Bayesian Nonparametric Spectral Analysis for Gravitational Wave Astronomy

Abstract: The new era of gravitational wave astronomy truly began on September 14, 2015 with the sensational first direct observation of gravitational waves, when LIGO recorded the signature of the merger of two black holes. In the subsequent three observing runs of the LIGO/Virgo network, gravitational waves from 90 compact binary mergers have been announced. Moreover, the future space-based observatory LISA will open the low-frequency window on gravitational waves and will be sensitive to a vast range of sources including the white dwarf binaries in our Milky Way and mergers of supermassive black holes at the centre of galaxies. Beyond signal detection, a major challenge has been the development of statistical methodology for estimating the physical waveform parameters and quantifying their uncertainties. Bayesian methods and MCMC have played a key role in this new era of astrophysics. I will review the statistical methods that enabled the estimation of the waveform parameters. This challenge has also been a key driver for new theoretical and methodological advancements in statistics. The call for a more robust instrumental noise characterization aiming at a simultaneous estimation of noise characteristics and gravitational wave parameters has triggered ongoing research into Bayesian nonparametric analysis of time series. Starting with nonparametric Bayesian approaches to spectral density estimation of univariate Gaussian stationary time series, I will review novel extensions to multivariate, non-Gaussian, and locally stationary time series.

other computer sciencespace physics and aeronomydata analysis, statistics and probability

Audience: researchers in the topic

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IAU-IAA Astrostats & Astroinfo seminar(archived version by January 2023)

Series comments: This is an archived version of the seminar with information about talks by January 2023.

Use the following link for the new version: sites.google.com/view/iau-iaaseminar-new

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Joint IAU-IAA Astrostats & Astroinfo seminar series focuses on statistical and computational methodological challenges arising in the various fields of astronomy. It discusses existing and new advanced approaches in statistical analysis and data mining of astronomical data.

In the 21st century, increasing resources are devoted to wide-field astronomical surveys, multi-dimensional data, and high-throughput instruments that produce peta-scale datasets and giga-scale samples. In addition to the growing tasks of data storage and management, new statistical tools have been developed or specified for astronomical problems. Astronomical insights require characterizing structure in images, spectra or time series by using non-linear, often high-dimensional models.

This international online seminar series is an initiative of the International Astrostatistics Association and the IAU Astroinformatics and Astrostatistics Commission.

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