Speaker
Description
The High Altitude Water Cherenkov (HAWC) observatory surveys the very-high-energy sky in the energy range between 300 GeV and >100 TeV. Its wide field of view makes it particularly suitable for studying large, extended regions of emission that often contain multiple point and diffuse sources of gamma rays. Existing blind search methods to detect sources in HAWC data use a computationally expensive, iterative source fitting algorithm that can take several days to scan a few degree region in the sky. In this work, we adopt a new approach to speed up the identification of sources using an image processing pipeline. Using a blob finder algorithm, based on the Determinant of a Gaussian algorithm, this pipeline seeds sources accurately up to 300 times faster than the current HAWC source search pipeline. The pipelines output are then passed onto a global multi-threaded likelihood fitter for accurate source localization. We present the improved performance and sensitivity studies of the pipeline and discuss prospects for future applications on other astrophysical datasets.
| Collaboration(s) | HAWC Collaboration |
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