S.S. collaboration, using the open analysis frameworks ctools and Gammapy. First, we show that, when using these tools in a classical analysis approach and comparing to the proprietary H.E.S.S. analysis framework, virtually identical high-level analysis results, such as field-of-view maps and spectra, are obtained. We then describe the construction of a generic background model from data of H.E.S.S. observations, and demonstrate that a 3D likelihood analysis using this background model yields high-level analysis results that are highly compatible with those obtained from the classical analyses. This validation of the 3D likelihood analysis approach on experimental data is an important step towards using this method for IACT data analysis, and in particular for the analysis of data from the upcoming Cherenkov Telescope Array (CTA).

The young massive stellar cluster Westerlund 1 in gamma rays as seen with H.E.S.S.

“…The young massive stellar cluster Westerlund 1 as seen with H.E.S.S. construct a model for the residual hadronic background, depending on two field-of-view coordinates and reconstructed energy, following the procedure described in [15]. We then employ Gammapy to carry out the subsequent high-level analysis.…”

“…While this approach is still relatively new in IACT data analysis, its application to the analysis of H.E.S.S. data has been explored and verified [15]. We carry out the analysis using the Gammapy software package [16] (version 0.17), which naturally provides the possibility to perform likelihood analyses based on 3D background models.…”

Revisiting the PeVatron candidate MGRO J1908+06 with an updated H.E.S.S. analysis

“…This is an another cross-check and validation of gammapy, a toolset for the future gamma-ray observatories, which has started to be used in H.E.S.S. recently [2,23,24…”

Search for enhanced TeV gamma ray emission from Giant Molecular Clouds using H.E.S.S.

“…A three dimensional (3D) likelihood analysis provides us with a much more sensitive technique. While such techniques have been routinely used for high energy -ray data processing, its implementation in the field of IACT analysis is relatively recent [14,15]. A spectro-morphological template model is constructed for the cosmic ray-induced background from archival runs with mostly empty fields of view.…”