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[ascl:2201.008] fermi-gce-flows: Infer the Galactic Center gamma-ray excess

fermi-gce-flows uses a machine learning-based technique to characterize the contribution of modeled components, including unresolved point sources, to the GCE. It can perform posterior parameter estimation while accounting for pixel-to-pixel spatial correlations in the gamma-ray map. On application to Fermi data, the method generically attributes a smaller fraction of the GCE flux to unresolved point source-like emission when compared to traditional approaches.

Code site:
https://github.com/smsharma/fermi-gce-flows
Described in:
https://ui.adsabs.harvard.edu/abs/2021arXiv211006931M
Bibcode:
2022ascl.soft01008M
Preferred citation method:

Please see citation information at https://github.com/smsharma/fermi-gce-flows


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ascl:2201.008
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