activity
20192026
most citedComputational Techniques for Parameter Estimation of Gravitational Wave Signals

9 citations · 9 across the 9 of their papers we have counts for

collaborators

13 papers

astro-ph.IM2026

Variational Bayesian Inference for the Spectral Structure of LISA Noise

Jianan Liu, Avi Vajpeyi, Renate Meyer +2

Estimating spectral density matrices for future space-based gravitational-wave detectors such as LISA is challenging due to the long duration of the data and the correlated instrum…

gr-qc2026

Bayesian P-spline recovery of stochastic gravitational-wave backgrounds in LISA

Nazeela Aimen, Patricio Maturana-Russel, Avi Vajpeyi +2

The detection of a stochastic gravitational-wave background (SGWB) is a primary science objective for the Laser Interferometer Space Antenna (LISA). However, extracting these signa…

astro-ph.HE2026

Insights into the Pulsar Timing Array hypothesis space

El Mehdi Zahraoui, Patricio Maturana-Russel, Willem van Straten +2

We present novel insights into the pulsar-noise model space in pulsar timing array (PTA) experiments. Through a comparative analysis of the same Parkes PTA second data release obse…

stat.ME2026

Multivariate Bayesian P-spline estimation of spectral density matrices, with application to LISA TDI noise

Avi Vajpeyi, Renate Meyer, Patricio Maturana-Russel +1

We present a Bayesian P-spline method for estimating the frequency-dependent cross-spectral density matrix of stationary multivariate time series. The inverse spectral matrix is pa…

astro-ph.IM2025

Enhancing evidence estimation through informed probability density approximation

El Mehdi Zahraoui, Patricio Maturana-Russel, Avi Vajpeyi +3

We introduce the Morph approximation, a class of product approximations of probability densities that selects low-order disjoint parameter blocks by maximizing the sum of their tot…

gr-qc2025

Bayesian power spectral density estimation for LISA noise based on penalized splines with a parametric boost

Nazeela Aimen, Patricio Maturana-Russel, Avi Vajpeyi +2

Flexible and accurate noise characterization is crucial for the precise estimation of gravitational-wave parameters. We introduce a Bayesian method for estimating the power spectra…