K.H.B. acknowledges and appreciates support from NSF NRT-2125764. M.M. acknowledges financial support from the European Research Council for the ERC Consolidator grant DEMOBLACK, under contract No. 770017 (PI: Mapelli) and from the German Excellence Strategy via the Heidelberg Cluster of Excellence (EXC 2181-390900948) STRUCTURES. This work used the resources provided by the Vanderbilt Advanced Computing Center for Research and Education (ACCRE), a collaboratory operated by and for Vanderbilt faculty at Vanderbilt University.
A Sea of Black Holes: Characterizing the LISA Signature for Stellar-origin Black Hole Binaries
Abstract
Observations by the LIGO, Virgo, and KAGRA (LVK) detectors have provided new insights into the demographics of stellar-origin black hole binaries (sBHBs). A few years before gravitational-wave signals from sBHB mergers are recorded in the LVK detectors, their early coalescence will leave a unique signature in the ESA/NASA mission Laser Interferometer Space Antenna (LISA). Multiband observations of sBHB sources between the LISA and LVK detectors opens an unprecedented opportunity to investigate the astrophysical environment and multimessenger early alerts. In this study, we report the sBHB sources that are expected to be present in the LISA data derived directly from the hydrodynamic cosmological simulation Illustris. By surveying snapshots across cosmological volume, metallicity, and lookback time, we calculate the expected sBHBs present in the LISA data for various combinations of mission lifetimes and stellar population models. For stellar population estimates consistent with the LVK rates, we find that only 10 sBHBs across the Illustris snapshots would be detected with significant confidence for a 10 yr LISA mission, while a 4 yr LISA mission would detect only ∼1 sBHB. Our work paves the way for creating LISA mock data and benchmarking LISA detection pipelines directly using cosmological simulations.
Copyright and License
© 2025. The Author(s). Published by the American Astronomical Society.
Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
Acknowledgement
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Additional details
- National Science Foundation
- NRT-2125764
- European Research Council
- DEMOBLACK 770017
- Deutsche Forschungsgemeinschaft
- Heidelberg Cluster of Excellence EXC 2181-390900948
- Accepted
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2025-01-21Accepted
- Available
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2025-02-24Published
- Caltech groups
- TAPIR
- Publication Status
- Published