Pourvu:
Oui
The origin of cosmic rays (CRs) with up to 10^20 eV energies is one of the most important questions in astrophysics to date. One way to track down CR sources and study CR propagation is to look for the products of cosmic ray interactions interactions, in particular high-energy (TeV-PeV) neutrinos. These neutrinos, indeed, are characteristic of hadronic interactions and thus would be an unambiguous signature of the presence of cosmic rays. Moreover, since neutrino trajectories are not deflected, their detection would allow locating CR interaction sites. During the past two years, the discovery by IceCube of neutrinos emitted from the NGC1068 galaxy and from the galactic plane has demonstrated the capability of current and upcoming experiments to not identify astrophysical neutrinos but also to discover and study specific sources, thereby opening a new research program in astrophysics. A key component of this program will be the KM3NeT experiment.
KM3NeT is a water Cherenkov detector composed of two large-scale arrays, ARCA and ORCA, which are both under construction and taking data in the Mediterranean Sea. Currently, around 12% of the detector is in place, and the completion date is set to 2027. It is therefore expected that the PhD students enrolled in the project will have access to the data associated with partial configurations of the experiment, in addition to sensitivity estimates related to the full expected detector. One key asset of KM3NeT, once completed, is its unprecedented angular resolution, which could allow not only precisely locating individual neutrino sources but also studying their substructure. This excellent resolution will be particularly important when studying neutrinos emitted within our Galaxy. Indeed, neutrinos produced within the Milky Way, first observed by IceCube in 2023, could be produced both by the interactions of CRs trapped in our Galaxy with the ambient medium (diffuse emission) and by interactions occurring near galactic CR sources. Galactic high-energy neutrinos could in fact be produced by a wide range of objects such as circumstellar Core-Collapse Supernovae (transient emission), Supernova remnants, or Pulsar Wind Nebulae. Identifying and studying these sources will be a major endeavour of KM3NeT.
The goal of the PhD is to study KM3NeT’s performance, and evaluate its projected sensitivity, for identifying the origin of neutrinos produced in our Galaxy. To this end, the student will use both data (for existing configurations), and simulations of the completed detector. When nearing the completion of their PhD, it is possible that the student will be able to apply their analysis frameworks to the first data from the final configuration of KM3NeT, possibly combined with the full ANTARES dataset (precursor of KM3NeT). The results of the analyses performed during the PhD will lead to one or several publication(s) reporting KM3NeT's discoveries or constraints on given source populations. The position will be based at APC and will be co-supervised by Dr. Sonia El Hedri and Pr. Antoine Kouchner.
The KM3NeT group at APC had been playing a leading role in searches for high-energy neutrinos at the ANTARES experiment as well as in the search for low-energy supernova neutrinos at KM3NeT. As part of the KM3NeT collaboration, the candidate will participate in collaboration meetings (travelling 3-4 times per year), and take part in the data processing, detector monitoring, and maintenance activities. Some experience with Python programming (optionally also C++) and with data analysis would be highly appreciated.
KM3NeT is a water Cherenkov detector composed of two large-scale arrays, ARCA and ORCA, which are both under construction and taking data in the Mediterranean Sea. Currently, around 12% of the detector is in place, and the completion date is set to 2027. It is therefore expected that the PhD students enrolled in the project will have access to the data associated with partial configurations of the experiment, in addition to sensitivity estimates related to the full expected detector. One key asset of KM3NeT, once completed, is its unprecedented angular resolution, which could allow not only precisely locating individual neutrino sources but also studying their substructure. This excellent resolution will be particularly important when studying neutrinos emitted within our Galaxy. Indeed, neutrinos produced within the Milky Way, first observed by IceCube in 2023, could be produced both by the interactions of CRs trapped in our Galaxy with the ambient medium (diffuse emission) and by interactions occurring near galactic CR sources. Galactic high-energy neutrinos could in fact be produced by a wide range of objects such as circumstellar Core-Collapse Supernovae (transient emission), Supernova remnants, or Pulsar Wind Nebulae. Identifying and studying these sources will be a major endeavour of KM3NeT.
The goal of the PhD is to study KM3NeT’s performance, and evaluate its projected sensitivity, for identifying the origin of neutrinos produced in our Galaxy. To this end, the student will use both data (for existing configurations), and simulations of the completed detector. When nearing the completion of their PhD, it is possible that the student will be able to apply their analysis frameworks to the first data from the final configuration of KM3NeT, possibly combined with the full ANTARES dataset (precursor of KM3NeT). The results of the analyses performed during the PhD will lead to one or several publication(s) reporting KM3NeT's discoveries or constraints on given source populations. The position will be based at APC and will be co-supervised by Dr. Sonia El Hedri and Pr. Antoine Kouchner.
The KM3NeT group at APC had been playing a leading role in searches for high-energy neutrinos at the ANTARES experiment as well as in the search for low-energy supernova neutrinos at KM3NeT. As part of the KM3NeT collaboration, the candidate will participate in collaboration meetings (travelling 3-4 times per year), and take part in the data processing, detector monitoring, and maintenance activities. Some experience with Python programming (optionally also C++) and with data analysis would be highly appreciated.
Responsable:
Antoine Kouchner et Sonia El Hedri
Services/Groupes:
Année:
2024
Formations:
Thèse