University of Minnesota
School of Physics & Astronomy

Cosmology Lunchtime Seminar

Monday, December 10th 2018
12:15 pm:
Speaker: Rich Ormiston, UMN
Subject: Extending the reach of gravitational-wave detectors with machine learning

With the advent of gravitational-wave astronomy, techniques to extend the reach of gravitational- wave detectors are desired. In addition to the stellar mass black hole and neutron star mergers already detected, many more are below the surface of the noise, available for detection if the noise is reduced enough. One method for noise reduction applies machine learning algorithms to gravitational-wave detector data and auxiliary channels on-site to reduce the noise in the time-series due to instrumental artifacts. Given realistic assumptions about coupling mechanisms, we are able to reduce the noise floor, leading to detector sensitivity improvements. This framework is generic enough to subtract both linear and non-linear coupling mechanisms, and learn about the mechanisms which are not currently understood to be limiting detector sensitivities. We discuss lessons learned and how this work can be generalized to other time series regression analyses in all areas of science.

Faculty Host: Vuk Mandic

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