53 research outputs found

    Virgo Detector Characterization and Data Quality during the O3 run

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    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.Comment: 86 pages, 33 figures. This paper has been divided into two articles which supercede it and have been posted to arXiv on October 2022. Please use these new preprints as references: arXiv:2210.15634 (tools and methods) and arXiv:2210.15633 (results from the O3 run

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

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    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.Comment: 57 pages, 18 figures. To be submitted to Class. and Quantum Grav. This is the "Results" part of preprint arXiv:2205.01555 [gr-qc] which has been split into two companion articles: one about the tools and methods, the other about the analyses of the O3 Virgo dat

    Virgo Detector Characterization and Data Quality: tools

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    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.Comment: 44 pages, 16 figures. To be submitted to Class. and Quantum Grav. This is the "Tools" part of preprint arXiv:2205.01555 [gr-qc] which has been split into two companion articles: one about the tools and methods, the other about the analyses of the O3 Virgo dat

    Search for dark matter produced in association with a Higgs boson decaying to a pair of bottom quarks in proton-proton collisions at root s=13TeV

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    A search for dark matter produced in association with a Higgs boson decaying to a pair of bottom quarks is performed in proton-proton collisions at a center-of-mass energy of 13 TeV collected with the CMS detector at the LHC. The analyzed data sample corresponds to an integrated luminosity of 35.9 fb(-1). The signal is characterized by a large missing transverse momentum recoiling against a bottom quark-antiquark system that has a large Lorentz boost. The number of events observed in the data is consistent with the standard model background prediction. Results are interpreted in terms of limits both on parameters of the type-2 two-Higgs doublet model extended by an additional light pseudoscalar boson a (2HDM+a) and on parameters of a baryonic Z simplified model. The 2HDM+a model is tested experimentally for the first time. For the baryonic Z model, the presented results constitute the most stringent constraints to date.Peer reviewe

    A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution

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    We describe a method to obtain point and dispersion estimates for the energies of jets arising from b quarks produced in proton-proton collisions at an energy of s = 13 TeV at the CERN LHC. The algorithm is trained on a large sample of simulated b jets and validated on data recorded by the CMS detector in 2017 corresponding to an integrated luminosity of 41 fb - 1 . A multivariate regression algorithm based on a deep feed-forward neural network employs jet composition and shape information, and the properties of reconstructed secondary vertices associated with the jet. The results of the algorithm are used to improve the sensitivity of analyses that make use of b jets in the final state, such as the observation of Higgs boson decay to b b ¯

    Observation of gravitational waves from the coalescence of a 2.5−4.5 M⊙ compact object and a neutron star

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    Search for eccentric black hole coalescences during the third observing run of LIGO and Virgo

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    Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass M>70 M⊙) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities 0<e≤0.3 at 0.33 Gpc−3 yr−1 at 90\% confidence level

    Search for gravitational-lensing signatures in the full third observing run of the LIGO-Virgo network

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    Gravitational lensing by massive objects along the line of sight to the source causes distortions of gravitational wave-signals; such distortions may reveal information about fundamental physics, cosmology and astrophysics. In this work, we have extended the search for lensing signatures to all binary black hole events from the third observing run of the LIGO--Virgo network. We search for repeated signals from strong lensing by 1) performing targeted searches for subthreshold signals, 2) calculating the degree of overlap amongst the intrinsic parameters and sky location of pairs of signals, 3) comparing the similarities of the spectrograms amongst pairs of signals, and 4) performing dual-signal Bayesian analysis that takes into account selection effects and astrophysical knowledge. We also search for distortions to the gravitational waveform caused by 1) frequency-independent phase shifts in strongly lensed images, and 2) frequency-dependent modulation of the amplitude and phase due to point masses. None of these searches yields significant evidence for lensing. Finally, we use the non-detection of gravitational-wave lensing to constrain the lensing rate based on the latest merger-rate estimates and the fraction of dark matter composed of compact objects

    Ultralight vector dark matter search using data from the KAGRA O3GK run

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    Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for U(1)B−L gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the U(1)B−L gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM
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