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arXiv · 2501.11865

A White Dwarf Binary Candidate Discovered by LAMOST Using Dynamical Method

Abstract

We present the discovery of a binary system containing a white dwarf candidate using data from the LAMOST. Our analysis of the radial velocity data allowed us to determine an orbital period of approximately 0.953 days and a mass function of 0.129 $M_\odot$. Through spectral energy distribution (SED) fitting, we obtained the stellar parameters of the visible star. By combining these results with the mass function, we established a relationship between the mass of the invisible star and the system's inclination angle, along with the Roche lobe radius. We find that the mass of the invisible star is below the Chandrasekhar limit when the inclination angle exceeds $35^\circ$. Given that systems with large variations in radial velocity typically have high inclination angles, we classify the invisible star as a white dwarf candidate. The Roche lobe radius exceeds the physical radius of the visible star, indicating that no mass transfer occurs, which results in a weak ellipsoidal modulation effect. Additionally, we obtained light curves from the TESS, ASAS-SN, and CRTS surveys. The light curves also exhibit a periodicity of approximately 0.95 days, with ellipsoidal modulation only in the 2019 TESS observations. Coupled with the strong $\rm H_{\alpha}$ emission line observed in the LAMOST MRS spectrum, we infer that the surface of the visible star contains significant hot spots. This obscures the system's inherently weak ellipsoidal modulation, resulting in a manifestation of rotational variables. Furthermore, an analysis of the dynamical characteristics of this system indicates that it has a high inclination angle ($>60$ degrees) and its orbital properties are consistent with those of typical thin disk stars, supporting the hypothesis that the invisible object is a white dwarf.

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BibTeXRIS

Haifan Zhu, Wei Wang, Xue Lib, Jia-jia Li, Pengfu Tian. 2025-01-21. A White Dwarf Binary Candidate Discovered by LAMOST Using Dynamical Method. https://arxiv.org/abs/2501.11865

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