Electronic Theses and Dissertations

Date of Award


Document Type


Degree Name

M.S. in Physics

First Advisor

Marco Cavaglia

Second Advisor

Emanuele Berti

Third Advisor

Lucien M. Cremaldi

Relational Format



When LIGO's interferometers are in operation, many auxiliary data channels monitor and record the state of the instruments and surrounding environmental conditions. Analyzing these channels allows LIGO scientists to evaluate the quality of the data collected and veto data segments of poor quality. A set of scripts were built up in an ad hoc fashion, sometimes with limited documentation, to assist in this analysis. In this thesis, we present DQTunePipe , a set of Python modules to replace these scripts and aid in the detector characterization of the LIGO instruments. The use of Python makes the analysis method more compatible with existing LIGO tools. DQTunePipe improves data quality analysis by allowing users to select specific detector characterization tasks as well as providing a maintainable framework upon which additional modules may be built. The nature of the Python DQTunePipe code allows the addition of new features with great simplicity. This thesis details the structure of DQTunePipe, serves as its documentation at the time of this writing, and outlines the procedures for incorporating new features.

Included in

Physics Commons



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