No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Search for gravitational-wave bursts in the third Advanced LIGO-Virgo run with coherent WaveBurst enhanced by machine learning
Abstract
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 a 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 twofold Hanford-Livingston and the threefold 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.
... The two ML post-processing algorithms that are employed currently are eXtreme-Gradient Boost (or XG-Boost (XGB)) and Gaussian Mixture Modelling (GMM). XGB [43,44] uses a decision tree-based ensemble learning classifying algorithm to construct a penalty factor which is multiplied with the cWB ranking statistic, widening the separation between the signal and noise distributions. GMM models the distribution of multi-dimensional cWB attributes as a superposition of Gaussians. ...
... This process ensures that when the search algorithm runs on the background data, all triggers are of noise origin. In this work we do not perform time-sliding ourselves, but rather postprocess the background produced by the O3 cWB search [44]. For the remainder of this work, we use background triggers and noise triggers interchangeably. ...
... The authors would like to thank the authors of [44] for the production of cWB triggers used for the analysis in this paper. The authors would like to thank Shubhanshu Tiwari, Edoardo Milotti and Marco Drago for interesting discussions and suggestions. ...
All-sky searches for generic short-duration astrophysical GW transients are often challenging because of noise transients. Developing novel signal-noise discriminators is crucial for GW transient searches with LIGO Scientific, Virgo, and KAGRA (LVK) detectors. In this work, we adapt a recently developed Jensen Shannon divergence (JSD)-based measure, which assesses the cross-detector parameter consistency to distinguish between weakly modeled or unmodelled astrophysical GW signals and loud noise triggers. We first extend a 2-detector JSD-based measure, developed in an earlier work, to a 3-detector network. We leverage this to modify the test statistic of the existing Coherent Waveburst (cWB)-Gaussian Mixture Modelling (GMM) algorithm for short-duration transients towards improving the search sensitivity to ad-hoc waveforms like Sine-Gaussians, Gaussian Pulses, and White Noise Bursts. We find that with the new method, which we term cWB-GMM-JSD, the sensitivity to the ad-hoc waveforms, given by , improves by at an IFAR of 10 years for the 2-detector network consisting of LHO and LLO detectors, and by at the same IFAR for the 3-detector network consisting of LHO, LLO and Virgo detectors. Finally, we apply the modified statistic in the revised data analysis pipeline on the publicly available data from the third observing run (O3) of the LIGO and Virgo detectors. Although we do not find any new event in the O3 data, we see a notable rise in the statistical significance of most of the known GW events, which further testifies to the enhancement in sensitivities.
... Supernova GWs lack the clean structure of binary mergers, instead displaying complex broad-band emission. Consequently, detection studies primarily rely on excess energy methods (Arnaud et al. 2004;Ando et al. 2005;Yokozawa et al. 2015;Hayama et al. 2015;Gossan et al. 2016;Abbott et al. 2016;Srivastava et al. 2019;Abbott et al. 2020;Halim et al. 2021;Szczepańczyk et al. 2021 Richardson et al. 2022;Afle et al. 2023;Szczepańczyk et al. 2023;Bruel et al. 2023;Szczepańczyk et al. 2024;Gill 2024), Bayesian analysis and/or principle component analysis (Summerscales et al. 2008;Powell et al. 2016Powell et al. , 2017Powell 2018;Roma et al. 2019;Afle & Brown 2021;Raza et al. 2022), and machine learning techniques (Astone et al. 2018;Chan et al. 2020;López et al. 2021;Mukherjee et al. 2021;Antelis et al. 2022;Mitra et al. 2023;Casallas-Lagos et al. 2023). ...
... However, it is unclear how large a role the differences in the noise used in Szczepańczyk et al. (2021) and the noise we use effects the comparison. Comparing our result to Szczepańczyk et al. (2023), we see that our matched-filtering method outperforms the excess energy search by almost a factor of 10 (see their Fig. 4). A direct comparison to Szczepańczyk et al. (2023) is not straight forward because they enforce a FAR of one per hundred years, whereas we do not consider false alarms when calculating the detection efficiency (see Section 5 for a discussion regarding our FAR). ...
... Comparing our result to Szczepańczyk et al. (2023), we see that our matched-filtering method outperforms the excess energy search by almost a factor of 10 (see their Fig. 4). A direct comparison to Szczepańczyk et al. (2023) is not straight forward because they enforce a FAR of one per hundred years, whereas we do not consider false alarms when calculating the detection efficiency (see Section 5 for a discussion regarding our FAR). For galactic events, the blind search methodology employed by the LVK is not the most efficient approach, and the FAR can be significantly reduced by incorporating timing information from neutrino detectors. ...
Gravitational waves from core-collapse supernovae are a promising yet challenging target for detection due to the stochastic and complex nature of these signals. Conventional detection methods for core-collapse supernovae rely on excess energy searches because matched filtering has been hindered by the lack of well-defined waveform templates. However, numerical simulations of core-collapse supernovae have improved our understanding of the gravitational wave signals they emit, which enables us, for the first time, to construct a set of templates that closely resemble predictions from numerical simulations. In this study, we investigate the possibility of detecting gravitational waves from core-collapse supernovae using a matched-filtering methods. We construct a theoretically-informed template bank and use it to recover a core-collapse supernova signal injected into real LIGO-Virgo-KAGRA detector data. We evaluate the detection efficiency of the matched-filtering approach and how well the injected signal is reconstructed. We discuss the false alarm rate of our approach and investigate the main source of false triggers. We recover 88\% of the signals injected at a distance of 1 kpc and 50% of the signals injected at 2 kpc. For more than 50% of the recovered events, the underlying signal characteristics are reconstructed within an error of 15%. We discuss the strengths and limitations of this approach and identify areas for further improvements to advance the potential of matched filtering for supernova gravitational-wave detection. We also present the open-source Python package SynthGrav used to generate the template bank.
... Recent work has seen the application of a different ML-based approach as postproduction to the cWB algorithm [43], in which the authors used the decision tree method, XGBoost, to improve the classification of signal and noise transients while maintaining unmodeled requirements to the analysis. XGBoost learns how to discriminate between typical noise and signal population features through chosen cWB summary statistics, outputting a number between 0 (noise) and 1 (signal) which weights the SNR of given events. ...
... To construct the signal model, generic band-limited white noise burst (WNB) injections are simulated to represent the wide range of signal attribute space, as in the XGBoost postproduction in [43]. The WNBs span the low-frequency range of the all-sky short search, and are designed to cover the signal parameter space over selected attributes. ...
... Note that only 10% of injected CS amplitudes fall inside the analyzed frequency band of the algorithm. Both sensitivities and GW search results are compared to studies completed with other cWB postproduction methodologies, namely the cWB standard (STD) postproduction detailed in [39], and the ML-enhanced decision tree postproduction of XGBoost, detailed in [43]. ...
We present an enhanced method for the application of Gaussian mixture modeling (GMM) to the coherent WaveBurst (cWB) algorithm in the search for short-duration gravitational wave (GW) transients. The supervised machine learning method of GMM allows for the multidimensional distributions of noise and signal to be modeled over a set of representative attributes, which aids in the classification of GW signals against noise transients (glitches) in the data. We demonstrate that updating the approach to model construction eliminates bias previously seen in the GMM analysis, increasing the robustness and sensitivity of the analysis over a wider range of burst source populations. The enhanced methodology is applied to the generic burst all-sky short search in the LIGO-Virgo full third observing run (O3), marking the first application of GMM to the 3 detector Livingston-Hanford-Virgo network. For both 2- and 3- detector networks, we observe comparable sensitivities to an array of generic signal morphologies, with significant sensitivity improvements to waveforms in the low quality factor parameter space at false alarm rates of 1 per 100 years. This proves that GMM can effectively mitigate blip glitches, which are one of the most problematic sources of noise for unmodeled GW searches. The cWB-GMM search recovers similar numbers of compact binary coalescence (CBC) events as other cWB postproduction methods, and concludes on no new gravitational wave detection after known CBC events are removed.
Published by the American Physical Society 2024
... Recent work has seen the application of a different MLbased approach to the cWB algorithm [43], in which the authors used the decision tree method of XGBoost to improve the classification of signal and noise transients while maintaining un-modelled requirements to the analysis. ...
... To construct the signal model, generic band-limited white noise burst (WNB) injections are simulated to represent the wide range of signal attribute space, as in the XGBoost post-production in [43]. The WNBs span the low-frequency range of the all-sky short search, and are designed to cover the signal parameter space over selected attributes. ...
... Both sensitivities and GW search results are compared to studies completed with other cWB post-production methodologies, namely the cWB standard (STD) postproduction detailed in [39], and the ML-enhanced decision tree post-production of XGBoost, detailed in [43]. ...
We present an enhanced method for the application of Gaussian Mixture Modelling (GMM) to the coherent WaveBurst (cWB) algorithm in the search for short-duration gravitational wave (GW) transients. The supervised Machine Learning method of GMM allows for the multi-dimensional distributions of noise and signal to be modelled over a set of representative attributes, which aids in the classification of GW signals against noise transients (glitches) in the data. We demonstrate that updating the approach to model construction eliminates bias previously seen in the GMM analysis, increasing the robustness and sensitivity of the analysis over a wider range of burst source populations. The enhanced methodology is applied to the generic burst all-sky short search in the LIGO-Virgo full third observing run (O3), marking the first application of GMM to the 3 detector Livingston-Hanford-Virgo network. For both 2- and 3- detector networks, we observe comparable sensitivities to an array of generic signal morphologies, with significant sensitivity improvements to waveforms in the low Quality factor parameter space at false alarm rates of 1 per 100 years. This proves that GMM can effectively mitigate blip glitches, which are one of the most problematic sources of noise for un-modelled GW searches. The cWB-GMM search recovers similar numbers of compact binary coalescence (CBC) events as other cWB post-production methods, and concludes on no new gravitational wave detection after known CBC events are removed.
