We investigate the use of particle swarm optimization (PSO) algorithm for detection of gravitational-wave signals from compact binary coalescences. We show that the PSO is fast and effective in searching for gravitational wave signals. The PSO-based aligned-spin coincident multi-detector search recovers appreciably more gravitational-wave signals, for a signal-to-noise ratio (SNR) of 10, the PSO based aligned-spin search recovers approximately 26 $\%$ more events as compared to the template bank searches. The PSO-based aligned-spin coincident search uses 48k matched-filtering operations, and provides a better parameter estimation accuracy at the detection stage, as compared to the PyCBC template-bank search in LIGO's second observation run (O2) with 400k template points. We demonstrate an effective PSO-based precessing coincident search with 320k match-filtering operations per detector. We present results of an all-sky aligned-spin coherent search with 576k match-filtering operations per detector, for some examples of two-, three-, and four-detector networks constituting of the LIGO detectors in Hanford and Livingston, Virgo and KAGRA. Techniques for background estimation that are applicable to real data for PSO-based coincident and coherent searches are also presented.
Coalescing compact binary systems consisting of neutron stars and/or black holes should be detectable with upcoming advanced gravitational-wave detectors such as LIGO, Virgo, GEO and {KAGRA}. Gravitational-wave experiments to date have been riddled with non-Gaussian, non-stationary noise that makes it challenging to ascertain the significance of an event. A popular method to estimate significance is to time shift the events collected between detectors in order to establish a false coincidence rate. Here we propose a method for estimating the false alarm probability of events using variables co…
In this paper, we study an application of deep learning to the advanced LIGO and advanced Virgo coincident detection of gravitational waves (GWs) from compact binary star mergers. This deep learning method is an extension of the Deep Filtering method used by George and Huerta (2017) for multi-inputs of network detectors. Simulated coincident time series data sets in advanced LIGO and advanced Virgo detectors are analyzed for estimating source luminosity distance and sky location. As a classifier, our deep neural network (DNN) can effectively recognize the presence of GW signals when the optima…
The Multi-Band Template Analysis is a low-latency analysis pipeline for the detection of gravitational waves to triggering electromagnetic follow up observations. Coincident observation of gravitational waves and an electromagnetic counterpart will allow us to develop a complete picture of energetic astronomical events. We give an outline of the MBTA pipeline, as well as the procedure for distributing gravitational wave candidate events to our astronomical partners. We give some details of the recent work that has been done to improve the MBTA pipeline and are now making preparations for the a…
Observations of an optical source coincident with gravitational wave emission detected from a binary neutron star coalescence will improve the confidence of detection, provide host galaxy localisation, and test models for the progenitors of short gamma ray bursts. We employ optical observations of three short gamma ray bursts, 050724, 050709, 051221, to estimate the detection rate of a coordinated optical and gravitational wave search of neutron star mergers. Model R-band optical afterglow light curves of these bursts that include a jet-break are extrapolated for these sources at the sensitivi…
The multi-band template analysis (MBTA) pipeline is a low-latency coincident analysis pipeline for the detection of gravitational waves (GWs) from compact binary coalescences. MBTA runs with a low computational cost, and can identify candidate GW events online with a sub-minute latency. The low computational running cost of MBTA also makes it useful for data quality studies. Events detected by MBTA online can be used to alert astronomical partners for electromagnetic follow-up. We outline the current status of MBTA and give details of recent pipeline upgrades and validation tests that were per…
In the first two years of Gravitational Wave (GW) Astronomy, half a dozen compact binary coalescences (CBCs) have been detected. As the sensitivities and bandwidths of the detectors improve and new detectors join the network, many more sources are expected to be detected. The goal will not only be to find as many sources as possible in the data but to understand the dynamics of the sources much more precisely. Standard searches are currently restricted to a smaller parameter space which assumes aligned spins. Construction of a larger and denser parameter space, and optimising the resultant inc…
Gravitational-wave signals from compact binary coalescences are most efficiently identified through matched filter searches, which match the data against a pre-generated bank of gravitational-wave templates. Although different techniques for performing the matched filter, as well as generating the template bank, exist, currently all modelled gravitational-wave searches use templates that restrict the component spins to be aligned (or anti-aligned) with the orbital angular momentum. This means that current searches are less sensitive to gravitational-wave signals generated from binaries with ge…
