Scientific article
OA Policy
English

Investigating the Lower Mass Gap with Low-mass X-Ray Binary Population Synthesis

Published inThe Astrophysical journal, vol. 954, no. 2, 212
Publication date2023-09-01
First online date2023-09-08
Abstract

Mass measurements from low-mass black hole X-ray binaries (LMXBs) and radio pulsars have been used to identify a gap between the most massive neutron stars (NSs) and the least massive black holes (BHs). BH mass measurements in LMXBs are typically only possible for transient systems: outburst periods enable detection via all-sky X-ray monitors, while quiescent periods enable radial velocity measurements of the low-mass donor. We quantitatively study selection biases due to the requirement of transient behavior for BH mass measurements. Using rapid population synthesis simulations ( COSMIC ), detailed binary stellar-evolution models ( MESA ), and the disk instability model of transient behavior, we demonstrate that transient LMXB selection effects introduce observational biases, and can suppress mass-gap BHs in the observed sample. However, we find a population of transient LMXBs with mass-gap BHs form through accretion-induced collapse of an NS during the LMXB phase, which is inconsistent with observations. These results are robust against variations of binary evolution prescriptions. The significance of this accretion-induced collapse population depends upon the maximum NS birth mass M NS , birth − max . To reflect the observed dearth of low-mass BHs, COSMIC and MESA models favor M NS , birth − max ≲ 2 M ⊙ . In the absence of further observational biases against LMXBs with mass-gap BHs, our results indicate the need for additional physics connected to the modeling of LMXB formation and evolution.

Funding
  • Gordon and Betty Moore Foundation [GBMF8477]
  • National Science Foundation - REU Site: Preparing a Diverse Workforce through Interdisciplinary Astrophysics Research [1757792]
Citation (ISO format)
SIEGEL, Jared C. et al. Investigating the Lower Mass Gap with Low-mass X-Ray Binary Population Synthesis. In: The Astrophysical journal, 2023, vol. 954, n° 2, p. 212. doi: 10.3847/1538-4357/ace9d9
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Article (Published version)
Identifiers
Journal ISSN0004-637X
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