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arxiv 2408.05290 v1 pith:YVBBCJ6L submitted 2024-08-09 astro-ph.CO

Probing the nature of dark matter using strongly lensed gravitational waves from binary black holes

classification astro-ph.CO
keywords lenseddarkmattereventsdistributionexpectedmassnumber
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Next-generation ground-based gravitational-wave (GW) detectors are expected to detect millions of binary black hole mergers during their operation period. A small fraction ($\sim 0.1 - 1\%$) of them will be strongly lensed by intervening galaxies and clusters, producing multiple copies of the GW signals. The expected number of lensed events and the distribution of the time delay between lensed images will depend on the mass distribution of the lenses at different redshifts. Warm dark matter or fuzzy dark matter models predict lower abundances of small mass dark matter halos as compared to the standard cold dark matter. This will result in a reduction in the number of strongly lensed GW events, especially at small time delays. Using the number of lensed events and the lensing time delay distribution, we can put a lower bound on the mass of the warm/fuzzy dark matter particle from a catalog of lensed GW events. The expected bounds from GW strong lensing from next-generation detectors are significantly better than the current constraints.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Improved Identification of Strongly Lensed Gravitational Waves with Host Galaxy Locations

    astro-ph.CO 2025-12 unverdicted novelty 6.0

    A two-step Bayesian reweighting scheme using Euclid galaxy locations boosts the Bayes factor for true lensed GW pairs by a factor of about 10 while lowering it for unlensed coincidences.

  2. Parameter inference of millilensed gravitational waves using neural spline flows

    gr-qc 2025-05 conditional novelty 6.0

    Neural spline flows perform fast posterior inference on 11-dimensional millilensed GW parameters with accuracy comparable to dynesty for most quantities and a 3-day to 0.8-second speedup.