Pourvu:
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The origin of cosmic rays represents a major missing block in our understanding of the Universe. The main challenge we face is that, being charged, they are deviated in their journey from their natural accelerator to the Earth. There is however an indirect way to study their acceleration sites: wherever a cosmic ray is accelerated to high energies, it unavoidably interacts with its environment, leading to the production of photons and neutrinos. These by-products can travel along geodesics and can thus directly point to the loci of particle acceleration in the Universe. While photon observations alone are often ambiguous, neutrinos represent a true smoking-gun for cosmic ray acceleration in astrophysical objects. This indirect window on natural particle accelerators has been opened at last with the development of neutrino astronomy and the first multi-messenger observing campaigns. We have now collected several evidences (at the 3 to 4-sigma levels) for neutrino emission from active galactic nuclei, the observational effect of accretion onto super-massive black-holes, but we still lack unambiguous detections above 5-sigmas. The next-generation gamma-ray and neutrino telescopes are already under construction: they will drastically improve our observing capabilities, allowing us to fully enter into the multi-messenger era.
The PhD candidate will join the ANR-funded research project COCOA-NuGETs (COnstraints on COsmic-ray Acceleration by Neutrino and Gamma-ray observations of Extragalactic TargetS, see https://anr.fr/fr/rechercher-sur-anrfr/?q=COCOA+NuGETs&id=1817&L=0), that builds up and expands on these early multi-messenger results and paves the way for the early science of the Cherenkov Telescope Array Observatory (CTAO). This thesis is focused on developing and applying novel analysis methodologies that leverage the combined power of gamma-ray and neutrino observations to pinpoint cosmic-ray acceleration sites in the Universe. The PhD candidate will work on two complementary fronts:
on one side, they will contribute to the implementation of advanced multi-wavelength and multi-messenger fitting algorithms within the Gammapy software framework, enabling the joint analysis and modeling of gamma-ray and neutrino data. This will provide a robust platform for interpreting observations in a unified astrophysical context, and produce statistically sound constraints on the model parameters, and hence on the physical properties of the cosmic-ray accelerators;
on the other they will analyze the first data delivered by the northern array of CTAO to identify and characterize neutrino-emitting black-hole systems by applying the tools developed in the first part;
The PhD candidate will join the ANR-funded research project COCOA-NuGETs (COnstraints on COsmic-ray Acceleration by Neutrino and Gamma-ray observations of Extragalactic TargetS, see https://anr.fr/fr/rechercher-sur-anrfr/?q=COCOA+NuGETs&id=1817&L=0), that builds up and expands on these early multi-messenger results and paves the way for the early science of the Cherenkov Telescope Array Observatory (CTAO). This thesis is focused on developing and applying novel analysis methodologies that leverage the combined power of gamma-ray and neutrino observations to pinpoint cosmic-ray acceleration sites in the Universe. The PhD candidate will work on two complementary fronts:
on one side, they will contribute to the implementation of advanced multi-wavelength and multi-messenger fitting algorithms within the Gammapy software framework, enabling the joint analysis and modeling of gamma-ray and neutrino data. This will provide a robust platform for interpreting observations in a unified astrophysical context, and produce statistically sound constraints on the model parameters, and hence on the physical properties of the cosmic-ray accelerators;
on the other they will analyze the first data delivered by the northern array of CTAO to identify and characterize neutrino-emitting black-hole systems by applying the tools developed in the first part;
Responsable:
Matteo Cerruti
Services/Groupes:
Année:
2025
Formations:
Thèse