Faster likelihood evaluation enhances the efficiency of gravitational wave signal analysis. We present Mode-by-mode Relative Binning (MRB), a new method designed for obtaining fast and accurate likelihoods for advanced waveform models that include spin-orbit precession effects and multiple radiation harmonics from compact binary coalescence. Leveraging the "twisting-up" procedure of constructing precessing waveform modes from non-precessing ones, the new method mitigates degrade of relative binning accuracy due to interference from superimposed modes. Additionally, we supplement algorithms for…
We evaluate how well EOBNR waveforms, obtained from the effective one-body formalism, perform in detecting gravitational wave (GW) signals from binary black hole (BBH) coalescences modelled by numerical relativity (NR) groups participating in the second edition of the numerical injection analysis (NINJA-2). In this study, NINJA-2 NR-based signals that are available in the public domain were injected in simulated Gaussian, stationary data prepared for three LIGO-Virgo detectors with early Advanced LIGO sensitivities. Here we studied only non-spinning BBH signals. A total of 2000 such signals fr…
Detection of many compact binary coalescences (CBCs) is one of the primary goals of the present and future ground-based gravitational-wave (GW) detectors. While increasing the detectors' sensitivities will be crucial in achieving this, efficient data analysis strategies can play a vital role. With given computational power in hand, efficient data analysis techniques can expand the size and dimensionality of the parameter space to search for a variety of GW sources. Matched filtering based analyses that depend on modeled signals to produce adequate signal-to-noise ratios for signal detection ma…
Max-Planck-Institut für Gravitationsphysik, Albert-Einstein-Institut（马克斯·普朗克引力物理研究所（阿尔伯特·爱因斯坦研究所））；Leibniz Universität Hannover（莱布尼茨汉诺威大学）
Gravitational waves from the coalescence of compact-binary sources are now routinely observed by Earth bound detectors. The most sensitive search algorithms convolve many different pre-calculated gravitational waveforms with the detector data and look for coincident matches between different detectors. Machine learning is being explored as an alternative approach to building a search algorithm that has the prospect to reduce computational costs and target more complex signals. In this work we construct a two-detector search for gravitational waves from binary black hole mergers using neural ne…
The advent of gravitational wave (GW) astronomy has provided us with observations of black holes more massive than those known from X-ray astronomy. However, the observation of an intermediate-mass black hole (IMBH) remains a big challenge. After their second observing run, the LIGO \& Virgo Scientific collaborations (LVC) placed upper limits on the coalescence rate density of non-precessing IMBH binaries (IMBHBs). In this article, we explore the sensitivity of two of the search pipelines used by the LVC to signals from 69 numerically simulated IMBHBs with generic spins, out of which 27 have a…
The next generation of gravitational-wave observatories will reach low frequency limits on the orders of a few Hz, thus enabling the detection of gravitational wave signals of very long duration. The run time of standard parameter estimation techniques with these long waveforms can be months or even years, making it impractical with existing Bayesian inference pipelines. Reduced order modeling and reduced order quadrature integration rule have recently been exploited as promising techniques that can greatly reduce parameter estimation computational costs. We describe a Python-based reduced ord…
We describe a hierarchical data analysis pipeline for coherently searching for gravitational wave (GW) signals from non-spinning compact binary coalescences (CBCs) in the data of multiple earth-based detectors. It assumes no prior information on the sky position of the source or the time of occurrence of its transient signals and, hence, is termed "blind". The pipeline computes the coherent network search statistic that is optimal in stationary, Gaussian noise, and allows for the computation of a suite of alternative statistics and signal-based discriminators that can improve its performance i…
Inter-University Centre for Astronomy and Astrophysics (IUCAA)（印度理工学院天文学和天体物理学跨大学中心）；Max-Planck-Institut für Gravitationsphysik (Albert-Einstein-Institut)（马克斯-普朗克引力物理研究所（阿尔伯特-爱因斯坦研究所））；Institut für Gravitationsphysik, Leibniz Universität Hannover（汉诺威莱布尼茨大学引力物理研究所）；Max Planck Institute for Gravitational Physics (Albert Einstein Institute)（马克斯·普朗克引力物理研究所（阿尔伯特·爱因斯坦研究所））