... Over the years, different strategies to mitigate the impact of transient noises have been integrated into cWB: two estimators, called Qveto 0 and Qveto 1 , have been designed to pinpoint short-duration glitches, and recently cWB has been enhanced by a signal-noise classification with the decision-tree learning algorithm XGBoost [30]. This latter methodology exploits a set of summary statistics computed by cWB, and has shown to increase the search sensitivity for compact binary coalescence and generic GW searches [30][31][32]. Here, we propose an additional estimator, computed using the autoencoder neural network, that can be straightforwardly included in the statistics used to build the XGBoost model, further enhancing the discrimination of glitches. ...
... Recently, to automate the signal-noise separation and avoid the application of hard thresholds, a procedure based on a decision tree learning algorithm, called XGBoost [48], has been implemented. XGBoost performs a binary classification between GW signals and noise learning the differences between the population of the signal and of the noise from a list of eight cWB summary statistics that do not depend on the waveform morphology [30][31][32]. The signal population is modeled using generic white noise burst (WNB) waveforms, which are basically random noise constrained in a certain time-frequency range sampled from a random distribution. ...
... This configuration will be referred as XGBoost + AE model, while the configuration without the autoencoder statistic will be referred simply as XGBoost model. The cWB pipeline's set up and the hyperparameters employed for the XGBoost tuning are equal for the two configurations, and the same used for the generic GWT search performed with cWB enhanced by XGBoost, which provides the most stringent constraints on the isotropic emission of GW energy from burst sources to date [32]. Using these two configurations, we analyse 40 days, between February and March 2020, of coincident data between the LIGO detectors. ...
The gravitational-wave (GW) detector data are affected by short-lived instrumental or terrestrial transients, called “glitches”, which can simulate GW signals. Mitigation of glitches is particularly difficult for algorithms which target generic sources of short-duration GW transients (GWT), and do not rely on GW waveform models to distinguish astrophysical signals from noise, such as Coherent WaveBurst (cWB). This work is part of the long-term effort to mitigate transient noises in cWB, which led to the introduction of specific estimators, and a machine-learning based signal-noise classification algorithm. Here, we propose an autoencoder neural network, integrated into cWB, that learns transient noises morphologies from GW time-series. We test its performance on the glitch family known as “blip”. The resulting sensitivity to generic GWT and binary black hole mergers significantly improves when tested on LIGO detectors data from the last observation period (O3b). At false alarm rate of one event per 50 years the sensitivity volume increases up to 30% for signal morphologies similar to blip glitches. In perspective, this tool can adapt to classify different transient noise classes that may affect future observing runs, enhancing GWT searches.
... Recently, the cWB pipeline was upgraded with XGBoost (Chen and Guestrin 2016), an ensemble based boosted decision-tree algorithm, to automate the signalnoise classification of cWB events (Mishra et al 2021(Mishra et al , 2022Szczepańczyk et al 2023). Two types of input data are used: signal events from simulations and noise events from background estimations. ...
... Therefore, this approach uses the XGBoost output as a penalty factor which applies a weight between 0 (noise) and 1 (signal) to the cWB ranking statistic. This enhanced cWB pipeline was tuned to search for generic GW bursts in O3 data, where it demonstrated robustness as a model-agnostic search, and improved the allsky search sensitivity across the broad spectrum of simulated signals, ranging from a few percent improvement for sine gaussian waveforms up to factors of about 3 for gaussian pulses (Szczepańczyk et al 2023)]. The authors also report the most stringent constraints on isotropic emission of GW energy from short-duration burst sources with the enhanced cWB pipeline, improving on previous constraints by about 5% to 10% depending on the frequency of the GW signal. ...
This article provides an overview of the current state of machine learning in gravitational-wave research with interferometric detectors. Such applications are often still in their early days, but have reached sufficient popularity to warrant an assessment of their impact across various domains, including detector studies, noise and signal simulations, and the detection and interpretation of astrophysical signals. In detector studies, machine learning could be useful to optimize instruments like LIGO, Virgo, KAGRA, and future detectors. Algorithms could predict and help in mitigating environmental disturbances in real time, ensuring detectors operate at peak performance. Furthermore, machine-learning tools for characterizing and cleaning data after it is taken have already become crucial tools for achieving the best sensitivity of the LIGO--Virgo--KAGRA network. In data analysis, machine learning has already been applied as an alternative to traditional methods for signal detection, source localization, noise reduction, and parameter estimation. For some signal types, it can already yield improved efficiency and robustness, though in many other areas traditional methods remain dominant. As the field evolves, the role of machine learning in advancing gravitational-wave research is expected to become increasingly prominent. This report highlights recent advancements, challenges, and perspectives for the current detector generation, with a brief outlook to the next generation of gravitational-wave detectors.
... Rapid inference of signal parameters has also been demonstrated through neural posterior estimation, offering speedups of about 10 3 − 10 4 times over traditional Bayesian methods while maintaining agreement with them [49][50][51]. In addition, methods such as gradient boosting and Gaussian Mixture Modelling have also been used as postprocessing steps for cWB leading to an improved detection efficiency [52,53]. Generative models such as Gengli have been developed to create realistic glitches, helping to create synthetic datasets that more closely resemble real detector data [54]. ...
Gravitational wave (GW) transient searches rely on signal-noise discriminators to distinguish astrophysical signals from noise artefacts. These discriminators are typically tuned towards expected signal morphologies, which may limit their effectiveness as detector sensitivity improves and more complex signals, such as from core collapse supernovae or compact binary mergers featuring precession, higher-order harmonics, or eccentricity, become detectable. In this work, we use a Convolutional Neural Network-based approach to classify noise transients from astrophysical transients, aiming to enhance the sensitivity of existing searches. We evaluate our method on two matched filter based searches, PyCBC-IMBH and PyCBC-HM tuned for Intermediate Mass Black Hole (IMBH) binary systems. Our approach improves the sensitive volume-time reach of these searches by approximately 30% at a false alarm rate of once per 100 years. Finally, we apply our method to the first four chunks of the first half of the third observation run and demonstrate a marked improvement in significance. In particular, we significantly improve the first IMBH binary GW event GW190521 with an IFAR exceeding 42000 years.
... The implemented ML methods would learn a single feature vector derived from multi-detector analysis to perform the binary classification task. Such applications have proven successful in the context of binary black holes [35,36], gamma-ray bursts [37,38], and burst searches [39][40][41][42]. Nonetheless, these multivariate methods are not restricted to a single feature vector; they can also integrate information from several single-detector analysis [43] and other data representations, such as singular value decomposition [44] to distinguish GW signals from background glitches. ...
The direct observation of intermediate-mass black holes (IMBH) populations would not only strengthen the possible evolutionary link between stellar and supermassive black holes, but unveil the details of the pair-instability mechanism and elucidate their influence in galaxy formation. Conclusive observation of IMBHs remained elusive until the detection of gravitational-wave (GW) signal GW190521, which lies with high confidence in the mass gap predicted by the pair-instability mechanism. Despite falling in the sensitivity band of current GW detectors, IMBH searches are challenging due to their similarity to transient bursts of detector noise, known as glitches. In this proof-of-concept work, we combine a matched-filter algorithm with a Machine Learning (ML) method to differentiate IMBH signals from non-transient burst noise, known as glitches. In particular, we build a multi-layer perceptron network to perform a multi-class classification of the output triggers of matched-filter. In this way we are able to distinguish simulated GW IMBH signals from different classes of glitches that occurred during the third observing run (O3) in single detector data. We train, validate, and test our model on O3a data, reaching a true positive rate of over for simulated IMBH signals. In O3b, the true positive rate is over . We also combine data from multiple detectors to search for simulated IMBH signals in real detector noise, providing a significance measure for the output of our ML method.
... On the contrary, little or no attention has been given, even within the LISA scientific community, to the time-domain description of the detector response beyond the LWA, as well as to the combined time-frequency response. While modeled analysis is often implemented in the frequency domain, both in pipelines analyzing data from current interferometers [9][10][11][12][13] and in planned methods for future interferometers like LISA [34][35][36][37][38], the time domain and, above all, the time-frequency domain methods are at the basis of unmodeled analysis of GW transients [15][16][17][18][39][40][41][42][43]. ...
The response of a gravitational-wave (GW) interferometer is spatially modulated and is described by two antenna patterns, one for each polarization state of the waves. The antenna patterns are derived from the shape and size of the interferometer, usually under the assumption that the interferometer size is much smaller than the wavelength of the gravitational waves (long wavelength approximation, LWA). This assumption is well justified as long as the frequency of the gravitational waves is well below the free spectral range (FSR) of the Fabry-Perot cavities in the interferometer arms as it happens for current interferometers (~kHz for the LIGO interferometers and ~kHz for Virgo and KAGRA). However, the LWA can no longer be taken for granted with third--generation instruments (Einstein Telescope, Cosmic Explorer and LISA) because of their longer arms. This has been known for some time, and previous analyses have mostly been carried out in the frequency domain. In this paper, we explore the behavior of the frequency--dependent antenna patterns in the time domain and in the time--frequency domain, with specific reference to the searches of short GW transients. We analyze the profound changes in the concept of Dominant Polarization Frame, which must be generalized in a nontrivial way, we show that the conventional likelihood-based analysis of coherence in different interferometers can no longer be applied as in current analysis pipelines, and that methods based on the null stream in triangular (60{\deg}) interferometers no longer work. Overall, this paper establishes methods and tools that can be used to overcome these difficulties in the unmodeled analysis of short GW transients.
... A detailed description of the XGBoost post-production analysis is published elsewhere (Mishra et al. 2021(Mishra et al. , 2022Szczepańczyk et al. 2023). The final cWB detection statistic used for the estimation of the detection significance is the same as the one described in Mishra et al. (2022) ρ ...
