Identification of New Candidate Be/X-Ray Binary Systems in the Small Magellanic Cloud via Analysis of S-CUBED Source Catalog

TL;DR

This study develops a multi-wavelength archival analysis method to identify new candidate Be/X-ray binary systems in the Small Magellanic Cloud, overcoming detection challenges due to their transient X-ray emission.

Contribution

It introduces a novel approach combining infrared, optical, and ultraviolet data with clustering and SED-fitting to find BeXRB candidates missed by traditional X-ray surveys.

Findings

Identified six new candidate BeXRB systems.

Demonstrated effectiveness of ultraviolet to near-infrared data in detection.

Showed that archival multi-wavelength analysis can supplement X-ray surveys.

Abstract

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 thusfar 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 due 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, SED-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.