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.
","abstract_html":"<p>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.</p>","abstract_has_math":false,"creators":["Rankins, Brooke Anne"],"institution":null,"degree_name":"M.S. in Physics","degree_level":"Thesis","degree_discipline":null,"degree_department":null,"school":null,"contributors":["Marco Cavaglia","Emanuele Berti","Lucien M. Cremaldi"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011-01-01T08:00:00Z","date_published":"2011-01-01T08:00:00Z","updated_at":"2026-07-24T03:05:22Z","subjects":["Data Quality","Detchar","LIGO","Physics"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://egrove.olemiss.edu/etd/239","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Marco Cavaglia","Emanuele Berti","Lucien M. Cremaldi"]},{"key":"dc:creator","label":"Author","values":["Rankins, Brooke Anne"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2019-01-01T08:00:00Z"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S. in Physics"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Data Quality","Detchar","LIGO","Physics"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://egrove.olemiss.edu/etd/239"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["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.
"]},{"key":"dc:title","label":"Title","values":["DQTunePipe: a Set of Python Tools for LIGO Detector Characterization"]}]}],"canonical_facts":{"dc:contributor":["Marco Cavaglia","Emanuele Berti","Lucien M. Cremaldi"],"dc:creator":["Rankins, Brooke Anne"],"dc:date.available":["2019-01-01T08:00:00Z"],"dc:description.abstract":["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.
"],"dc:identifier":["https://egrove.olemiss.edu/etd/239"],"dc:subject":["Data Quality","Detchar","LIGO","Physics"],"dc:title":["DQTunePipe: a Set of Python Tools for LIGO Detector Characterization"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S. in Physics"]},"updated_at":"2026-07-24T03:05:22Z"}