Burst searches identify gravitational-wave (GW) signals in the detector data without use of a specific signal model, unlike the matched-filter searches that correlate data with simulated signal waveforms (templates). While matched filters are optimal for detection of known signals in the Gaussian noise, the burst searches can be more efficient in finding unusual events not covered by templates or those affected by non-Gaussian noise artifacts. Here, we report the detection of 3 gravitational wave signals that are uncovered by a burst search Coherent WaveBurst (cWB) optimized for the detection of binary black hole (BBH) mergers. They were found in the data from the LIGO/Virgo's third observing run (O3) with a combined significance of 3.6 . Each event appears to be a BBH merger not previously reported by the LIGO/Virgo's matched-filter searches. The most significant event has a reconstructed primary component in the upper mass gap (M), and unusually low mass ratio (), implying a dynamical or AGN origin. The 3 new events are consistent with the expected number of cWB-only detections in the O3 run (), and belong to the stellar-mass binary population with the total masses in the M range.
... The calculation of the likelihood over the sky allows for building a sky map that characterizes the probability of the GW source sky location. A new feature with respect to O3 cWB analyses has been implemented for the significance assessment -a machine learning algorithm based on XG-Boost (Mishra et al. 2022;Szczepańczyk et al. 2023). In low-latency, cWB analyzes 180 s data segments overlapping every 30 s. ...
Multi-messenger searches for binary neutron star (BNS) and neutron star-black hole (NSBH) mergers are currently one of the most exciting areas of astronomy. The search for joint electromagnetic and neutrino counterparts to gravitational wave (GW)s has resumed with Advanced LIGO (aLIGO)'s, Advanced Virgo (AdVirgo)'s and KAGRA's fourth observing run (O4). To support this effort, public semi-automated data products are sent in near real-time and include localization and source properties to guide complementary observations. Subsequent refinements, as and when available, are also relayed as updates. In preparation for O4, we have conducted a study using a simulated population of compact binaries and a Mock Data Challenge (MDC) in the form of a real-time replay to optimize and profile the software infrastructure and scientific deliverables. End-to-end performance was tested, including data ingestion, running online search pipelines, performing annotations, and issuing alerts to the astrophysics community. In this paper, we present an overview of the low-latency infrastructure as well as an overview of the performance of the data products to be released during O4 based on a MDC. We report on expected median latencies for the preliminary alert of full bandwidth searches (29.5 s) and for the creation of early warning triggers (-3.1 s), and show consistency and accuracy of released data products using the MDC. This paper provides a performance overview for LVK low-latency alert structure and data products using the MDC in anticipation of O4.
... Burst-search around the kilohertz frequency band has been studied extensively in the context of ground-based interferometric GW detectors such as LIGO and Virgo[53][54][55]. ...
Transient gravitational waves (aka gravitational wave bursts) within the nanohertz frequency band could be generated by a variety of astrophysical phenomena such as the encounter of supermassive black holes, the kinks or cusps in cosmic strings, or other as-yet-unknown physical processes. Radio-pulses emitted from millisecond pulsars could be perturbed by passing gravitational waves, hence the correlation of the perturbations in a pulsar timing array can be used to detect and characterize burst signals with a duration of years. We propose a fully Bayesian framework for the analysis of the pulsar timing array data, where the burst waveform is generically modeled by piecewise straight lines, and the waveform parameters in the likelihood can be integrated out analytically. As a result, with merely three parameters (in addition to those describing the pulsars' intrinsic and background noise), one is able to efficiently search for the existence and the sky location of {a burst signal}. If a signal is present, the posterior of the waveform can be found without further Bayesian inference. We demonstrate this model by analyzing simulated data sets containing a stochastic gravitational wave background {and a burst signal generated by the parabolic encounter of two supermassive black holes.
Progress in gravitational-wave astronomy depends upon having sensitive detectors with good data quality. Since the end of the LIGO-Virgo-KAGRA third Observing run in March 2020, detector-characterization efforts have lead to increased sensitivity of the detectors, swifter validation of gravitational-wave candidates and improved tools used for data-quality products. In this article, we discuss these efforts in detail and their impact on our ability to detect and study gravitational-waves. These include the multiple instrumental investigations that led to reduction in transient noise, along with the work to improve software tools used to examine the detectors data-quality. We end with a brief discussion on the role and requirements of detector characterization as the sensitivity of our detectors further improves in the future Observing runs.
This article provides an overview of the current state of machine learning in gravitational-wave research with interferometric detectors. Such applications are often still in their early days, but have reached sufficient popularity to warrant an assessment of their impact across various domains, including detector studies, noise and signal simulations, and the detection and interpretation of astrophysical signals. In detector studies, machine learning could be useful to optimize instruments like LIGO, Virgo, KAGRA, and future detectors. Algorithms could predict and help in mitigating environmental disturbances in real time, ensuring detectors operate at peak performance. Furthermore, machine-learning tools for characterizing and cleaning data after it is taken have already become crucial tools for achieving the best sensitivity of the LIGO–Virgo–KAGRA network. In data analysis, machine learning has already been applied as an alternative to traditional methods for signal detection, source localization, noise reduction, and parameter estimation. For some signal types, it can already yield improved efficiency and robustness, though in many other areas traditional methods remain dominant. As the field evolves, the role of machine learning in advancing gravitational-wave research is expected to become increasingly prominent. This report highlights recent advancements, challenges, and perspectives for the current detector generation, with a brief outlook to the next generation of gravitational-wave detectors.
In the existing body of literature, numerous waveforms of core collapse supernovae (CCSN) have emerged from extensive simulations conducted in high-performance computing facilities globally. These waveforms exhibit distinct characteristics related to their explosion mechanisms, influenced by parameters such as progenitor mass, angular momentum, gravitational wave energy, peak frequency, duration, and equation of state. Core collapse supernovae stand out as highly anticipated sources in LIGO’s fourth observation (O4) run, prompting dedicated efforts to detect them. The integration of machine learning, specifically convolutional neural networks (CNN), has become a pivotal avenue for analysis. This study addresses a fundamental query: how can a CNN be comprehensively trained to capture all potential CCSN signatures, optimizing accuracy? The investigation presents a multivariate classification of the entire supernova waveform landscape to strategically select training waveforms that maximize the feature space. Rigorously tested on both known and unknown waveforms, the method achieves a classification accuracy of ≥90%. This approach has been seamlessly incorporated into the multilayer signal enhancement with coherent wave burst and CNN (MuLaSEcC) analysis pipeline, showcasing promising outcomes using LIGO O3b data. Noteworthy improvements include a reduction in background by ≥99%, along with the calculation of detection efficiencies for ten contemporary explosion models. The paper evaluates the search pipeline’s performance by illustrating detection probability as a function of false alarm rate and false alarm probability. The results highlight a ≥50% detection efficiency within an SNR range of 20–35 for the ten analyzed models, whether trained or untrained. Time-frequency images of CCSN signals detected by the pipeline show broadband features of the CCSN waveforms that are predicted in the simulations.
Coalescing massive black hole binaries (MBHBs) are one of primary sources for space-based gravitational wave (GW) observations. The mergers of these binaries are expected to give rise to detectable electromagnetic (EM) emissions with a narrow time window. The premerger detection of GW signals is vital for follow-up EM observations. The conventional approach for searching GW signals involves high computational costs. In this study, we present a deep learning model to search for GW signals from MBHBs. Our model is able to process 4.7 days of simulated data within 0.01 seconds and detect GW signals several hours to days before the final merger. The model provides the possibility of the coincident GW and EM detection of MBHBs.
The analysis of gravitational-wave signals is one of the most challenging application areas of signal processing, because of the extreme weakness of these signals and of the great complexity of gravitational-wave detectors. Wavelet transforms are specially helpful in detecting and analyzing gravitational-wave transients and several analysis pipelines are based on these transforms, both continuous and discrete. While discrete wavelet transforms have distinct advantages in terms of computing efficiency, continuous wavelet transforms (CWT) produce smooth and visually stunning time-frequency maps where the wavelet energy is displayed in terms of time and frequency. In addition to wavelets, short-time Fourier transforms (STFT) and Stockwell transforms (ST) are also used, or the Q-transform, which is a Morlet waveletlike transform where the width of the Gaussian envelope is parametrized by a parameter denoted by Q [Chatterji et al., Classical Quantum Gravity 21, S1809 (2004)]. To date, the use of CWTs in gravitational-wave data analysis has been limited by the higher computational load when compared with discrete wavelets, and also by the lack of an inversion formula for wavelet families that do not satisfy the admissibility condition. In this paper we consider Morlet wavelets parametrized in the same way as the Q-transform (hence the name wavelet Q-transform) which have all the advantages of the Morlet wavelets and where the wavelet transform can be inverted with a computationally efficient specialization of the nonstandard inversion formula of Lebedeva and Postnikov [Lebedeva and Postnikov, R. Soc. Open Sci. 1, 140124 (2014)]. We also introduce a two-parameter extension (the wavelet Qp-transform) which is well adapted to chirping signals like those originating from compact binary coalescences (CBC), and show that it is also invertible just like the wavelet Q-transform. The inversion formulas of both transforms allow for effective noise filtering and produce very clean reconstructions of gravitational-wave signals. Our preliminary results indicate that the method could be well suited to perform accurate tests of general relativity by comparing modeled and unmodeled reconstructions of CBC gravitational-wave signals.
