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Gravitational Waves from Massive Black Hole Mergers in ASTRID: Predictions for LISA

Astrophysics of Galaxies 2025-11-11 v3

Abstract

We use the ASTRID cosmological simulation to forecast massive black hole (MBH) mergers detectable by Laser Interferometer Space Antenna (LISA) down to z=0z=0. ASTRID directly models MBH dynamical friction, allowing a realistic tracking of their trajectory. It also incorporates relatively low-mass MBH seeds down to 5×104M5\times10^{4} M_{\odot}, providing a more complete picture of LISA MBH mergers. We find that LISA MBH mergers initially have high eccentricities, peaking around e0=0.8e_0 = 0.8 across all redshifts. Accounting for this boosts the event rate from 5.6 yr1^{-1} (if circular orbits are assumed) to 10.5 yr1^{-1}. This enhancement is largely due to additional inspiral sources that will coalesce after LISA's observation, which constitute 46%46\% of detected events.This underscores the importance of LISA's sensitivity to the early inspiral phase, especially for eccentric binaries that emit gravitational waves across a wider frequency band. Most LISA events in ASTRID arise from MBH1056 MM_{\mathrm{BH}}\sim10^{5-6}\ M_\odot, low-redshift (z<2z<2) and low mass-ratio (q0.01q\sim0.01-0.10.1) mergers. Accounting for eccentricity broadens the detectable MBH mass range up to 109M10^{9} M_\odot and shifts the peak of detectable mergers to a lower redshift zpeak=0.8z_{\rm peak}=0.8. This implies that the most massive LISA events may also be PTA sources. We predict LISA events to be in various galaxy environments, including many low-mass satellite galaxies. The electromagnetic (EM) counterparts of most LISA sources have active galactic nuclei (AGN) luminosities Lbol>1042L_{\rm bol}>10^{42} erg s1^{-1}, albeit only 1%1\% with >1044>10^{44} erg s1^{-1}. The brightest AGN are those associated with the rare LISA/PTA events with MBH>108MM_{\rm BH}>10^{8} M_\odot.

Keywords

Cite

@article{arxiv.2503.24304,
  title  = {Gravitational Waves from Massive Black Hole Mergers in ASTRID: Predictions for LISA},
  author = {Bonny Y. Wang and Yihao Zhou and William Chen and Nianyi Chen and Tiziana Di Matteo and Rupert Croft and Simeon Bird and Yueying Ni},
  journal= {arXiv preprint arXiv:2503.24304},
  year   = {2025}
}

Comments

19 Pages, 12 Figures; Published in ApJ