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In this article, we present Gammapy, an open-source Python package for the analysis of astronomical $\gamma$-ray data, and illustrate the functionalities of its first long-term-support release, version 1.0. Built on the modern Python scientific ecosystem, Gammapy provides a uniform platform for reducing and modeling data from different $\gamma$-ray instruments for many analysis scenarios. Gammapy complies with several well-established data conventions in high-energy astrophysics, providing serialized data products that are interoperable with other software packages. Starting from event lists and instrument response functions, Gammapy provides functionalities to reduce these data by binning them in energy and sky coordinates. Several techniques for background estimation are implemented in the package to handle the residual hadronic background affecting $\gamma$-ray instruments. After the data are binned, the flux and morphology of one or more $\gamma$-ray sources can be estimated using Poisson maximum likelihood fitting and assuming a variety of spectral, temporal, and spatial models. Estimation of flux points, likelihood profiles, and light curves is also supported. After describing the structure of the package, we show, using publicly available $\gamma$-ray data, the capabilities of Gammapy in multiple traditional and novel $\gamma$-ray analysis scenarios, such as spectral and spectro-morphological modeling and estimations of a spectral energy distribution and a light curve. Its flexibility and power are displayed in a final multi-instrument example, where datasets from different instruments, at different stages of data reduction, are simultaneously fitted with an astrophysical flux model., Comment: 26 pages, 16 figures

The standardisation of gamma-ray astronomical data emerged in recent years as a necessity for the future generation of gamma-ray observatories. Nevertheless, adopting a common format for gamma-ray instruments can already benefit the current generation of gamma-ray instruments. As the end of their operations approaches, it provides a natural solution for the production of their data legacy. Additionally it eases data combination for multi-instrument analyses, thus enhancing the potential for scientific discovery with the wealth of data so far gathered. In this contribution, we present for the first time the effort to adapt the data of the MAGIC telescopes to the standardised format proposed by the Data Formats for Gamma-ray Astronomy initiative. We validate the data conversion by analysing the standardised data with the open-source software Gammapy and comparing the results obtained against those produced with the MAGIC proprietary software, MARS. For both samples chosen (Crab Nebula and Mrk421 observation), for all the scientific products extracted (spectra and light curves), we observe good agreement between the results of the two software., Comment: To be included in the Proceedings of 7th Heidelberg International Symposium on High-Energy Gamma-Ray Astronomy (Gamma2022)

The open-source Python package Gammapy, developed for the high-level analysis of gamma-ray data, requires gamma-like event lists combined with the corresponding instrument response functions. For a morphological analysis, these data have to include a background acceptance model. Here we report an approach to generate such a model for the MAGIC telescope data, accounting for the azimuth and zenith dependencies of the MAGIC background acceptance. We validate this method using observations of the Crab Nebula with different offsets from the pointing position., Comment: 6 pages, 6 figures, Proceedings of the 7th Heidelberg International Symposium on High-Energy Gamma-Ray Astronomy, PoS(Gamma2022)215

In this review, we discuss various open-source software for modelling the broad-band emission of extragalactic sources from radio up to the highest gamma ray energies. As we provide an overview of the different tools available, we discuss the physical processes such tools implement and detail the computations they can perform. We also examine their conformity with modern good software practices. After considering the currently available software as a first generation of open-source modelling tools, we outline some desirable characteristics for the next generation., Comment: Accepted for publication in Galaxies. Included in the special issue https://www.mdpi.com/journal/galaxies/special_issues/TeVAstronomy

The operation of the future Cherenkov Telescope Array (CTA), the next generation of Imaging Atmospheric Cherenkov Telescopes (IACTs), as an Open Observatory requires data products and analysis tools to be accessible and usable by the scientific community. This requirement has impelled gamma-ray astronomers to develop open-source science tools and standardised data formats. The objective of this presentation is to provide a perspective on the current effort to define a prototypical format for high-level gamma-ray astronomical data. The initiative, started by the IACT community in 2016, has gained in the years 2018 and 2019 full recognition thanks to the first public data releases in such format by current-generation IACTs, followed by a series of papers employing it either to test the capabilities of open-source gamma-ray analysis tools or to showcase examples of reproducible, multi-instrument analysis., Comment: Proceeding of the XXX Astronomical Data Analysis Software and Systems (ADASS) conference

The MAGIC telescopes are one of the three major IACTs (Imaging Atmospheric Cherenkov Telescopes) for observation of gamma rays in the TeV regime currently operative. MAGIC functions since 2003, and has published data from more than 60 sources, mostly blazars. MAGIC already provides astronomical \texttt{.fits} files with basic final scientific products such as spectral energy distributions, light curves and skymaps from published results. In future, the format of the files can be complemented with further relevant information to the community: a) by including the full multi-wavelength dataset enclosed in a publication, b) providing data in alternative easy-to-use formats such as ASCII or ECSV, which are accessible with other commonly used packages such as \texttt{astropy} or \texttt{gammapy}. Finally, besides high level products, activities have started to provide photon event lists and instrument response functions in a format such that scientists within and outside the community are allowed to perform higher level analysis. A second aim is to provide a full legacy of MAGIC data. This contribution will illustrate the achievements and plans of this activity., Comment: Proceedings of the ICRC 2019

The Cherenkov Telescope Array (CTA) will be able to perform unprecedented observations of the transient very high-energy sky. An on-line science alert generation (SAG) pipeline, with a required 30 second latency, will allow the discovery or follow-up of gamma ray bursts (GRBs) and flaring emission from active galactic nuclei, galactic compact objects and electromagnetic counterparts of gravitational waves or neutrino messengers. The CTA sensitivity for very short exposures does not only depend on the technological performance of the array (e.g. effective area, background discrimination efficiency). The algorithms to evaluate the significance of the detection also define the sensitivity, together with their computational efficiency in order to satisfy the SAG latency requirements. We explore the aperture photometry and likelihood analysis techniques, and the associated parameters (e.g. on-source to off-source exposure ratio, minimum number of required signal events), defining the CTA ability to detect a significant signal at short exposures. The resulting CTA differential flux sensitivity as a function of the observing time, obtained using the latest Monte Carlo simulations, is compared to the sensitivities of Fermi-LAT and current-generation IACTs obtained in the overlapping energy ranges., Comment: Proceedings of the 36th International Cosmic Ray Conference - Madison, WI, USA (PoS(ICRC2019)673)