Detection confidence of the source-agnostic gravitational-wave burst search pipeline BayesWave is quantified by the log signal-versus-glitch Bayes factor, lnBS,G. A recent study shows that lnBS,G increases with the number of detectors. However, the increasing frequency of non-Gaussian noise transients (glitches) in expanded detector networks is not accounted for in the study. Glitches can mimic or mask burst signals resulting in false alarm detections, consequently reducing detection confidence. This paper presents an empirical study on the impact of false alarms on the overall performance of BayesWave, with expanded detector networks. The noise background of BayesWave for the Hanford-Livingston (HL, two-detector) and Hanford-Livingston-Virgo (HLV, three-detector) networks are measured using a set of nonastrophysical background triggers from the first half of Advanced LIGO and Advanced Virgo’s Third Observing Run (O3a). Efficiency curves are constructed by combining lnBS,G of simulated binary black hole signals with the background measurements, to characterize BayesWaves’s detection efficiency as a function of the per-trigger false alarm probability. The HL and HLV network efficiency curves are shown to be similar. A separate analysis finds that detection significance of O3 gravitational-wave candidates as measured by BayesWave are also comparable for the HL and HLV networks. Consistent results from the two independent analyses suggests that the overall burst detection performance of BayesWave does not improve with the addition of Virgo at O3a sensitivity, because the increased false alarm probability offsets the advantage of higher lnBS,G.
The gamma-ray burst GRB 221009A is among the most luminous of its kind and its proximity to Earth has made it an exceptionally rare observational event. The International Gamma-ray Astrophysics Laboratory ( INTEGRAL ) was in an optimal aspect position to use its all-sky instruments for recording the prompt emission and early gamma-ray afterglow in unprecedented detail. Following the initial detection, a swiftly scheduled follow-up observation allowed for the hard X-ray afterglow time and spectral evolution to be observed for up to almost a week. The INTEGRAL hard X-ray and soft gamma-ray observations have started to bridge the energy gap between the traditionally well-studied soft X-ray afterglow and the high-energy afterglow observed by Fermi /LAT. We discuss the possible implications of these observations for follow-ups of multi-messenger transients with hard X-ray and gamma-ray telescopes.
Gravitational-wave (GW) observations provide unique information about compact objects. As detector sensitivity increases, new astrophysical sources of GWs could emerge. Close hyperbolic encounters are one such source class: Scattering of stellar mass compact objects is expected to manifest as GW burst signals in the frequency band of current detectors. We present the search for GWs from hyperbolic encounters in the second half of the third Advanced LIGO-Virgo observing run (O3b). We perform a model-informed search with a machine-learning enhanced Coherent WaveBurst algorithm. No significant event has been identified in addition to known detections of compact binary coalescences. We inject in the O3b data nonspinning third post-Newtonian order accurate hyperbolic encounter model with component masses between [2,100]M⊙, impact parameter in [60,100]GM/c2, and eccentricity in [1.05, 1.6]. We further discuss the properties of the simulation recovered. For the first time, we report the sensitivity volume achieved for such sources, which for O3b data reaches up to 3.9±1.4×105 Mpc3 yr for compact objects with masses in the range [20,40]M⊙, corresponding to a rate density upper limit of 0.589±0.094×10−5 Mpc−3 yr−1. Finally, we present a projected sensitive volume for the next observing runs of current detectors, namely, O4 and O5.
Transient gravitational waves (aka gravitational wave bursts) within the nanohertz frequency band could be generated by a variety of astrophysical phenomena such as the encounter of supermassive black holes, the kinks or cusps in cosmic strings, or other as-yet-unknown physical processes. Radio pulses emitted from millisecond pulsars could be perturbed by passing gravitational waves; hence, the correlation of the perturbations in a pulsar timing array can be used to detect and characterize burst signals with a duration of O(1–10) years. We propose a fully Bayesian framework for the analysis of the pulsar-timing-array data, where the burst waveform is generically modeled by piecewise straight lines, and the waveform parameters in the likelihood can be integrated out analytically. As a result, with merely three parameters (in addition to those describing the pulsars’ intrinsic and background noise), one is able to efficiently search for the existence and the sky location of a burst signal. If a signal is present, the posterior of the waveform can be found without further Bayesian inference. We demonstrate this model by analyzing simulated datasets containing a stochastic gravitational wave background and a burst signal generated by the parabolic encounter of two supermassive black holes.
We investigate the final collapse of rotating and non-rotating pulsational pair-instability supernova progenitors with zero-age-main-sequence masses of 60, 80, and 115 M⊙ and iron cores between 2.37 M⊙ and 2.72 M⊙ by 2D hydrodynamics simulations. Using the general relativistic NADA-FLD code with energy-dependent three-flavor neutrino transport by flux-limited diffusion allows us to follow the evolution beyond the moment when the transiently forming neutron star (NS) collapses to a black hole (BH), which happens within 350–580 ms after bounce in all cases. Because of high neutrino luminosities and mean energies, neutrino heating leads to shock revival within ≲ 250 ms post bounce in all cases except the rapidly rotating 60 M⊙ model. In the latter case, centrifugal effects support a 10 per cent higher NS mass but reduce the radiated neutrino luminosities and mean energies by ∼20 per cent and ∼10 per cent, respectively, and the neutrino-heating rate by roughly a factor of two compared to the non-rotating counterpart. After BH formation, the neutrino luminosities drop steeply but continue on a 1–2 orders of magnitude lower level for several 100 ms because of aspherical accretion of neutrino and shock-heated matter, before the ultimately spherical collapse of the outer progenitor shells suppresses the neutrino emission to negligible values. In all shock-reviving models BH accretion swallows the entire neutrino-heated matter and the explosion energies decrease from maxima around 1.5 × 1051 erg to zero within a few seconds latest. Nevertheless, the shock or a sonic pulse moves outward and may trigger mass loss, which we estimate by long-time simulations with the Prometheus code. We also provide gravitational-wave signals.
There is some weak evidence that the black hole merger named GW190521 had a non-zero eccentricity1,2. In addition, the masses of the component black holes exceeded the limit predicted by stellar evolution3. The large masses can be explained by successive mergers4,5, which may be efficient in gas disks surrounding active galactic nuclei, but it is difficult to maintain an eccentric orbit all the way to the merger, as basic physics would argue for circularization6. Here we show that active galactic nuclei disk environments can lead to an excess of eccentric mergers, if the interactions between single and binary black holes are frequent5 and occur with mutual inclinations of less than a few degrees. We further illustrate that this eccentric population has a different distribution of the inclination between the spin vectors of the black holes and their orbital angular momentum at merger7, referred to as the spin–orbit tilt, compared with the remaining circular mergers. The accretion disk environments surrounding active galactic nuclei are potential locations where there is an excess of eccentric mergers of large black holes, which have different spin–orbit tilts compared with circular mergers.
The origin of black hole mergers discovered by the LIGO¹ and Virgo² gravitational-wave observatories is currently unknown. GW1905213,4 is the heaviest black hole merger detected so far. Its observed high mass and possible spin-induced orbital precession could arise from the binary having formed following a close encounter. An observational signature of close encounters is eccentric binary orbit5–7; however, this feature is currently difficult to identify due to the lack of suitable gravitational waveforms. No eccentric merger has been previously found⁸. Here we report 611 numerical relativity simulations covering the full eccentricity range and an estimation approach to probe the eccentricity of mergers. Our set of simulations corresponds to ~10⁵ waveforms, comparable to the number used in gravitational-wave searches, albeit with coarser mass ratio and spin resolution. We applied our approach to GW190521 and found that it is most consistent with a highly eccentric (e=0.69−0.22+0.17; 90% credible level) merger within our set of waveforms. This interpretation is supported over a non-eccentric merger with >10 odds ratio if ≳10% of GW190521-like mergers are highly eccentric. Detectable orbital eccentricity would be evidence against an isolated binary origin, which is otherwise difficult to rule out on the basis of observed mass and spin9,10.
We investigate observable signatures of a first-order quantum chromodynamics (QCD) phase transition in the context of core-collapse supernovae. To this end, we conduct axially symmetric numerical relativity simulations with multi-energy neutrino transport, using a hadron–quark hybrid equation of state (EOS). We consider four nonrotating progenitor models, whose masses range from 9.6 to 70 M ⊙ . We find that the two less-massive progenitor stars (9.6 and 11.2 M ⊙ ) show a successful explosion, which is driven by the neutrino heating. They do not undergo the QCD phase transition and leave behind a neutron star. As for the more massive progenitor stars (50 and 70 M ⊙ ), the proto-neutron star (PNS) core enters the phase transition region and experiences the second collapse. Because of a sudden stiffening of the EOS entering to the pure quark matter regime, a strong shock wave is formed and blows off the PNS envelope in the 50 M ⊙ model. Consequently the remnant becomes a quark core surrounded by hadronic matter, leading to the formation of the hybrid star. However, for the 70 M ⊙ model, the shock wave cannot overcome the continuous mass accretion and it readily becomes a black hole. We find that the neutrino and gravitational wave (GW) signals from supernova explosions driven by the hadron–quark phase transition are detectable for the present generation of neutrino and GW detectors. Furthermore, the analysis of the GW detector response reveals unique kHz signatures, which will allow us to distinguish this class of supernova explosions from failed and neutrino-driven explosions.
As the Advanced LIGO and Advanced Virgo interferometers, soon to be joined by the KAGRA interferometer, increase their sensitivity, they detect an ever-larger number of gravitational waves with a significant presence of higher multipoles in addition to the dominant (2, 2) multipole. These higher multipoles can be detected with different approaches, such as the minimally-modeled burst search methods, and here we discuss one such approach based on the coherent WaveBurst pipeline (cWB). During the inspiral phase the higher multipoles produce chirps whose instantaneous frequency is a multiple of the dominant (2, 2) multipole, and here we describe how cWB can be used to detect these spectral features. The search is performed within suitable regions of the time-frequency representation; their shape is determined by optimizing the Receiver Operating Characteristics. This novel method has already been used in the GW190814 discovery paper (Astrophys. J. Lett. 896 L44) and is very fast and flexible. Here we describe in full detail the procedure used to detect the (3, 3) multipole in GW190814 as well as searches for other higher multipoles during the inspiral phase, and apply it to another event that displays higher multipoles, GW190412, replicating the results obtained with different methods. The procedure described here can be used for the fast analysis of higher multipoles and to support the findings obtained with the model-based Bayesian parameter estimates.
