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Andrea Miani

Publications and source records attributed to Andrea Miani.

4 recordsLinked to original sources

Optimizing searches for gravitational wave bursts using coherent WaveBurst 2G

The most general searches for gravitational wave transients (GWTs) rely on data analysis methods that do not assume prior knowledge of the signal waveform, direction, or arrival time on Earth. These searches provide data-driven signal reconstructions that are crucial both for testing available emission models and for discovering yet-to-be-uncovered sources. Here, we discuss progress in the detection performance of the coherent WaveBurst second-generation pipeline (cWB-2G), which is highly adaptable to both minimally modeled and model-informed searches for GWTs. Several search configurations for GWTs are examined using approximately 14.8 days of observation time from the third observing run by LIGO-Virgo-KAGRA (LVK). Recent enhancements include a ranking statistic fully based on multivariate classification with eXtreme Gradient Boosting, a thorough validation of the statistical significance accuracy of GWT candidates, and a measurement of the correlations of false alarms and simulated detections between different concurrent searches. For the first time, we provide a comprehensive comparison of cWB-2G performance on data from networks made of two and three detectors, and we demonstrate the advantage of combining concurrent searches for GWTs of generic morphology in a global observatory. This work offers essential insights for assessing our data analysis strategies in ongoing and future LVK searches for generic GWTs.

gr-qc

Constraints on the amplitude of gravitational wave echoes from black hole ring-down using minimal assumptions

Gravitational wave echoes may appear following a compact binary coalescence if the remnant is an "exotic compact object" (ECO). ECOs are proposed alternatives to the black holes of Einstein's general relativity theory and are predicted to possess reflective boundaries. This work reports a search for gravitational wave transients (GWTs) of generic morphology occurring shortly after (<1s) binary black hole (BBH) mergers, therefore targeting all gravitational wave echo models. We investigated the times after the ringdown for the higher signal-to-noise ratio BBHs within the public catalog GWTC-3 by the LIGO-Virgo-KAGRA collaborations (LVK). Our search is based on the coherentWaveBurst pipeline, widely used in generic searches for GWTs by the LVK, and deploys new methods to enhance its detection performances at low signal-to-noise ratios. We employ Monte Carlo simulations for estimating the detection efficiency of the search and determining the statistical significance of candidates. We find no evidence of previously undetected GWTs and our loudest candidates are morphologically consistent with known instrumental noise disturbances. Finally, we set upper limits on the amplitude of GW echoes for single BBH mergers.

gr-qc

Search for gravitational-wave bursts in the third Advanced LIGO-Virgo run with coherent WaveBurst enhanced by Machine Learning

This paper presents a search for generic short-duration gravitational-wave (GW) transients (or GW bursts) in the data from the third observing run of Advanced LIGO and Advanced Virgo. We use coherent WaveBurst (cWB) pipeline enhanced with a decision-tree classification algorithm for more efficient separation of GW signals from noise transients. The machine-learning (ML) algorithm is trained on a representative set of noise events and a set of simulated stochastic signals that are not correlated with any known signal model. This training procedure preserves the model-independent nature of the search. We demonstrate that the ML-enhanced cWB pipeline can detect GW signals at a larger distance than previous model-independent searches. The sensitivity improvements are achieved across the broad spectrum of simulated signals, with the goal of testing the robustness of this model-agnostic search. At a false-alarm rate of one event per century, the detectable signal amplitudes are reduced up to almost an order of magnitude, most notably for the single-cycle signal morphologies. This ML-enhanced pipeline also improves the detection efficiency of compact binary mergers in a wide range of masses, from stellar mass to intermediate-mass black holes, both with circular and elliptical orbits. After excluding previously detected compact binaries, no new gravitational-wave signals are observed for the two-fold Hanford-Livingston and the three-fold Hanford-Livingston-Virgo detector networks. With the improved sensitivity of the all-sky search, we obtain the most stringent constraints on the isotropic emission of gravitational-wave energy from short-duration burst sources.

gr-qc

Addressing the challenges of detecting time-overlapping compact binary coalescences

Standard detection and analysis techniques for transient gravitational waves make the assumption that detector data contains, at most, one signal at any time. As detectors improve in sensitivity, this assumption will no longer be valid. In this paper we examine how current search techniques for transient gravitational waves will behave under the presence of more than one signal. We perform searches on data sets containing time-overlapping compact binary coalescences. This includes a modelled, matched filter search (PyCBC), and an unmodelled coherent search, coherent WaveBurst (cWB). Both of these searches are used by the LIGO-Virgo-KAGRA collaboration. We find that both searches are capable of identifying both signals correctly when the signals are dissimilar in merger time, $|Δt_c| \geq 1$ second, with PyCBC losing only $1\%$ of signals for overlapping binary black hole mergers. Both pipelines can find signal pairings within the region $|Δt_c| < 1$ second. However, clustering routines in the pipelines will cause only one of the two signals to be recovered, as such the efficiency is reduced. Within this region, we find that cWB can identify both signals. We also find that matched filter searches can be modified to provide estimates of the correct parameters for each signal.

gr-qc