The SkyLLH framework for IceCube point-source search

The IceCube Collaboration

Research output: Contribution to journalConference articlepeer-review


Hypothesis tests based on unbinned log-likelihood (LLH) functions are a common technique used in multi-messenger astronomy, including IceCube’s neutrino point-source searches. We present the general Python-based tool "SkyLLH", which provides a modular framework for implementing and executing log-likelihood functions to perform data analyses with multi-messenger astronomy data. Specific SkyLLH framework features for a new and improved time-integrated IceCube point-source analysis are highlighted, including the support for kernel density estimation (KDE) based probability density functions. In addition, the support for a variety of point-source analysis types, such as stacked and time-variable searches, will be presented.

Original languageEnglish (US)
Article number1073
JournalProceedings of Science
StatePublished - Mar 18 2022
Event37th International Cosmic Ray Conference, ICRC 2021 - Virtual, Berlin, Germany
Duration: Jul 12 2021Jul 23 2021

All Science Journal Classification (ASJC) codes

  • General


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