We performed a detailed analysis of the detectability of a wide range of gravitational waves derived from core-collapse supernova simulations using gravitational-wave detector noise scaled to the sensitivity of the upcoming fourth and fifth observing runs of the Advanced LIGO, Advanced Virgo, and KAGRA. We use the coherent WaveBurst algorithm, which was used in the previous observing runs to search for gravitational waves from core-collapse supernovae. As coherent WaveBurst makes minimal assumptions on the morphology of a gravitational-wave signal, it can play an important role in the first detection of gravitational waves from an event in the Milky Way. We predict that signals from neutrino-driven explosions could be detected up to an average distance of 10 kpc, and distances of over 100 kpc can be reached for explosions of rapidly-rotating progenitor stars. An estimated minimum signal-to-noise ratio of 10–25 is needed for the signals to be detected. We quantify the accuracy of the waveforms reconstructed with coherent WaveBurst and we determine that the most challenging signals to reconstruct are those produced in long-duration neutrino-driven explosions, and models that form black holes a few seconds after the core bounce.
After the detection of gravitational waves from compact binary coalescences, the search for transient gravitational-wave signals with less well-defined waveforms for which matched filtering is not well suited is one of the frontiers for gravitational-wave astronomy. Broadly classified into “short” ≲1 s and “long” ≳1 s duration signals, these signals are expected from a variety of astrophysical processes, including non-axisymmetric deformations in magnetars or eccentric binary black hole coalescences. In this work, we present a search for long-duration gravitational-wave transients from Advanced LIGO and Advanced Virgo’s third observing run from April 2019 to March 2020. For this search, we use minimal assumptions for the sky location, event time, waveform morphology, and duration of the source. The search covers the range of 2–500 s in duration and a frequency band of 24–2048 Hz. We find no significant triggers within this parameter space; we report sensitivity limits on the signal strength of gravitational waves characterized by the root-sum-square amplitude hrss as a function of waveform morphology. These hrss limits improve upon the results from the second observing run by an average factor of 1.8.
We search for gravitational-wave signals produced by cosmic strings in the Advanced LIGO and Virgo full O3 dataset. Search results are presented for gravitational waves produced by cosmic string loop features such as cusps, kinks, and, for the first time, kink-kink collisions. A template-based search for short-duration transient signals does not yield a detection. We also use the stochastic gravitational-wave background energy density upper limits derived from the O3 data to constrain the cosmic string tension Gμ as a function of the number of kinks, or the number of cusps, for two cosmic string loop distribution models. Additionally, we develop and test a third model that interpolates between these two models. Our results improve upon the previous LIGO–Virgo constraints on Gμ by 1 to 2 orders of magnitude depending on the model that is tested. In particular, for the one-loop distribution model, we set the most competitive constraints to date: Gμ≲4×10−15. In the case of cosmic strings formed at the end of inflation in the context of grand unified theories, these results challenge simple inflationary models.
We report on gravitational-wave discoveries from compact binary coalescences detected by Advanced LIGO and Advanced Virgo in the first half of the third observing run (O3a) between 1 April 2019 15 ∶ 00 UTC and 1 October 2019 15 ∶ 00 UTC. By imposing a false-alarm-rate threshold of two per year in each of the four search pipelines that constitute our search, we present 39 candidate gravitational-wave events. At this threshold, we expect a contamination fraction of less than 10%. Of these, 26 candidate events were reported previously in near-real time through gamma-ray coordinates network notices and circulars; 13 are reported here for the first time. The catalog contains events whose sources are black hole binary mergers up to a redshift of approximately 0.8, as well as events whose components cannot be unambiguously identified as black holes or neutron stars. For the latter group, we are unable to determine the nature based on estimates of the component masses and spins from gravitational-wave data alone. The range of candidate event masses which are unambiguously identified as binary black holes (both objects ≥ 3 M ⊙ ) is increased compared to GWTC-1, with total masses from approximately 14 M ⊙ for GW190924_021846 to approximately 150 M ⊙ for GW190521. For the first time, this catalog includes binary systems with significantly asymmetric mass ratios, which had not been observed in data taken before April 2019. We also find that 11 of the 39 events detected since April 2019 have positive effective inspiral spins under our default prior (at 90% credibility), while none exhibit negative effective inspiral spin. Given the increased sensitivity of Advanced LIGO and Advanced Virgo, the detection of 39 candidate events in approximately 26 weeks of data (approximately 1.5 per week) is consistent with GWTC-1.
Published by the American Physical Society 2021
We report on the population of 47 compact binary mergers detected with a false-alarm rate of <1 yr(-1) in the second LIGO-Virgo Gravitational-Wave Transient Catalog. We observe several characteristics of the merging binary black hole (BBH) population not discernible until now. First, the primary mass spectrum contains structure beyond a power law with a sharp high-mass cutoff; it is more consistent with a broken power law with a break at 39.7(-9.1)(+20.3) M-circle dot or a power law with a Gaussian feature peaking at 33.1(-5.6)(+4.0) M-circle dot (90% credible interval). While the primary mass distribution must extend to similar to 65 M-circle dot or beyond, only 2.9(-1.7)(+3.5)% of systems have primary masses greater than 45 M-circle dot. Second, we find that a fraction of BBH systems have component spins misaligned with the orbital angular momentum, giving rise to precession of the orbital plane. Moreover, 12%-44% of BBH systems have spins tilted by more than 90 degrees, giving rise to a negative effective inspiral spin parameter, chi(eff). Under the assumption that such systems can only be formed by dynamical interactions, we infer that between 25% and 93% of BBHs with nonvanishing vertical bar chi(eff)vertical bar > 0.01 are dynamically assembled. Third, we estimate merger rates, finding R-BBH = 23.9(-8.6)(+14.3) Gpc(-3) yr(-1) for BBHS and R-BNS = 320(-240)(+490) Gpc(-3) yr(-1) for binary neutron stars. We find that the BBH rate likely increases with redshift (85% credibility) but not faster than the star formation rate (86% credibility). Additionally, we examine recent exceptional events in the context of our population models, finding that the asymmetric masses of GW190412 and the high component masses of GW190521 are consistent with our models, but the low secondary mass of GW190814 makes it an outlier.
coherent WaveBurst (cWB) is a highly configurable pipeline designed to detect a broad range of gravitational-wave (GW) transients in the data of the worldwide network of GW detectors. The algorithmic core of cWB is a time–frequency analysis with the Wilson–Daubechies–Meyer wavelets aimed at the identification of GW events without prior knowledge of the signal waveform. cWB has been in active development since 2003 and it has been used to analyze all scientific data collected by the LIGO-Virgo detectors ever since. On September 14, 2015, the cWB low-latency search detected the first gravitational-wave event, GW150914, a merger of two black holes. In 2019, a public open-source version of cWB has been released with GPLv3 license.
The detection of gravitational waves from mergers of tens of Solar mass black hole binaries has led to a surge in interest in primordial black holes (PBHs) as a dark matter candidate. We aim to provide a (relatively) concise overview of the status of PBHs as a dark matter candidate, circa Summer 2020. First we review the formation of PBHs in the early Universe, focussing mainly on PBHs formed via the collapse of large density perturbations generated by inflation. Then we review the various current and future constraints on the present day abundance of PBHs. We conclude with a discussion of the key open questions in this field.
We present our current best estimate of the plausible observing scenarios for the Advanced LIGO, Advanced Virgo and KAGRA gravitational-wave detectors over the next several years, with the intention of providing information to facilitate planning for multi-messenger astronomy with gravitational waves. We estimate the sensitivity of the network to transient gravitational-wave signals for the third (O3), fourth (O4) and fifth observing (O5) runs, including the planned upgrades of the Advanced LIGO and Advanced Virgo detectors. We study the capability of the network to determine the sky location of the source for gravitational-wave signals from the inspiral of binary systems of compact objects, that is binary neutron star, neutron star–black hole, and binary black hole systems. The ability to localize the sources is given as a sky-area probability, luminosity distance, and comoving volume. The median sky localization area (90% credible region) is expected to be a few hundreds of square degrees for all types of binary systems during O3 with the Advanced LIGO and Virgo (HLV) network. The median sky localization area will improve to a few tens of square degrees during O4 with the Advanced LIGO, Virgo, and KAGRA (HLVK) network. During O3, the median localization volume (90% credible region) is expected to be on the order of 105,106,107Mpc3 for binary neutron star, neutron star–black hole, and binary black hole systems, respectively. The localization volume in O4 is expected to be about a factor two smaller than in O3. We predict a detection count of 1-1+12(10-10+52) for binary neutron star mergers, of 0-0+19(1-1+91) for neutron star–black hole mergers, and 17-11+22(79-44+89) for binary black hole mergers in a one-calendar-year observing run of the HLV network during O3 (HLVK network during O4). We evaluate sensitivity and localization expectations for unmodeled signal searches, including the search for intermediate mass black hole binary mergers.
On May 21, 2019 at 03:02:29 UTC Advanced LIGO and Advanced Virgo observed a short duration gravitational-wave signal, GW190521, with a three-detector network signal-to-noise ratio of 14.7, and an estimated false-alarm rate of 1 in 4900 yr using a search sensitive to generic transients. If GW190521 is from a quasicircular binary inspiral, then the detected signal is consistent with the merger of two black holes with masses of 8 5 − 14 + 21 M ⊙ and 6 6 − 18 + 17 M ⊙ (90% credible intervals). We infer that the primary black hole mass lies within the gap produced by (pulsational) pair-instability supernova processes, with only a 0.32% probability of being below 65 M ⊙ . We calculate the mass of the remnant to be 14 2 − 16 + 28 M ⊙ , which can be considered an intermediate mass black hole (IMBH). The luminosity distance of the source is 5.3 − 2.6 + 2.4 Gpc , corresponding to a redshift of 0.82 − 0.34 + 0.28 . The inferred rate of mergers similar to GW190521 is 0.13 − 0.11 + 0.30 Gpc − 3 yr − 1 .
