Machine-Learned Dark Matter Subhalo Candidates in the 4FGL-DR2: Search for the Perturber of the GD-1 Stream
| dc.contributor.author | Mirabal, Nestor | |
| dc.contributor.author | Bonaca, Ana | |
| dc.date.accessioned | 2021-09-08T16:51:42Z | |
| dc.date.available | 2021-09-08T16:51:42Z | |
| dc.date.issued | 2021-11-15 | |
| dc.description.abstract | The detection of dark matter subhalos without a stellar component in the Galactic halo remains a challenge. We use supervised machine learning to identify high-latitude gamma-ray sources with dark matter-like spectra among unassociated gamma-ray sources in the 4FGL-DR2. Out of 843 4FGL-DR2 unassociated sources at |b|≥10∘, we select 73 dark matter subhalo candidates. Of the 69 covered by the Neil Gehrels Swift Observatory (Swift), 17 show at least one X-ray source within the 95% LAT error ellipse and 52 where we identify no new sources. This latest inventory of dark subhalos candidates allows us to investigate the possible dark matter substructure responsible for the perturbation in the GD-1 stellar stream. In particular, we examine the possibility that the alleged GD-1 dark subhalo may appear as a 4FGL-DR2 gamma-ray source from dark matter annihilation into Standard Model particles. | en_US |
| dc.description.sponsorship | The material is based upon work supported by NASA under award number 80GSFC21M0002. This research has made use of data obtained through the High Energy Astrophysics Science Archive Research Center Online Service, provided by the NASA/Goddard Space Flight Center. This work made use of data supplied by the UK Swift Science Data Centre at the University of Leicester. We acknowledge valuable conversations with Javier Coronado-Blázquez. We thank Miguel Ángel Sánchez-Conde for providing many helpful comments on the entire manuscript. AB acknowledges support from NASA through HST grant HST-GO-15930. | en_US |
| dc.description.uri | https://iopscience.iop.org/article/10.1088/1475-7516/2021/11/033/meta | en_US |
| dc.format.extent | 17 pages | en_US |
| dc.genre | journal articles | en_US |
| dc.genre | preprints | en_US |
| dc.identifier | doi:10.13016/m2zpxi-zwir | |
| dc.identifier.citation | Mirabal, Nestor and Bonaca, Ana." Machine-Learned Dark Matter Subhalo Candidates in the 4FGL-DR2: Search for the Perturber of the GD-1 Stream." Journal of Cosmology and Astroparticle Physics, vol 2021 (15 November 2021). https://doi.org/10.1088/1475-7516/2021/11/033 | en_US |
| dc.identifier.uri | http://hdl.handle.net/11603/22966 | |
| dc.identifier.uri | https://doi.org/10.1088/1475-7516/2021/11/033 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | IOP Publishing | en_US |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Center for Space Sciences and Technology | |
| dc.relation.ispartof | UMBC Faculty Collection | |
| dc.relation.ispartof | UMBC Physics Department | |
| dc.rights | This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. | en_US |
| dc.title | Machine-Learned Dark Matter Subhalo Candidates in the 4FGL-DR2: Search for the Perturber of the GD-1 Stream | en_US |
| dc.type | Text | en_US |