Published June 20, 2025 | Published
Journal Article Open

Echoes from beyond: Detecting gravitational-wave quantum imprints with LISA

  • 1. ROR icon Cornell University
  • 2. ROR icon Heidelberg University
  • 3. ROR icon KU Leuven
  • 4. ROR icon Perimeter Institute
  • 5. ROR icon California Institute of Technology

Abstract

We revisit gravitational wave echoes as a pathway to measuring quantization effects of black hole horizons. In particular, we construct a robust and phenomenologically motivated toy model for black hole reflectivity, enabling us to estimate the detectability of waveform echoes in gravitational wave interferometer data. We demonstrate how the frequency information of echoes, upon detection, can be leveraged to probe and constrain the quantum scale associated with the underlying theory of quantum gravity. Our analysis shows that echoes may manifest in LISA data with an estimated signal-to-noise ratio of up to . For such signals, the frequency features indicative of horizon quantization can be determined with subpercent precision.

Copyright and License

 © 2025 American Physical Society.

Acknowledgement

The authors wish to thank Doğa Veske for productive discussion and the LISA Simulation Working Group and LISA Simulation Expert Group for the lively discussions on all simulation-related activities. L. H. would like to acknowledge financial support from the European Research Council (ERC) under the European Unions Horizon 2020 research and innovation programme Grant Agreement No. 801781. L. H. further acknowledges support from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy EXC 2181/1-390900948 (the Heidelberg STRUCTURES Excellence Cluster). The authors thank the Heidelberg STRUCTURES Excellence Cluster for financial support and acknowledge support by the state of Baden-Württemberg, Germany, through bwHPC. Research at Perimeter Institute is supported in part by the Government of Canada through the Department of Innovation, Science and Economic Development and by the Province of Ontario through the Ministry of Colleges and Universities. This material is based upon work supported by the National Science Foundation under Grants No. PHY-2407742, No. PHY- 2207342, and No. OAC-2209655 at Cornell. This work was supported by the Sherman Fairchild Foundation at Cornell. This work was supported in part by the Sherman Fairchild Foundation and by NSF Grants No. PHY-2309211, No. PHY-2309231, and No. OAC-2209656 at Caltech.

Data Availability

The data that support the findings of this article are openly available [77].

Additional Information

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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Additional details

Created:
July 2, 2025
Modified:
July 2, 2025