Investigating the neutrino emission of candidate neutrino-emitter blazars with the IceCubePy likelihood framework

Active galactic nuclei are promising candidates for astrophysical neutrino sources, as suggested by the detection of a high-energy neutrino positionally consistent with the flaring blazar TXS 0506+056 and evidence of neutrino emission from the nearby Seyfert galaxy NGC 1068. Our recent studies based on the IceCube time-integrated sky maps provided evidence of a statistically significant correlation between blazars and “hotspots” in the neutrino sky as seen by the IceCube Neutrino Observatory. A small subset of blazars, appearing as promising candidate neutrino point sources, has been highlighted. The neutrino emission properties of these blazars remain largely unexplored. The IceCube Collaboration has publicly released a 10-year muon-track dataset; however, publicly available analysis tools for these data are currently limited. In this contribution, we introduce IceCubePy, an unbinned maximum likelihood framework designed for the analysis of the public data from the IceCube Neutrino Observatory. We present the analysis performance of IceCubePy, finding general agreement with results published by the IceCube Collaboration. This demonstrates that the software has reached an adequate level of maturity and reliability suitable for scientific analyses.