We present a novel Machine Learning (ML) based strategy to search for binary black hole (BBH) mergers in data from ground-based gravitational wave (GW) observatories. This is the first ML-based search that not only recovers all the compact binary coalescences (CBCs) in the first GW transients catalog (GWTC-1), but also makes a clean detection of GW151216 by only adding a new coincident ranking statistic (MLStat) to a standard analysis that was used for GWTC-1. In CBC searches, reducing contamination by terrestrial and instrumental transients, which create a loud noise background by triggering …
Following a major upgrade, the two advanced detectors of the Laser Interferometer Gravitational-wave Observatory (LIGO) held their first observation run between September 2015 and January 2016. With a strain sensitivity of $10^{-23}/\sqrt{\mathrm{Hz}}$ at 100 Hz, the product of observable volume and measurement time exceeded that of all previous runs within the first 16 days of coincident observation. On September 14th, 2015 the Advanced LIGO detectors observed a transient gravitational-wave signal determined to be the coalescence of two black holes [Phys. Rev. Lett. 116, 061102 (2016)], launc…
This paper develops a general framework for studying the effectiveness of networks of interferometric gravitational wave detectors and then uses it to show that enlarging the existing LIGO-VIRGO network with one or more planned or proposed detectors in Japan (LCGT), Australia, and India brings major benefits, including much larger detection rate increases than previously thought... I show that there is a universal probability distribution function (pdf) for detected SNR values, which implies that the most likely SNR value of the first detected event will be 1.26 times the search threshold. For…
Architecture Acceleration of Machine Learning Gravitational Waveform Surrogate Models
INFN, Sezione di Firenze（意大利国家核物理研究所佛罗伦萨分部）；INFN, Sezione di Pisa（意大利国家核物理研究所比萨分部）；INAF, Osservatorio di Astrofisica e Scienza dello Spazio（意大利国家天体物理研究所空间科学与天体物理观测站）；INFN, Sezione di Bologna（意大利国家核物理研究所博洛尼亚分部）
By now, tens of gravitational-wave (GW) events have been detected by the LIGO and Virgo detectors. These GWs have all been emitted by compact binary coalescence, for which we have excellent predictive models. However, there might be other sources for which we do not have reliable models. Some are expected to exist but to be very rare (e.g., supernovae), while others may be totally unanticipated. So far, no unmodeled sources have been discovered, but the lack of models makes the search for such sources much more difficult and less sensitive. We present here a search for unmodeled GW signals usi…
The detection of an electromagnetic transient which may originate from a binary neutron star merger can increase the probability that a given segment of data from the LIGO-Virgo ground-based gravitational-wave detector network contains a signal from a binary coalescence. Additional information contained in the electromagnetic signal, such as the sky location or distance to the source, can help rule out false alarms, and thus lower the necessary threshold for a detection. Here, we develop a framework for determining how much sensitivity is added to a gravitational-wave search by triggering on a…
PyCBC Live Search for Compact Binary Mergers in Advanced LIGO and Virgo's Fourth Observing Run
University of Maryland, College Park（马里兰大学帕克分校）；Institute for Cosmology and Gravitation, University of Portsmouth（朴茨茅斯宇宙学与引力研究所，朴茨茅斯大学）；Université Paris-Saclay, CNRS/IN2P3, IJCLab（巴黎-萨克雷大学，法国国家科学研究中心/欧洲核子研究学院，IJCLab）；Instituto Galego de Física de Altas Enerxías, Universidade de Santiago de Compostela（加利西亚高能物理研究所，圣地亚哥-德孔波斯特拉大学）
本文改进了 PyCBC Live 低延迟搜索管道，用于 LIGO-Virgo-KAGRA 第四次观测运行（O4），通过增强排名统计量、优化信噪比恢复和实现预警搜索，将灵敏度提高 1.7-2.3 倍，并实现 2.5-3.5 秒延迟的并合前预警。
Hyperparameter optimization of hp-greedy reduced basis for gravitational wave surrogates
CONICET（阿根廷国家科学与技术研究理事会）；Facultad de Matemática, Astronomía, Física y Computación, Universidad Nacional de Córdoba（科尔多瓦国立大学数学、天文、物理与计算机学院）；ISISTAN-CONICET Research Institute（ISISTAN-阿根廷国家科学与技术研究理事会研究所）；UNICEN University（中阿根廷国立大学）；Facultad de Ciencias Exactas y Tecnología, Universidad Nacional de Tucumán（图库曼国立大学精确科学与技术学院）
On September 14, 2015 at 09:50:45 UTC the two detectors of the Laser Interferometer Gravitational-wave Observatory (LIGO) simultaneously observed the binary black hole merger GW150914. We report the results of a matched-filter search using relativistic models of compact-object binaries that recovered GW150914 as the most significant event during the coincident observations between the two LIGO detectors from September 12 to October 20, 2015. GW150914 was observed with a matched filter signal-to-noise ratio of 24 and a false alarm rate estimated to be less than 1 event per 203 000 years, equiva…
Supplemental information for a Letter reporting the rate of binary black hole (BBH) coalescences inferred from 16 days of coincident Advanced LIGO observations surrounding the transient gravitational wave signal GW150914. In that work we reported various rate estimates whose 90\% credible intervals fell in the range $2$--$600 \, \mathrm{Gpc}^{-3} \mathrm{yr}^{-1}$. Here we give details of our method and computations, including information about our search pipelines, a derivation of our likelihood function for the analysis, a description of the astrophysical search trigger distribution expected…
