Astrostatistics in Gravitational-wave Astronomy

Abstract: Modern astronomical data sets often raise challenges associated with selection biases, accounting for confusion between backgrounds and foregrounds, and performing inference on big data with complex, multi-parameter models. I will discuss some of the techniques that we used to attack these problems, illustrating them with results from gravitational-wave observations of merging black holes … and a bit further afield.

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Series comments: This is an archived version of the seminar with information about talks by January 2023.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