REVIEW 2 cited by
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
Probing the nature of dark matter using strongly lensed gravitational waves from binary black holes
read the original abstract
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.
Forward citations
Cited by 2 Pith papers
-
Improved Identification of Strongly Lensed Gravitational Waves with Host Galaxy Locations
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.
-
Parameter inference of millilensed gravitational waves using neural spline flows
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.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.