FluxMC integrates flow matching with parallel tempering MCMC to converge in under five hours on high-fidelity IMRPhenomHM waveforms for massive black hole binaries, where standard methods fail after hundreds of hours and produce two to three orders of magnitude higher distributional error.
Fast gravitational wave parameter estimation without com- promises
6 Pith papers cite this work. Polarity classification is still indexing.
6
Pith papers citing it
citation-role summary
background 4
citation-polarity summary
roles
background 4polarities
background 4representative citing papers
F-statistic framework analytically maximizes over distance and polarization to enable faster Bayesian inference of compact binary coalescences with a new evidence formulation that matches full frequency-domain results at lower cost.
Bayesian inference on LVK O1-O3 events with eccentric aligned-spin waveforms yields log10 Bayes factors of 1.77-4.75 favoring eccentricity for GW200129, GW190701 and GW200208_22, and >99.5% probability that at least one of 57 events is eccentric under an astrophysically motivated rate prior.
Bayesian analysis of GW170817 with PPE framework and EM polarization constraints shows mild preference for scalar mode in quadrupole harmonics and improves bounds on non-GR parameters by up to 60%.
The JCDM model yields H0 of 66.95 plus or minus 0.51 km/s/Mpc and Omega_m of 0.3419 plus or minus 0.0065 in a flat universe, rising to H0 of 69.13 plus or minus 0.56 with slight positive curvature, fitting late-time data but struggling with full early-universe consistency.
Relative binning accelerates TIGER parameterized GR tests by factors of 10-100 while recovering unbiased posteriors on simulated signals and real events like GW150914.
citing papers explorer
-
FluxMC: Rapid and High-Fidelity Inference for Space-Based Gravitational-Wave Observations
FluxMC integrates flow matching with parallel tempering MCMC to converge in under five hours on high-fidelity IMRPhenomHM waveforms for massive black hole binaries, where standard methods fail after hundreds of hours and produce two to three orders of magnitude higher distributional error.
-
A Robust and Efficient F-statistic-based Framework for Consistent Bayesian Inference of Compact Binary Coalescences
F-statistic framework analytically maximizes over distance and polarization to enable faster Bayesian inference of compact binary coalescences with a new evidence formulation that matches full frequency-domain results at lower cost.
-
Evidence for eccentricity in the population of binary black holes observed by LIGO-Virgo-KAGRA
Bayesian inference on LVK O1-O3 events with eccentric aligned-spin waveforms yields log10 Bayes factors of 1.77-4.75 favoring eccentricity for GW200129, GW190701 and GW200208_22, and >99.5% probability that at least one of 57 events is eccentric under an astrophysically motivated rate prior.
-
Tests of scalar polarizations with multi-messenger events
Bayesian analysis of GW170817 with PPE framework and EM polarization constraints shows mild preference for scalar mode in quadrupole harmonics and improves bounds on non-GR parameters by up to 60%.
-
Cosmological constraints on the big bang quantum cosmology model
The JCDM model yields H0 of 66.95 plus or minus 0.51 km/s/Mpc and Omega_m of 0.3419 plus or minus 0.0065 in a flat universe, rising to H0 of 69.13 plus or minus 0.56 with slight positive curvature, fitting late-time data but struggling with full early-universe consistency.
-
Accelerating parameter estimation for parameterized tests of general relativity with gravitational-wave observations
Relative binning accelerates TIGER parameterized GR tests by factors of 10-100 while recovering unbiased posteriors on simulated signals and real events like GW150914.