REVIEW 5 cited by
The wave nature of continuous gravitational waves from microlensing
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
read the original abstract
Gravitational wave predicted by General Relativity is the transverse wave of spatial strain. Several gravitational waveform signals from binary black holes and from a binary neutron star system accompanied by electromagnetic counterparts have been recorded by advanced LIGO and advanced Virgo. In analogy to light, the spatial fringes of diffraction and interference should also exist as the important features of gravitational waves. We propose that observational detection of such fringes could be achieved through gravitational lensing of continuous gravitational waves. The lenses would play the role of the diffraction barriers. Considering peculiar motions of the observer, the lens and the source, the spatial amplitude variation of diffraction or interference fringes should be detectable as an amplitude modulation of monochromatic gravitational signal.
Forward citations
Cited by 5 Pith papers
-
Gravitational lensing of gravitational waves: universal characteristics of strongly lensed memory waveforms
Strongly lensed gravitational-wave memory waveforms acquire universal parity signatures—odd for type I/III images, even for type II—that can identify image type via a simple step-function approximation.
-
Identification of Lensed Gravitational-Wave Beat Patterns by LISA
Strong lensing of MBHBs produces identifiable beat patterns in about 7% of detectable two-image LISA events, with Bayesian inference recovering time delay and magnification parameters.
-
Identifying Microlensing by Compact Dark Matter through Diffraction Patterns in Gravitational Waves with Machine Learning
A wavelet-convolution neural network distinguishes simulated lensed from unlensed gravitational waves with 92.2% accuracy (AUC 0.965) using wave-optics diffraction patterns.
-
Self-lensing of moving gravitational-wave sources can break the microlensing crossing timescale degeneracy
Self-lensing of a moving GW chirp by an orbiting black hole yields a curve width and interference beats that together give the orbital distance and the black hole mass.
-
Parameter estimation of microlensed gravitational waves with Conditional Variational Autoencoders
A conditional variational autoencoder trained on simulated microlensed binary black hole signals estimates lens mass and source offset with well-calibrated posteriors, runs about 10,000 times faster than Bilby, and cu...
Discussion (0). Continue with ORCID to comment.