Search for Sub-Solar Mass Binaries in the First and Second Part of LIGO's Fourth Observing Run O4a-O4b
Year: 2026
Type: preprint
Abstract: The observation of sub-solar mass neutron stars and black holes would signify a new class of astrophysical objects since these systems are not expected to form via standard stellar evolution. We present the first sub-solar mass search for binaries consisting of neutron star or black holes that uses the data from both the second part (O4b) and first part (O4a) of the fourth observing run of the Advanced LIGO detectors. The search covers primary masses 0.1 to 2 $M_\odot$ and secondary masses 0.1 to 1 $M_\odot$. Tidal effects up to $7\times10^5$ are accounted for in extremely low-mass neutron stars. No statistically significant candidates are identified. We place a $90\%$ confidence upper limit on the merger rate $\mathcal{R}_{90}$ for sub-solar mass black holes and neutron stars to be $< 5.2\times10^{2}\,\textrm{Gpc}^{-3}\,\textrm{yr}^{-1}$ for a chirp mass of 0.5 $M_\odot$, a factor $2.2 \times$ lower compared to previous O1-O4a searches. We constrain the effective local dark matter fraction to be $\tilde{f}_\textrm{PBH}<0.6\%$ for $M_{\textrm{PBH}}=0.8 \,M_\odot$, approximately $1.5$ factor improvement to previous O1-O4a constraints. Given our model assumptions, our local dark matter fraction constraints are $2-7$ times lower than the OGLE microlensing survey for $M_{\textrm{PBH}}\ge{0.6}~M_\odot$.
Source: arXiv (Cornell University)
Institution: Syracuse University
Language: English
Subfield: Astronomy and Astrophysics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
Awards: Partnership to Advance Throughput Computing (PATh), G4265142103, Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP), Gravitational-Wave Astronomy and Astrophysics at Syracuse University, CC-NIE Networking Infrastructure: Enhancing the OrangeGrid - Upgrading the Syracuse Campus Network to Enable High Throughput Research Computing
OpenAlex ID: W7221910813