A Systematic Search for Redback and Black Widow Candidates Based on the 4FGL-DR3 Unassociated Sources and the Zwicky Transient Facility Data
Abstract Spider pulsars represent a unique subclass of radio millisecond pulsars in binaries, and are further categorized into black widows and redbacks according to the mass of the low-mass companion. These pulsars, observable across multiple wavelengths, exhibit periodic variability in optical. The discovery and study of additional spider-type pulsars are crucial for a fuller understanding the evolution of binary stars in close orbits and the recycling theory of millisecond pulsars. In this work, we systematically searched for spider pulsar binary systems using time-domain variability data from the Zwicky Transient Facility and unassociated gamma-ray sources from the Fermi 4FGL-DR3 catalog. We developed a time-domain data processing pipeline that employs the Lomb–Scargle periodogram algorithm. As a result, we identified a total of 194 ellipsoidal variables and irradiation-type binary stars. Further refinement using the Gaia Hertzsprung–Russell diagram resulted in a selection of 24 spider pulsar candidates. Incorporating the 4FGL 95% confidence error ellipse reduced the sample to 19 candidates. An additional filter using the Gaia color-reduced proper motion diagram yielded nine “gold sample” candidates. These newly identified spider pulsar candidates will guide future observational campaigns in radio, X-ray, and optical spectroscopy, aiding in the comprehensive validation of their nature.
Authors
- W. J. Huang (ORCID: https://orcid.org/0000-0001-5546-8549)
- P. H. T. Tam (ORCID: https://orcid.org/0000-0002-1262-7375)
- Liangliang Ren (ORCID: https://orcid.org/0000-0002-1428-4003)
- Jiamao 佳茂 Lin 林
- Chunyan 春燕 Lu 卢
- Hewen 何文 Yang 杨
Publication Details
- Journal
- The Astrophysical Journal
- Published
- 2024-12-27
- DOI
- https://doi.org/10.3847/1538-4357/ad8e39
- Citations
- 4
- Primary Topic
- Gamma-ray bursts and supernovae
- Type
- article
- Field-Weighted Citation Impact
- 1.33
Funders
- National Natural Science Foundation of China