Abstract
The Cherenkov Telescope Array (CTA) is the next-generation ground-based very-high-energy gamma-ray observatory. By using three types of telescopes CTA can cover a wide energy range (20 ...GeV–300 TeV) with an order of magnitude higher sensitivity than the current telescopes. The Large-Sized Telescope (LST) is designed to detect 20 GeV–1 TeV gamma rays thanks to the large light collection area, sensitive photosensors, a fast trigger system, and readout electronics. The camera readout system must have a high signal-to-noise ratio and a linear signal sampling with a large dynamic range in order to efficiently detect dim and low-energy atmospheric showers. To meet this requirement we use the Domino Ring Sampler version 4 (DRS4), which also enables ultra-fast sampling with low power consumption. Some of the intrinsic characteristics of DRS4 chips require software corrections. These procedures lower the effect of non-Gaussian noise contribution and improve the timing resolution of the system. In this contribution we discuss the calibration algorithms and the resulting performance.
Context.
Modelling the broadband emission of jetted active galactic nuclei (AGN) constitutes one of the main research topics of extragalactic astrophysics in the multi-wavelength and multi-messenger ...domain.
Aims.
We present
agnpy
, an open-source python package modelling the radiative processes of relativistic particles accelerated in the jets of AGN. The package includes classes describing the galaxy components responsible for line and thermal emission and it calculates the absorption due to
γ
γ
pair production on several photon fields.
agnpy
aims to extend the effort of modelling and interpreting the emission of extragalactic sources to a wide number of astrophysicists.
Methods.
We present the package content and illustrate a few examples of applications of its functionalities. We validate the software by comparing its results against the literature and against other open-source software.
Results.
We illustrate the utility of
agnpy
in addressing the most common questions encountered while modelling the emission of jetted active galaxies. When comparing its results against the literature and other modelling tools adopting the same physical assumptions, we achieve an agreement within 10 − 30%.
Conclusions.
agnpy
represents one of the first systematic and validated collection of established radiative processes for jetted active galaxies in an open-source python package. We hope it will also stand among the first endeavours providing reproducible and transparent astrophysical software not only for data reduction and analysis, but also for modelling and interpretation.
Context. Diffusive shock acceleration (DSA) is the most promising mechanism that accelerates Galactic cosmic rays (CRs) in the shocks of supernova remnants (SNRs). It is based on particles scattering ...caused by turbulence ahead and behind the shock. The turbulence upstream is supposedly generated by the CRs, but this process is not well understood. The dominant mechanism may depend on the evolutionary state of the shock and can be studied via the CRs escaping upstream into the interstellar medium (ISM). Aims. Previous observations of the γ Cygni SNR showed a difference in morphology between GeV and TeV energies. Since this SNR has the right age and is at the evolutionary stage for a significant fraction of CRs to escape, our aim is to understand γ-ray emission in the vicinity of the γ Cygni SNR. Methods. We observed the region of the γ Cygni SNR with the MAGIC Imaging Atmospheric Cherenkov telescopes between 2015 May and 2017 September recording 87 h of good-quality data. Additionally, we analysed Fermi-LAT data to study the energy dependence of the morphology as well as the energy spectrum in the GeV to TeV range. The energy spectra and morphology were compared against theoretical predictions, which include a detailed derivation of the CR escape process and their γ-ray generation. Results. The MAGIC and Fermi-LAT data allowed us to identify three emission regions that can be associated with the SNR and that dominate at different energies. Our hadronic emission model accounts well for the morphology and energy spectrum of all source components. It constrains the time-dependence of the maximum energy of the CRs at the shock, the time-dependence of the level of turbulence, and the diffusion coefficient immediately outside the SNR shock. While in agreement with the standard picture of DSA, the time-dependence of the maximum energy was found to be steeper than predicted, and the level of turbulence was found to change over the lifetime of the SNR.
Modelling the broadband emission of jetted active galactic nuclei (AGN) constitutes one of the main research topics of extragalactic astrophysics in the multi-wavelength and multi-messenger domain. ...We present agnpy, an open-source python package modelling the radiative processes of relativistic particles accelerated in the jets of active galactic nuclei. The package includes classes describing the galaxy components responsible for line and thermal emission and calculates the absorption due to \(\gamma\gamma\) pair production on several photon fields. agnpy aims at extending the effort of modelling and interpreting the emission of extragalactic sources to a wide number of astrophysicists. We present the package content and illustrate a few examples of applications of its functionalities. We validate the software by comparing its results against the literature and against other open-source software. We illustrate the utility of agnpy in addressing the most common questions encountered while modelling the emission of jetted active galaxies. When comparing its results against the literature and other modelling tools adopting the same physical assumptions, we achieve an agreement within \(10-30\%\). agnpy represents one of the first systematic and validated collection of established radiative processes for jetted active galaxies in an open-source python package. We hope it will stand also among the first endeavours providing reproducible and transparent astrophysical software not only for data reduction and analysis, but also for modelling and interpretation.
A&A 670, A8 (2023) Context. Diffusive shock acceleration (DSA) is the most promising mechanism
to accelerate Galactic cosmic rays (CRs) in the shocks of supernova remnants
(SNRs). The turbulence ...upstream is supposedly generated by the CRs, but this
process is not well understood. The dominant mechanism may depend on the
evolutionary state of the shock and can be studied via the CRs escaping
upstream into the interstellar medium (ISM). Aims. Previous observations of the
$\gamma$-Cygni SNR showed a difference in morphology between GeV and TeV
energies. Since this SNR has the right age and is at the evolutionary stage for
a significant fraction of CRs to escape, we aim to understand $\gamma$-ray
emission in the vicinity of the $\gamma$-Cygni SNR. Methods. We observed the
region of the $\gamma$-Cygni SNR with the MAGIC Imaging Atmospheric Cherenkov
telescopes between May 2015 and September 2017 recording 87 h of good-quality
data. Additionally we analysed Fermi-LAT data to study the energy dependence of
the morphology as well as the energy spectrum in the GeV to TeV range. The
energy spectra and morphology were compared against theoretical predictions,
which include a detailed derivation of the CR escape process and their
$\gamma$-ray generation. Results. The MAGIC and Fermi-LAT data allowed us to
identify three emission regions, which can be associated with the SNR and
dominate at different energies. Our hadronic emission model accounts well for
the morphology and energy spectrum of all source components. It constrains the
time-dependence of the maximum energy of the CRs at the shock, the
time-dependence of the level of turbulence, and the diffusion coefficient
immediately outside the SNR shock. While in agreement with the standard picture
of DSA, the time-dependence of the maximum energy was found to be steeper than
predicted and the level of turbulence was found to change over the lifetime of
the SNR.
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