Analysis Framework for Multi-messenger Astronomy with IceCube
Kwok Lun Fan, John Evans, Michael Larson (for the IceCube, Collaboration)

TL;DR
This paper introduces i3mla, a Python package that simplifies the integration of IceCube neutrino data into multi-messenger astronomy analyses within the 3ML framework, enabling combined likelihood analyses across instruments.
Contribution
The paper presents a new Python-based unbinned-likelihood analysis tool, i3mla, compatible with 3ML, to facilitate multi-messenger analyses involving IceCube data.
Findings
Demonstrated how to use i3mla with 3ML for joint analyses.
Presented preliminary sensitivities with combined datasets.
Enabled integration of neutrino data into multi-messenger frameworks.
Abstract
Combining observational data from multiple instruments for multi-messenger astronomy can be challenging due to the complexity of the instrument response functions and likelihood calculation. We introduce a python-based unbinned-likelihood analysis package called i3mla (IceCube Maximum Likelihood Analysis). i3mla is designed to be compatible with the Multi-Mission Maximum Likelihood (3ML) framework, which enables multi-messenger astronomy analyses by combining the likelihood across different instruments. By making it possible to use IceCube data in the 3ML framework, we aim to facilitate the use of neutrino data in multi-messenger astronomy. In this work we illustrate how to use the i3mla package with 3ML and present preliminary sensitivities using the i3mla package and 3ML through a joint-fit with HAWC Public dataset.
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Taxonomy
TopicsAstrophysics and Cosmic Phenomena · Neutrino Physics Research
