A high-level analysis framework for HAWC
Patrick W. Younk, Robert J. Lauer, Giacomo Vianello, J. Patrick, Harding, Hugo Alberto Ayala Solares, Hao Zhou, and Michelle Hui (for the HAWC, Collaboration)

TL;DR
This paper introduces a modular, maximum likelihood-based analysis framework for HAWC data that enhances source modeling, detector calibration, and facilitates joint multi-observatory analyses.
Contribution
It presents a novel, flexible analysis framework integrated with 3ML, tailored for HAWC's unique data challenges and compatible with other observatories.
Findings
Framework enables optimized source and detector parameters.
Allows joint analysis with other observatories.
Facilitates handling of large, complex HAWC data sets.
Abstract
The High Altitude Water Cherenkov (HAWC) Observatory continuously observes gamma-rays between 100 GeV to 100 TeV in an instantaneous field of view of about 2 steradians above the array. The large amount of raw data, the importance of small number statistics, the large dynamic range of gamma-ray signals in time (1 - sec) and angular extent (0.1 - 100 degrees), and the growing need to directly compare results from different observatories pose some special challenges for the analysis of HAWC data. To address these needs, we have designed and implemented a modular analysis framework based on the method of maximum likelihood. The framework facilitates the calculation of a binned Poisson Log-likelihood value for a given physics model (i.e., source model), data set, and detector response. The parameters of the physics model (sky position, spectrum, angular extent, etc.) can be optimized…
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Taxonomy
TopicsAstrophysics and Cosmic Phenomena · Radiation Detection and Scintillator Technologies · Gamma-ray bursts and supernovae
