REVIEW 9 cited by
Mind the gap: addressing data gaps and assessing noise mismodeling in LISA
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
Mind the gap: addressing data gaps and assessing noise mismodeling in LISA
read the original abstract
Due to the sheer complexity of the Laser Interferometer Space Antenna (LISA) space mission, data gaps arising from instrumental irregularities and/or scheduled maintenance are unavoidable. Focusing on merger-dominated massive black hole binary signals, we test the appropriateness of the Whittle-likelihood on gapped data in a variety of cases. From first principles, we derive the likelihood valid for gapped data in both the time and frequency domains. Cheap-to-evaluate proxies to p-p plots are derived based on a Fisher-based formalism, and verified through Bayesian techniques. Our tools allow to predict the altered variance in the parameter estimates that arises from noise mismodeling, as well as the information loss represented by the broadening of the posteriors. The result of noise mismodeling with gaps is sensitive to the characteristics of the noise model, with strong low-frequency (red) noise and strong high-frequency (blue) noise giving statistically significant fluctuations in recovered parameters. We demonstrate that the introduction of a tapering window reduces statistical inconsistency errors, at the cost of less precise parameter estimates. We also show that the assumption of independence between inter-gap segments appears to be a fair approximation even if the data set is inherently coherent. However, if one instead assumes fictitious correlations in the data stream, when the data segments are actually independent, then the resultant parameter recoveries could be inconsistent with the true parameters. The theoretical and numerical practices that are presented in this work could readily be incorporated into global-fit pipelines operating on gapped data.
Forward citations
Cited by 9 Pith papers
-
The geometry of lunar gravitational wave detection
Optimal SSB frame origin for LGWA cuts sampling time by 10x and tightens chirp mass and sky position constraints for stellar-mass binaries beyond LVK performance.
-
First-time assessment of glitch-induced bias and uncertainty in inference of extreme mass ratio inspirals
Moderately mitigated glitch streams induce negligible to minor biases (0.04–0.6σ) in EMRI parameters while weakly mitigated streams with higher-SNR events can reach ~1σ biases, making EMRI inference more robust than f...
-
Flexible Gravitational-Wave Parameter Estimation with Transformers
Dingo-T1 is one transformer model that adapts at inference to arbitrary detector subsets and frequency cuts for gravitational-wave parameter estimation.
-
Handling Data Gaps for the Next Generation of Gravitational-Wave Observatories
Presents an efficient time-frequency Bayesian gap-filling technique that avoids costly matrix operations and integrates into LISA Global Fit, demonstrated on simulated LISA data.
-
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.
-
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.
-
Global time-frequency search for stellar-mass binary black holes in LISA
A time-frequency semi-coherent search pipeline detects stellar-mass BBH inspirals in LISA data down to coherent SNR of approximately 11-14 on the Yorsh data challenge for aligned-spin, low-eccentricity systems.
-
An explicit and differentiable Wilson-Daubechies-Meyer transform for gravitational-wave data analysis
An explicit, GPU-ready WDM wavelet-packet package reproduces frequency-domain LISA galactic-binary posteriors under stationary noise and documents the full discrete construction.
-
An explicit and differentiable Wilson-Daubechies-Meyer transform for gravitational-wave data analysis
Open-source WDM transform package with JAX support and numerical validation of equivalence to frequency-domain likelihoods for a LISA binary under stationary noise.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.