Data Analysis Techniques for Ligo Detector Characterization

Date

2017

Authors

Valdes Sanchez, Guillermo A.

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Abstract

Gravitational-wave astronomy is a branch of astronomy which aims to use gravitational waves to collect observational data about astronomical objects and events such as black holes, neutron stars, supernovae, and processes including those of the early universe shortly after the Big Bang.

Einstein first predicted gravitational waves in the early century XX, but it was not until Septem- ber 14, 2015, that the Laser Interferometer Gravitational-Wave Observatory (LIGO) directly ob- served the first gravitational waves in history.

LIGO consists of two twin detectors, one in Livingston, Louisiana and another in Hanford, Washington. Instrumental and sporadic noises limit the sensitivity of the detectors. Scientists conduct Data Quality studies to distinguish a gravitational-wave signal from the noise, and new techniques are continuously developed to identify, mitigate, and veto unwanted noise.

This work presents the application of data analysis techniques, such as Hilbert-Huang trans- form (HHT) and Kalman filtering (KF), in LIGO detector characterization. We investigated the application of HHT to characterize the gravitational-wave signal of the first detection, we also demonstrated the functionality of HHT identifying noise originated from light being scattered by perturbed surfaces, and we estimated thermo-optical aberration using KF.

We put particular attention to the scattering origin application, for which a tool was developed to identify disturbed surfaces originating scattering noise. The results reduced considerably the time to search for the scattering surface and helped LIGO commissioners to mitigate the noise.

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Keywords

data analysis, detector characterization, gravitational waves, Hilbert-Huang transform, LIGO, signal processing

Citation

Department

Physics and Astronomy