Identification of New Candidate Be/X-Ray Binary Systems in the Small Magellanic Cloud via Analysis of the S-CUBED Source Catalog
It has long been known that a large population of Be/X-ray binaries (BeXRBs) exists in the Milky Way’s neighboring dwarf galaxy, the Small Magellanic Cloud (SMC), due to a recent period of intense star formation. Since 2016, efforts have been made to monitor this population and identify new BeXRBs t...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2025-01-01
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| Series: | The Astrophysical Journal |
| Subjects: | |
| Online Access: | https://doi.org/10.3847/1538-4357/addfd1 |
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| Summary: | It has long been known that a large population of Be/X-ray binaries (BeXRBs) exists in the Milky Way’s neighboring dwarf galaxy, the Small Magellanic Cloud (SMC), due to a recent period of intense star formation. Since 2016, efforts have been made to monitor this population and identify new BeXRBs through the Swift SMC Survey (S-CUBED). S-CUBED’s weekly observation cadence has identified many new BeXRBs that exist within the SMC, but evidence suggests that more systems exist that have thus far escaped detection. A major challenge in identifying new BeXRBs is their transient nature at high-energy wavelengths, which prevents them from being detected via their X-ray emission characteristics when not in outburst. In order to identify sources that may have been missed owing to a long period of quiescence, it becomes necessary to devise methods of detection that rely on wavelengths at which BeXRBs are more persistent emitters. In this work, we attempt to use archival analysis of infrared, optical, and ultraviolet observations to identify new candidate BeXRBs that have been overlooked within the S-CUBED source catalog. Using X-ray/optical selection of source properties, unsupervised clustering, spectral energy distribution fitting to VizieR archival measurements, and ultraviolet light-curve analysis, we are able to identify six new candidate BeXRB systems that otherwise would have been missed by automated analysis pipelines. Using these results, we demonstrate the use of ultraviolet through near-infrared observational data in identifying candidate BeXRBs when they cannot be identified using their X-ray emission. |
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| ISSN: | 1538-4357 |