Published by the American Physical Society 2020
We report the observation of a compact binary coalescence involving a 22.2–24.3 M_⊙ black hole and a compact object with a mass of 2.50–2.67 M_⊙ (all measurements quoted at the 90% credible level). The gravitational-wave signal, GW190814, was observed during LIGO's and Virgo's third observing run on 2019 August 14 at 21:10:39 UTC and has a signal-to-noise ratio of 25 in the three-detector network. The source was localized to 18.5 deg² at a distance of 241_(-45)^(+41) Mpc; no electromagnetic counterpart has been confirmed to date. The source has the most unequal mass ratio yet measured with gravitational waves, 0.112_(-0.009)^(+0.008), and its secondary component is either the lightest black hole or the heaviest neutron star ever discovered in a double compact-object system. The dimensionless spin of the primary black hole is tightly constrained to ≤ 0.07. Tests of general relativity reveal no measurable deviations from the theory, and its prediction of higher-multipole emission is confirmed at high confidence. We estimate a merger rate density of 1–23 Gpc⁻³ yr⁻¹ for the new class of binary coalescence sources that GW190814 represents. Astrophysical models predict that binaries with mass ratios similar to this event can form through several channels, but are unlikely to have formed in globular clusters. However, the combination of mass ratio, component masses, and the inferred merger rate for this event challenges all current models of the formation and mass distribution of compact-object binaries.
Based on the prior O1–O2 observing runs, about 30% of the data collected by Advanced LIGO and Virgo in the next observing runs are expected to be single-interferometer data, i.e. they will be collected at times when only one detector in the network is operating in observing mode. Searches for gravitational-wave signals from supernova events do not rely on matched filtering techniques because of the stochastic nature of the signals. If a Galactic supernova occurs during single-interferometer times, separation of its unmodelled gravitational-wave signal from noise will be even more difficult due to lack of coherence between detectors. We present a novel machine learning method to perform single-interferometer supernova searches based on the standard LIGO-Virgo coherent WaveBurst pipeline. We show that the method may be used to discriminate Galactic gravitational-wave supernova signals from noise transients, decrease the false alarm rate of the search, and improve the supernova detection reach of the detectors.
When formed through dynamical interactions, stellar-mass binary black holes (BBHs) may retain eccentric orbits (e > 0.1 at 10 Hz) detectable by ground-based gravitational-wave detectors. Eccentricity can therefore be used to differentiate dynamically formed binaries from isolated BBH mergers. Current template-based gravitational-wave searches do not use waveform models associated with eccentric orbits, rendering the search less efficient for eccentric binary systems. Here we present the results of a search for BBH mergers that inspiral in eccentric orbits using data from the first and second observing runs (O1 and O2) of Advanced LIGO and Advanced Virgo. We carried out the search with the coherent WaveBurst algorithm, which uses minimal assumptions on the signal morphology and does not rely on binary waveform templates. We show that it is sensitive to binary mergers with a detection range that is weakly dependent on eccentricity for all bound systems. Our search did not identify any new binary merger candidates. We interpret these results in light of eccentric binary formation models. We rule out formation channels with rates greater than or similar to 100 Gpc(-3) yr(-1) for e > 0.1, assuming a black hole mass spectrum with a power-law index less than or similar to 2.
We present the results from three gravitational-wave searches for coalescing compact binaries with component masses above 1 M ⊙ during the first and second observing runs of the advanced gravitational-wave detector network. During the first observing run ( O 1 ), from September 12, 2015 to January 19, 2016, gravitational waves from three binary black hole mergers were detected. The second observing run ( O 2 ), which ran from November 30, 2016 to August 25, 2017, saw the first detection of gravitational waves from a binary neutron star inspiral, in addition to the observation of gravitational waves from a total of seven binary black hole mergers, four of which we report here for the first time: GW170729, GW170809, GW170818, and GW170823. For all significant gravitational-wave events, we provide estimates of the source properties. The detected binary black holes have total masses between 18.6 − 0.7 + 3.2 M ⊙ and 84.4 − 11.1 + 15.8 M ⊙ and range in distance between 320 − 110 + 120 and 2840 − 1360 + 1400 Mpc . No neutron star–black hole mergers were detected. In addition to highly significant gravitational-wave events, we also provide a list of marginal event candidates with an estimated false-alarm rate less than 1 per 30 days. From these results over the first two observing runs, which include approximately one gravitational-wave detection per 15 days of data searched, we infer merger rates at the 90% confidence intervals of 110 − 3840 Gpc − 3 y − 1 for binary neutron stars and 9.7 − 101 Gpc − 3 y − 1 for binary black holes assuming fixed population distributions and determine a neutron star–black hole merger rate 90% upper limit of 610 Gpc − 3 y − 1 .
Published by the American Physical Society 2019
Blip glitches are short noise transients present in data from ground-based gravitational-wave observatories. These glitches resemble the gravitational-wave signature of massive binary black hole mergers. Hence, the sensitivity of transient gravitational-wave searches to such high-mass systems and other potential short duration sources is degraded by the presence of blip glitches. The origin and rate of occurrence of this type of glitch have been largely unknown. In this paper we explore the population of blip glitches in Advanced LIGO during its first and second observing runs. On average, we find that Advanced LIGO data contains approximately two blip glitches per hour of data. We identify four subsets of blip glitches correlated with detector auxiliary or environmental sensor channels, however the physical causes of the majority of blips remain unclear.
We derive from first principles a third post-Newtonian (3PN) accurate Keplerian-type parametric solution to describe PN accurate dynamics of nonspinning compact binaries in hyperbolic orbits. Orbital elements and functions of the parametric solution are obtained in terms of the conserved orbital energy and angular momentum in both Arnowitt-Deser-Misner-type and modified harmonic coordinates. Elegant checks are provided that include a modified analytic continuation prescription to obtain our independent hyperbolic parametric solution from its eccentric version. A prescription to model gravitational wave polarization states for hyperbolic compact binaries experiencing 3.5PN accurate orbital motion is presented that employs our 3PN accurate parametric solution.
Cosmic strings are topological defects which can be formed in grand unified theory scale phase transitions in the early universe. They are also predicted to form in the context of string theory. The main mechanism for a network of Nambu-Goto cosmic strings to lose energy is through the production of loops and the subsequent emission of gravitational waves, thus offering an experimental signature for the existence of cosmic strings. Here we report on the analysis conducted to specifically search for gravitational-wave bursts from cosmic string loops in the data of Advanced LIGO 2015-2016 observing run (O1). No evidence of such signals was found in the data, and as a result we set upper limits on the cosmic string parameters for three recent loop distribution models. In this paper, we initially derive constraints on the string tension Gμ and the intercommutation probability, using not only the burst analysis performed on the O1 data set but also results from the previously published LIGO stochastic O1 analysis, pulsar timing arrays, cosmic microwave background and big-bang nucleosynthesis experiments. We show that these data sets are complementary in that they probe gravitational waves produced by cosmic string loops during very different epochs. Finally, we show that the data sets exclude large parts of the parameter space of the three loop distribution models we consider.
This is a review article on the primordial black holes (PBHs), with particular focus on the massive ones () which have not evaporated by the present epoch by the Hawking radiation. By the detections of gravitational waves by LIGO, we have gained a completely novel tool to observationally search for PBHs complementary to the electromagnetic waves. Based on the perspective that gravitational-wave astronomy will make a significant progress in the next decades, a purpose of this article is to give a comprehensive review covering a wide range of topics on PBHs. After discussing PBH formation as well as several inflation models leading to PBH production, we summarize various existing and future observational constraints. We then present topics on formation of PBH binaries, gravitational waves from PBH binaries, various observational tests of PBHs by using gravitational waves.
We study the final fate of a very massive star by performing full general relativistic (GR), three-dimensional (3D) simulation with three-flavor multi-energy neutrino transport. Utilizing a 70 solar mass zero metallicity progenitor, we self-consistently follow the radiation-hydrodynamics from the onset of gravitational core-collapse until the second collapse of the proto-neutron star (PNS), leading to black hole (BH) formation. Our results show that the BH formation occurs at a post-bounce time of ~300 ms for the 70 Msun star. This is significantly earlier than those in the literature where lower mass progenitors were employed. At a few ~10 ms before BH formation, we find that the stalled bounce shock is revived by intense neutrino heating from the very hot PNS, which is aided by violent convection behind the shock. In the context of 3D-GR core-collapse modeling with detailed neutrino transport, our numerical results present the first evidence to validate the fallback scenario of the 70 Msun star, where the neutrino-driven shock revival precedes the BH formation. We also analyze the gravitational-wave and neutrino emission, both of which possess characteristic signatures of the second collapse.
We present results from general-relativistic (GR) three-dimensional (3D) core-collapse simulations with approximate neutrino transport for three non-rotating progenitors (11.2, 15, and 40 Msun) using different nuclear equations of state (EOSs). We find that the combination of progenitor's higher compactness at bounce and the use of softer EOS leads to stronger activity of the standing accretion shock instability (SASI). We confirm previous predications that the SASI produces characteristic time modulations both in neutrino and gravitational-wave (GW) signals. By performing a correlation analysis of the SASI-modulated neutrino and GW signals, we find that the correlation becomes highest when we take into account the time-delay effect due to the advection of material from the neutrino sphere to the proto-neutron star core surface. Our results suggest that the correlation of the neutrino and GW signals, if detected, would provide a new signature of the vigorous SASI activity in the supernova core, which can be hardly seen if neutrino-convection dominates over the SASI.
