SciPost Submission Page
Dark matter or millisecond pulsars? A deep learning-based analysis of the Fermi Galactic Centre Excess
by Florian List, Nicholas L. Rodd, Geraint F. Lewis
Submission summary
| Authors (as registered SciPost users): | Florian List |
| Submission information | |
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| Preprint Link: | scipost_202209_00003v1 (pdf) |
| Code repository: | https://github.com/FloList/GCE_NN |
| Date accepted: | Nov. 28, 2022 |
| Date submitted: | Sept. 1, 2022, 10:16 p.m. |
| Submitted by: | Florian List |
| Submitted to: | SciPost Physics Proceedings |
| Proceedings issue: | 14th International Conference on Identification of Dark Matter (IDM2022) |
| Ontological classification | |
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| Academic field: | Physics |
| Specialties: |
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| Approaches: | Computational, Phenomenological |
Abstract
The $\gamma$-ray Galactic Centre Excess (GCE) remains one of the few observed high-energy signals for which a dark matter (DM) origin is a plausible explanation. We present a deep learning-based analysis of the $\gamma$-ray sky in the Galactic Centre region, carefully accounting for the mathematical degeneracy between faint point-sources (PSs) such as millisecond pulsars (MSPs) and DM-like Poisson emission. Using recent models for the Galactic foregrounds, we find that relatively few bright PSs just below \textit{Fermi}'s detection threshold seem unlikely to explain the GCE, although we continue to find evidence for PSs. Looking ahead, further improvements in the modelling of the $\gamma$-ray sky will be crucial for distinguishing between a DM-like and point-like morphology of the signal.
Published as SciPost Phys. Proc. 12, 034 (2023)
Reports on this Submission
Report #1 by Anonymous (Referee 1) on 2022-10-21 (Invited Report)
- Cite as: Anonymous, Report on arXiv:scipost_202209_00003v1, delivered 2022-10-21, doi: 10.21468/SciPost.Report.5947
Strengths
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This study tries to study the puzzling origin of Galactic center gamma excess with convolutional neural networks. This is a novel method and definitely will lead to some interesting understandings of the problem.
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The manuscript provides a nice summary of their method, as well as potential extensions to improve it in the future.
Weaknesses
Report
Requested changes
None.
