English

A simulation study on the sub-threshold joint gravitational wave-electromagnetic wave observation on binary neutron star mergers

High Energy Astrophysical Phenomena 2024-10-01 v1 Cosmology and Nongalactic Astrophysics

Abstract

The coalescence of binary neutron stars (BNS) is a prolific source of gravitational waves (GWs) and electromagnetic (EM) radiation, offering a dual observational window into the Universe. Lowering the signal-to-noise ratio (S/N) threshold is a simple and cost-effective way to enhance the detection probability of GWs from BNS mergers. In this study, we introduce a metric of the purity of joint GW and EM detections PjointP_{\rm joint}, which is in analogue to PastroP_{\rm astro} in GW only observations. By simulating BNS merger GWs jointly detected by the HLV network and EM counterparts (kilonovae and short Gamma-ray bursts, sGRBs) with an assumed merger rate density of BNS, we generate catalogs of GW events and EM counterparts. Through this simulation, we analyze joint detection pairs, both correct and misidentified. We find the following: 1. For kilonovae, requiring Pjoint>P_{\rm joint}> 95\% instead of Pastro>95%P_{\rm astro}>95\% reduces the S/N from 9.2 to 8.5-8.8, allowing 5-13 additional joint detections per year and increasing the GW detection volume by 9-17\%; 2. For sGRBs, requiring Pjoint>P_{\rm joint}> 95\% instead of PastroP_{\rm astro} reduces the S/N from 9.2 to 8.1-8.5; 3. Increasing kilonova or sGRB detection capability does not improve PjointP_{\rm joint} due to a higher rate of misidentifications. We also show that sub-threshold GW and kilonova detections can reduce the uncertainty in measuring the Hubble constant to 89-92\% of its original value, and sub-threshold GW and sGRB observations can enhance the precision of constraining the speed of GWs to 88\% of previously established values.

Keywords

Cite

@article{arxiv.2409.19295,
  title  = {A simulation study on the sub-threshold joint gravitational wave-electromagnetic wave observation on binary neutron star mergers},
  author = {Yun-Fei Du and Emre Seyit Yorgancioglu and Jin-Hui Rao and Ankit Kumar and Shu-Xu Yi and Shuang-Nan Zhang and Shu Zhang},
  journal= {arXiv preprint arXiv:2409.19295},
  year   = {2024}
}

Comments

Accepted for publication in MNRAS, 8 pages, 7 figures

R2 v1 2026-06-28T19:00:26.891Z