In this work, we use the coherent WaveBurst (cWB) pipeline enhanced with machine learning (ML) to search for binary black hole (BBH) mergers in the Advanced LIGO-Virgo strain data from the third observing run. We detect, with equivalent or higher significance, all gravitational-wave (GW) events previously reported by the standard cWB search for BBH mergers in the third GW Transient Catalog. The ML-enhanced cWB search identifies five additional GW candidate events from the catalog that were previously missed by the standard cWB search. Moreover, we identify three marginal candidate events not listed in third GW Transient Catalog. For simulated events distributed uniformly in a fiducial volume, we improve the sensitive hypervolume with respect to the standard cWB search by approximately 28% and 34% for the stellar-mass and intermediate mass black hole binary mergers respectively, detected with a false-alarm rate less than 1/100 yr−1. We show the robustness of the ML-enhanced search for detection of generic BBH signals by reporting increased sensitivity to the spin-precessing and eccentric BBH events as compared to the standard cWB search. Furthermore, we compare the improvement of the ML-enhanced cWB search for different detector networks.
With the release of the third Gravitational-Wave Transient Catalogue (GWTC-3), 90 observations of compact-binary mergers by Virgo and LIGO detectors are confirmed. Some of these mergers are suspected to have occurred in star clusters. The density of black holes at the cores of these clusters is so high that mergers can occur through a few generations forming increasingly massive black holes. These conditions also make it possible for three black holes to interact, most likely via single-binary encounters. In this paper, we present a first study of how often such encounters can happen in nuclear star clusters (NSCs) as a function of redshift and whether these encounters are observable by gravitational-wave (GW) detectors. This study focuses on effectively hyperbolic encounters leaving out the resonant encounters. We find that in NSCs single-binary encounters occur rarely compared to binary mergers and that hyperbolic encounters most likely produce the strongest GW emission below the observation band of terrestrial GW detectors. While several of them can be expected to occur per year with peak energy in the LISA band, their amplitude is low, and detection by LISA seems improbable.
Neutron stars are known to show accelerated spin-up of their rotational frequency called a glitch. Highly magnetized rotating neutron stars (pulsars) are frequently observed by radio telescopes (and in other frequencies), where the glitch is observed as irregular arrival times of pulses which are otherwise very regular. A glitch in an isolated neutron star can excite the fundamental (f)-mode oscillations which can lead to gravitational wave generation. This gravitational wave signal associated with stellar fluid oscillations has a damping time of 10–200 ms and occurs at the frequency range between 2.2–2.8 kHz for the equation of state and mass range considered in this work, which is within the detectable range of the current generation of ground-based detectors. Electromagnetic observations of pulsars (and hence pulsar glitches) require the pulsar to be oriented so that the jet is pointed toward the detector, but this is not a requirement for gravitational wave emission which is more isotropic and not jetlike. Hence, gravitational wave observations have the potential to uncover nearby neutron stars where the jet is not pointed towards the Earth. In this work, we study the prospects of finding glitching neutron stars using a generic all-sky search for short-duration gravitational wave transients. The analysis covers the high-frequency range from 1–4 kHz of LIGO–Virgo detectors for signals up to a few seconds. We set upper limits for the third observing run of the LIGO–Virgo detectors and present the prospects for upcoming observing runs of LIGO, Virgo, KAGRA, and LIGO India. We find the detectable glitch size will be around 10−5 Hz for the fifth observing run for pulsars with spin frequencies and distances comparable to the Vela pulsar. We also present the prospects of localizing the direction in the sky of these sources with gravitational waves alone, which can facilitate electromagnetic follow-up. We find that for the five detector configuration, the localization capability for a glitch size of 10−5 Hz is around 132 deg2 at 1σ confidence for 50% of events with distance and spin frequency as that of Vela.
Dense astrophysical environments like globular clusters and galactic nuclei can host hyperbolic encounters of black holes which can lead to gravitational-wave driven capture. There are several astrophysical models which predict a fraction of binary black hole mergers to come from these radiation-driven capture scenarios. In this paper, we present the sensitivity of a search toward gravitational-wave driven capture events for O3, the third observing run of LIGO and Virgo. We use capture waveforms produced by numerical relativity simulations covering four different mass ratios and at least two different values of initial angular momentum per mass ratio. We employed the most generic search for short-duration transients in O3 to evaluate the search sensitivity in this parameter space for a wide range in total mass in terms of visible spacetime volume. From the visible spacetime volume we determine for the first time the merger rate upper limit of such systems. The most stringent estimate of rate upper limits at 90% confidence is 0.2 Gpc−3 yr−1 for an equal mass 200 M⊙ binary. Furthermore, in recent studies the event GW190521 has been suggested to be a capture event. With this interpretation of GW190521, we find the merger rate of similar events to be 0.47 Gpc−3 yr−1.
Coherent WaveBurst is a generic, multidetector gravitational wave burst search based on the excess power approach. The coherent WaveBurst algorithm currently employed in the all-sky short-duration gravitational wave burst search uses a conditional approach on selected attributes in the multidimensional event attribute space to distinguish between noisy events from that of astrophysical origin. We have been developing a supervised machine learning approach based on the Gaussian mixture modeling to model the attribute space for signals as well as noise events to enhance the probability of burst detection [Gayathri et al.Phys. Rev. D 102, 104023 (2020)]. We further extend the Gaussian mixture model approach to the all-sky short-duration coherent WaveBurst search as a postprocessing step on events from the first half of the third observing run (O3a). We show an improvement in sensitivity to generic gravitational wave burst signal morphologies as well as the astrophysical source such as core-collapse supernova models due to the application of our Gaussian mixture model approach to coherent WaveBurst triggers. The Gaussian mixture model method recovers the gravitational wave signals from massive compact binary coalescences identified by coherent WaveBurst targeted for binary black holes in GWTC-2, with better significance than the all-sky coherent WaveBurst search. No additional significant gravitational wave bursts are observed.
This paper presents the results of a search for generic short-duration gravitational-wave transients in data from the third observing run of Advanced LIGO and Advanced Virgo. Transients with durations of milliseconds to a few seconds in the 24–4096 Hz frequency band are targeted by the search, with no assumptions made regarding the incoming signal direction, polarization, or morphology. Gravitational waves from compact binary coalescences that have been identified by other targeted analyses are detected, but no statistically significant evidence for other gravitational wave bursts is found. Sensitivities to a variety of signals are presented. These include updated upper limits on the source rate density as a function of the characteristic frequency of the signal, which are roughly an order of magnitude better than previous upper limits. This search is sensitive to sources radiating as little as ∼10−10 M⊙c2 in gravitational waves at ∼70 Hz from a distance of 10 kpc, with 50% detection efficiency at a false alarm rate of one per century. The sensitivity of this search to two plausible astrophysical sources is estimated: neutron star f modes, which may be excited by pulsar glitches, as well as selected core-collapse supernova models.
By probing the population of binary black hole (BBH) mergers detected by LIGO-Virgo, we can infer properties about the underlying black hole formation channels. A mechanism known as pair-instability (PI) supernova is expected to prevent the formation of black holes from stellar collapse with mass greater than ∼40–65 M⊙ and less than ∼120 M⊙. Any BBH merger detected by LIGO-Virgo with a component black hole in this so-called PI mass gap likely originated from an alternative formation channel. Here, we firmly establish GW190521 as an outlier to the stellar-mass BBH population if the PI mass gap begins at or below 65 M⊙. In addition, for a PI lower boundary of 40–50 M⊙, we find it unlikely that the remaining distribution of detected BBH events, excluding GW190521, is consistent with the stellar-mass BBH population.
The coherent WaveBurst (cWB) search algorithm identifies generic gravitational wave (GW) signals in the LIGO-Virgo strain data. We propose a machine learning (ML) method to optimize the pipeline sensitivity to the special class of GW signals known as binary black hole (BBH) mergers. Here, we test the ML-enhanced cWB search on strain data from the first and second observing runs of Advanced LIGO and successfully recover all BBH events previously reported by cWB, with higher significance. For simulated events found with a false alarm rate less than 1 yr−1, we demonstrate the improvement in the detection efficiency of 26% for stellar-mass BBH mergers and 16% for intermediate mass black hole binary mergers. To demonstrate the robustness of the ML-enhanced search for the detection of generic BBH signals, we show that it has the increased sensitivity to the spin precessing or eccentric BBH events, even when trained on simulated quasicircular BBH events with aligned spins.
We present self-consistent 3D core-collapse supernova simulations of a 40 M ⊙ progenitor model using the isotropic diffusion source approximation for neutrino transport and an effective general relativistic potential up to ∼0.9 s postbounce. We consider three different rotational speeds with initial angular velocities of Ω 0 = 0 , 0.5, and 1 rad s ⁻¹ and investigate the impact of rotation on shock dynamics, black hole (BH) formation, and gravitational wave (GW) signals. The rapidly rotating model undergoes an early explosion at ∼250 ms postbounce and shows signs of the low T / ∣ W ∣ instability. We do not find BH formation in this model within ∼460 ms postbounce. In contrast, we find BH formation at 776 ms postbounce and 936 ms postbounce for the nonrotating and slowly rotating models, respectively. The slowly rotating model explodes at ∼650 ms postbounce, and the subsequent fallback accretion onto the proto–neutron star (PNS) results in BH formation. In addition, the standing accretion shock instability induces rotation of the PNS in the model that started with a nonrotating progenitor. Assuming conservation of specific angular momentum during BH formation, this corresponds to a BH spin parameter of a = J / M = 0.046. However, if no explosion sets in, all the angular momentum will eventually be accreted by the BH, resulting in a nonspinning BH. The successful explosion of the slowly rotating model drastically slows down the accretion onto the PNS, allowing continued cooling and contraction that results in an extremely high GW frequency ( f ∼ 3000 Hz) at BH formation, while the nonrotating model generates GW signals similar to our corresponding 2D simulations.
