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Supernova remnants as PeVatron candidates : analysis and modeling of simulated data from the Cherenkov Telescope Array

Abstract : The origin of the knee in the cosmic-ray spectrum at PeV energies is still an open question. Due to their large budget, supernova remnants (SNRs) are plausible candidates for these so-called PeVatrons. The accelerated charged particles interact with surrounding matter, produce neutral pion particles which consequently decay into high-energy gamma rays. These gamma rays, that are in TeV energies for PeVatrons, can then be detected by Cherenkov telescopes or other gamma observations. In this thesis work, we study the potential of Cherenkov Telescope Array (CTA) to observe such gamma rays. After selecting potential galactic PeVatron candidates present in the simulated Data Challenge One (DC-1) of CTA, we reconstruct their spectral energy distribution (SED) by using ctools package. In case measured data in other wavelengths exist, we combine this to the simulated SEDs to perform Multi-Wavelength (MWL) analysis. The SEDs are then fitted by using different non-thermal radiative models, including hadronic pi0 component. For the modelling we use the Naima package. Several results are obtained. The spectral parameters are reconstructed in good agreement with parameters used in DC-1. Simulations giving confidence for the data analysis process. Some potential PeVatron candidates having hard energy spectra are found among the studied SNRs. It is also shown that the MWL data gives good constrain for SED modelling and allows to determine whether a hadronic component is present in the data. If the DC-1 data were representative of reality, we could rule out most of the sources. Possible improvements in the input spectral models to be simulated for the next Data Challenge of CTA are proposed.
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Ziwei Ou. Supernova remnants as PeVatron candidates : analysis and modeling of simulated data from the Cherenkov Telescope Array. High Energy Astrophysical Phenomena [astro-ph.HE]. Université Paris-Saclay, 2019. English. ⟨NNT : 2019SACLS421⟩. ⟨tel-02493037⟩

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