arXiv subjects

G. S. Cabourn Davies

Publications and source records attributed to G. S. Cabourn Davies.

6 recordsLinked to original sources

arXiv2023

QoQ: a Q-transform based test for Gravitational Wave transient events

The observation of transient gravitational waves is hindered by the presence of transient noise, colloquially referred to as glitches. These glitches can often be misidentified as gravitational waves by searches for unmodeled transients using the excess-power type of methods and sometimes even excite template waveforms for compact binary coalescences while using matched filter techniques. They thus create a significant background in the searches. This background is more critical in getting identified promptly and efficiently within the context of real-time searches for gravitational-wave transients. Such searches are the ones that have enabled multi-messenger astrophysics with the start of the Advanced LIGO and Advanced Virgo data taking in 2015 and they will continue to enable the field for further discoveries. With this work we propose and demonstrate the use of a signal-based test that quantifies the fidelity of the time-frequency decomposition of the putative signal based on first principles on how astrophysical transients are expected to be registered in the detectors and empirically measuring the instrumental noise. It is based on the Q-transform and a measure of the occupancy of the corresponding time-frequency pixels over select time-frequency volumes; we call it ``QoQ''. Our method shows a 40% reduction in the number of retraction of public alerts that were issued by the LIGO-Virgo-KAGRA collaborations during the third observing run with negligible loss in sensitivity. Receiver Operator Characteristic measurements suggest the method can be used in online and offline searches for transients, reducing their background significantly.

gr-qc↗

arXiv2023

Virgo Detector Characterization and Data Quality: results from the O3 run

The Advanced Virgo detector has contributed with its data to the rapid growth of the number of detected gravitational-wave (GW) signals in the past few years, alongside the two Advanced LIGO instruments. First during the last month of the Observation Run 2 (O2) in August 2017 (with, most notably, the compact binary mergers GW170814 and GW170817), and then during the full Observation Run 3 (O3): an 11-months data taking period, between April 2019 and March 2020, that led to the addition of about 80 events to the catalog of transient GW sources maintained by LIGO, Virgo and now KAGRA. These discoveries and the manifold exploitation of the detected waveforms require an accurate characterization of the quality of the data, such as continuous study and monitoring of the detector noise sources. These activities, collectively named {\em detector characterization and data quality} or {\em DetChar}, span the whole workflow of the Virgo data, from the instrument front-end hardware to the final analyses. They are described in details in the following article, with a focus on the results achieved by the Virgo DetChar group during the O3 run. Concurrently, a companion article describes the tools that have been used by the Virgo DetChar group to perform this work.

gr-qc↗

arXiv2023

Virgo Detector Characterization and Data Quality: tools

Detector characterization and data quality studies -- collectively referred to as {\em DetChar} activities in this article -- are paramount to the scientific exploitation of the joint dataset collected by the LIGO-Virgo-KAGRA global network of ground-based gravitational-wave (GW) detectors. They take place during each phase of the operation of the instruments (upgrade, tuning and optimization, data taking), are required at all steps of the dataflow (from data acquisition to the final list of GW events) and operate at various latencies (from near real-time to vet the public alerts to offline analyses). This work requires a wide set of tools which have been developed over the years to fulfill the requirements of the various DetChar studies: data access and bookkeeping; global monitoring of the instruments and of the different steps of the data processing; studies of the global properties of the noise at the detector outputs; identification and follow-up of noise peculiar features (whether they be transient or continuously present in the data); quick processing of the public alerts. The present article reviews all the tools used by the Virgo DetChar group during the third LIGO-Virgo Observation Run (O3, from April 2019 to March 2020), mainly to analyse the Virgo data acquired at EGO. Concurrently, a companion article focuses on the results achieved by the DetChar group during the O3 run using these tools.

gr-qc↗

arXiv2022

Virgo Detector Characterization and Data Quality during the O3 run

The Advanced Virgo detector has contributed with its data to the rapid growth of the number of detected gravitational-wave signals in the past few years, alongside the two LIGO instruments. First, during the last month of the Observation Run 2 (O2) in August 2017 (with, most notably, the compact binary mergers GW170814 and GW170817) and then during the full Observation Run 3 (O3): an 11 months data taking period, between April 2019 and March 2020, that led to the addition of about 80 events to the catalog of transient gravitational-wave sources maintained by LIGO, Virgo and KAGRA. These discoveries and the manifold exploitation of the detected waveforms require an accurate characterization of the quality of the data, such as continuous study and monitoring of the detector noise. These activities, collectively named {\em detector characterization} or {\em DetChar}, span the whole workflow of the Virgo data, from the instrument front-end to the final analysis. They are described in details in the following article, with a focus on the associated tools, the results achieved by the Virgo DetChar group during the O3 run and the main prospects for future data-taking periods with an improved detector.

gr-qc↗

arXiv2021

Salient features of the optimised PyCBC IMBH search

Matched-filter based PyCBC searches have successfully detected $\sim \mathcal{O}(50)$ compact binary merger signals in the LIGO-Virgo data. While most PyCBC searches have been designed to detect stellar-mass binaries, we present here a new search that is optimised to detect short-duration \ac{GW} signals emitted by intermediate-mass black hole mergers. When applied to the first half of the third observation run data, the optimised search re-identified the \ac{IMBH} binary event, GW190521, with a false alarm rate of 1 in 727 yrs, significantly lower than the previous PyCBC search result of 1 in 0.94 yr. Analysis of simulated signals from \ac{IMBH} binaries with generically spinning components shows an increase in sensitivity by a factor of 1.2 to 3 over previous PyCBC searches.

gr-qc↗

arXiv2021

An optimized PyCBC search for gravitational waves from intermediate-mass black hole mergers

The detection of intermediate-mass black holes (IMBHs) i.e. those with mass $\sim 100$-$10^5 M_\odot$, is an emerging goal of gravitational-wave (GW) astronomy with wide implications for cosmology and tests of strong-field gravity. Current PyCBC-based searches for compact binary mergers, which matched filter the detector data against a set of template waveforms, have so far detected or confirmed several GW events. However, the sensitivity of these searches to signals arising from mergers of IMBH binaries is not optimal. Here, we present a new optimised PyCBC-based search for such signals. Our search benefits from using a targeted template bank, stricter signal-noise discriminators and a lower matched-filter frequency cut-off. In particular, for a population of simulated signals with isotropically distributed spins, we improve the sensitive volume-time product over previous PyCBC-based searches, at an inverse false alarm rate of 100 years, by a factor of 1.5 to 3 depending on the total binary mass. We deploy this new search on Advanced LIGO-Virgo data from the first half of the third observing run. The search does not identify any new significant IMBH binaries but does confirm the detection of the short-duration GW signal GW190521 with a false alarm rate of 1 in 727 years.

gr-qc↗