Ground-triggered Bayesian analysis enables detection and tight constraints on eccentricity and chirp mass for a GW190521-like eccentric binary black hole in one year of LISA or TianQin data at SNR ~7.
Fourier-domainmodulationsandde- lays of gravitational-wave signals
6 Pith papers cite this work. Polarity classification is still indexing.
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abstract
We present a Fourier-domain approach to modulations and delays of gravitational wave signals, a problem which arises in two different contexts. For space-based detectors like LISA, the orbital motion of the detector introduces a time-dependency in the response of the detector, consisting of both a modulation and a varying delay. In the context of signals from precessing spinning binary systems, a useful tool for building models of the waveform consists in representing the signal as a time-dependent rotation of a quasi-non-precessing waveform. In both cases, being able to compute transfer functions for these effects directly in the Fourier domain may enable performance gains for data analysis applications by using fast frequency-domain waveforms. Our results generalize previous approaches based on the stationary phase approximation for inspiral signals, extending them by including delays and computing corrections beyond the leading order, while being applicable to the broader class of inspiral-merger-ringdown signals. In the LISA case, we find that a leading-order treatment is accurate for high-mass and low-mass signals that are chirping fast enough, with errors consistently reduced by the corrections we derived. By contrast, low-mass binary black holes, if far away from merger and slowly-chirping, cannot be handled by this formalism and we develop another approach for these systems. In the case of precessing binaries, we explore the merger-ringdown range for a handful of cases, using a simple model for the post-merger precession. We find that deviations from leading order can give large fractional errors, while affecting mainly subdominant modes and giving rise to a limited unfaithfulness in the full waveform. Including higher-order corrections consistently reduces the unfaithfulness, and we further develop an alternative approach to accurately represent post-merger features.
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representative citing papers
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.
IMRPhenomXPHM is a new computationally efficient phenomenological model for precessing binary black hole gravitational-wave signals that incorporates higher-order modes via twisting-up maps from non-precessing waveforms.
DCL-xLSTM neural network detects lensed GW events with AUC over 0.99 using training on PM and SIS lens models in the millihertz band.
LGWA could observe more than one third of known binary black hole events, detect ~90 mergers per year, and measure chirp mass better than third-generation detectors for massive systems.
LISA EMRIs can constrain deviations from Kerr equatorial symmetry to 10^{-2} and axial symmetry to 10^{-3} using Analytic Kludge waveforms and Fisher analysis.
citing papers explorer
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Archival Inference for Eccentric Stellar-Mass Binary Black Holes in Space-Based Gravitational Wave Observations
Ground-triggered Bayesian analysis enables detection and tight constraints on eccentricity and chirp mass for a GW190521-like eccentric binary black hole in one year of LISA or TianQin data at SNR ~7.
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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.
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Computationally efficient models for the dominant and sub-dominant harmonic modes of precessing binary black holes
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Detection of Lensed Gravitational Waves in the Millihertz Band Using Frequency-Domain Lensing Feature Extraction Network
DCL-xLSTM neural network detects lensed GW events with AUC over 0.99 using training on PM and SIS lens models in the millihertz band.
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Gravitational-wave parameter estimation to the Moon and back: massive binaries and the case of GW231123
LGWA could observe more than one third of known binary black hole events, detect ~90 mergers per year, and measure chirp mass better than third-generation detectors for massive systems.
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Probing Kerr Symmetry Breaking with LISA Extreme-Mass-Ratio Inspirals
LISA EMRIs can constrain deviations from Kerr equatorial symmetry to 10^{-2} and axial symmetry to 10^{-3} using Analytic Kludge waveforms and Fisher analysis.