Bayesian Power Spectral Density Estimation for LISA Noise Based on Penalized Splines With a Parametric Boost
Date
Authors
Aimen, Nazeela
Maturana-Russel, Patricio
Vajpeyi, Avi
Christensen, Nelson
Meyer, Renate
Supervisor
Item type
Journal Article
Degree name
Journal Title
Journal ISSN
Volume Title
Publisher
American Physical Society (APS)
Abstract
Flexible and accurate noise characterization is crucial for the precise estimation of gravitational-wave parameters. We introduce a Bayesian method for estimating the power spectral density (PSD) of long, stationary time series, explicitly tailored for Laser Interferometer Space Antenna (LISA) data analysis. Our approach models the PSD as the geometric mean of a parametric and a nonparametric component, combining the knowledge from parametric models with the flexibility to capture deviations from theoretical expectations. The nonparametric component is expressed by a mixture of penalized B splines. Adaptive, data-driven knot placement, performed once at initialization, removes the need for a reversible-jump Markov chain Monte Carlo, while hierarchical roughness-penalty priors prevent overfitting. Validation on simulated autoregressive (AR) data of order 4 [AR(4)] demonstrates estimator consistency and shows that well-matched parametric components reduce the integrated absolute error compared to an uninformative baseline, requiring fewer spline knots to achieve comparable accuracy. Applied to one year of simulated LISA 𝑋-channel (univariate) noise, our method achieves relative integrated absolute errors of 𝒪(10ˉ²), making it suitable for iterative analysis pipelines and multiyear mission data sets.Description
Keywords
49 Mathematical Sciences, 4905 Statistics, gravitational waves, PSD estimation, P-splines, LISA
Source
Physical Review D, ISSN: 2470-0010 (Print); 2470-0029 (Online), American Physical Society (APS), 113(2). doi: 10.1103/dcb6-1jsl
Publisher's version
Rights statement
This is the Author's Accepted Manuscript of an article published in Physical Review D. The Version of Record is available at DOI: 10.1103/dcb6-1jsl