We report a degeneracy between the gravitational-wave signals from quasicircular precessing black-hole mergers and those from extremely eccentric mergers, namely, head-on collisions. Performing model selection on numerically simulated signals of head-on collisions using models for quasicircular binaries, we find that, for signal-to-noise ratios of 15 and 25, typical of Advanced LIGO observations, head-on mergers with respective total masses of M∈(125,300)M⊙ and M∈(200,440)M⊙ would be identified as precessing quasicircular intermediate-mass black-hole binaries located at a much larger distance. Ruling out the head-on scenario would require us to perform model selection using currently nonexistent waveform models for head-on collisions, together with the application of astrophysically motivated priors on the (rare) occurrence of those events. We show that in situations where standard parameter inference of compact binaries may report component masses inside (outside) the pair-instability supernova gap, the true object may be a head-on merger with masses outside (inside) this gap. We briefly discuss the potential implications of these findings for GW190521, which we analyze in detail in J. Calderón Bustillo et al., Phys. Rev. Lett. 126, 081101 (2021).
On May 21, 2019 the Advanced LIGO and Advanced Virgo detectors observed a gravitational-wave transient GW190521, the heaviest binary black-hole merger detected to date with remnant mass of 142 M⊙ that was published recently. This observation is the first strong evidence for the existence of intermediate-mass black holes. The significance of this observation was determined by the coherent waveburst (cWB) search algorithm, which identified GW190521 with minimal assumptions of its source model. In this paper, we show the performance of cWB for the detection of the binary black-hole mergers without use of the signal templates, describe the details of the GW190521 detection, and establish the consistency of the model-agnostic reconstruction of GW190521 by cWB with the theoretical waveform model of a binary black hole.
We explore the influence of non-axisymmetric modes on the dynamics of the collapsed core of rotating, magnetized high-mass stars in three-dimensional simulations of a rapidly rotating star with an initial mass of endowed with four different pre-collapse configurations of the magnetic field, ranging from moderate to very strong field strength and including the field predicted by the stellar evolution model. The model with the weakest magnetic field achieves shock revival due to neutrino heating in a gain layer characterized by a large-scale, hydrodynamic m = 1 spiral mode. Later on, the growing magnetic field of the proto neutron star launches weak outflows into the early ejecta. Their orientation follows the evolution of the rotational axis of the proto neutron star, which starts to tilt from the original orientation due to the asymmetric accretion flows impinging on its surface. The models with stronger magnetization generate mildly relativistic, magnetically driven polar outflows propagating over a distance of 104 km within a few . These jets are stabilized against disruptive non-axisymmetric instabilities by their fast propagation and by the shear of their toroidal magnetic field. Within the simulation times of around , the explosions reach moderate energies and the growth of the proto neutron star masses ceases at values substantially below the threshold for black hole formation, which, in combination with the high rotational energies, might suggest a possible later proto-magnetar activity.
We present 3D core-collapse supernova simulations of massive Population III progenitor stars at the transition to the pulsational pair instability regime. We simulate two progenitor models with initial masses of 85 and with the LS220, SFHo, and SFHx equations of state. The progenitor experiences a pair instability pulse coincident with core collapse, whereas the progenitor has already gone through a sequence of four pulses 1500 yr before collapse in which it ejected its H and He envelope. The models experience shock revival and then delayed collapse to a black hole (BH) due to ongoing accretion within hundreds of milliseconds. The diagnostic energy of the incipient explosion reaches up to in the SFHx model. Due to the high binding energy of the metal core, BH collapse by fallback is eventually unavoidable, but partial mass ejection may be possible. The models have not achieved shock revival or undergone BH collapse by the end of the simulation. All models exhibit relatively strong gravitational-wave emission both in the high-frequency g-mode emission band and at low frequencies. The SFHx and SFHo models show clear emission from the standing accretion shock instability. For our models, we estimate maximum detection distances of up to with LIGO and with Cosmic Explorer.
We present predictions for the gravitational wave (GW) emission of 3D supernova simulations performed for a 15 solar-mass progenitor with the prometheus–vertex code using energy-dependent, three-flavour neutrino transport. The progenitor adopted from stellar evolution calculations including magnetic fields had a fairly low specific angular momentum (jFe ≲ 10¹⁵ cm² s⁻¹) in the iron core (central angular velocity ΩFe,c ∼ 0.2 rad s⁻¹), which we compared to simulations without rotation and with artificially enhanced rotation (jFe ≲ 2 × 10¹⁶ cm² s⁻¹; ΩFe,c ∼ 0.5 rad s⁻¹). Our results confirm that the time-domain GW signals of SNe are stochastic, but possess deterministic components with characteristic patterns at low frequencies (≲200 Hz), caused by mass motions due to the standing accretion shock instability (SASI), and at high frequencies, associated with gravity-mode oscillations in the surface layer of the proto-neutron star (PNS). Non-radial mass motions in the post-shock layer as well as PNS convection are important triggers of GW emission, whose amplitude scales with the power of the hydrodynamic flows. There is no monotonic increase of the GW amplitude with rotation, but a clear correlation with the strength of SASI activity. Our slowly rotating model is a fainter GW emitter than the non-rotating model because of weaker SASI activity and damped convection in the post-shock layer and PNS. In contrast, the faster rotating model exhibits a powerful SASI spiral mode during its transition to explosion, producing the highest GW amplitudes with a distinctive drift of the low-frequency emission peak from ∼80–100 to ∼40–50 Hz. This migration signifies shock expansion, whereas non-exploding models are discriminated by the opposite trend.
Understanding gravitational wave emission from core-collapse supernovae will be essential for their detection with current and future gravitational wave detectors. This requires a sample of waveforms from modern 3D supernova simulations reaching well into the explosion phase, where gravitational wave emission is expected to peak. However, recent waveforms from 3D simulations with multigroup neutrino transport do not reach far into the explosion phase, and some are still obtained from non-exploding models. We therefore calculate waveforms up to 0.9 s after bounce using the neutrino hydrodynamics code coconut-fmt. We consider two models with low and normal explosion energy, namely explosions of an ultra-stripped progenitor with an initial helium star mass of ||, and of an || single star. Both models show gravitational wave emission from the excitation of surface g modes in the proto-neutron star with frequencies between || and 1000 Hz at peak emission. The peak amplitudes are about |6| and ||, respectively, which is somewhat higher than in most recent 3D models of the pre-explosion or early explosion phase. Using a Bayesian analysis, we determine the maximum detection distances for our models in simulated Advanced LIGO, Advanced Virgo, and Einstein Telescope (ET) design sensitivity noise. The more energetic || explosion will be detectable to about || by the LIGO/Virgo network and to about || with the ET.
We present 3D simulations of the core-collapse of massive rotating and non-rotating progenitors performed with the general relativistic neutrino hydrodynamics code coconut-fmt. The progenitor models include Wolf-Rayet stars with initial helium star masses of and , and an red supergiant. The model is a rapid rotator, whereas the two other progenitors are non-rotating. Both Wolf-Rayet models produce healthy neutrino-driven explosions, whereas the red supergiant model fails to explode. By the end of the simulations, the explosion energies have already reached and for the and model, respectively. They produce neutron stars of relatively high mass, but with modest kicks. Due to the alignment of the bipolar explosion geometry with the rotation axis, there is a relatively small misalignment of 30° between the spin and the kick in the rapidly rotating model. For this model, we find that rotation significantly changes the dependence of the characteristic gravitational-wave frequency of the f-mode on the proto-neutron star parameters compared to the non-rotating case. Its gravitational-wave amplitudes would make it detectable out to almost 2 Mpc by the Einstein Telescope. The other two progenitors have considerably smaller detection distances, despite significant low-frequency emission in the most sensitive frequency band of current gravitational-wave detectors.
We present the first results of the search for nonlinear memory from subsolar mass binary black hole (BBH) mergers during the second observing run (O2) of the LIGO and Virgo detectors. The oscillatory chirp signal from the inspiral and merger of low mass BBHs (MTot≤0.4 M⊙) are at very high frequencies and fall outside the sensitivity band of the current ground-based detectors. However, the nonoscillatory memory signal during the merger saturates toward the lower frequencies and can be detected for those proposed BBHs. We show in this work that the morphology of the memory signal depends minimally upon the source parameters of the binary, thus only the overall amplitude of the signal changes and hence the result can be interpolated for extremely low mass BBH mergers. We did not find any signal which can be interpreted as a memory signal, and we place upper limits on the rate of BBH mergers with MTot≤0.4 M⊙ for the first time.
The existence of ∼10 ⁹ M ⊙ supermassive black holes (SMBHs) within the first billion years of the Universe has stimulated numerous ideas for the prompt formation and rapid growth of black holes (BHs) in the early Universe. Here, we review ways in which the seeds of massive BHs may have first assembled, how they may have subsequently grown as massive as ∼10 ⁹ M ⊙ , and how multimessenger observations could distinguish between different SMBH assembly scenarios. We conclude the following: ▪ The ultrarare ∼10 ⁹ -M ⊙ SMBHs represent only the tip of the iceberg. Early BHs likely fill a continuum from the stellar-mass (∼10 M ⊙ ) to the supermassive (∼10 ⁹ ) regimes, reflecting a range of initial masses and growth histories. ▪ Stellar-mass BHs were likely left behind by the first generation of stars at redshifts as high as ∼30, but their initial growth typically was stunted due to the shallow potential wells of their host galaxies. ▪ Conditions in some larger, metal-poor galaxies soon became conducive to the rapid formation and growth of massive seed holes, via gas accretion and by mergers in dense stellar clusters. ▪ BH masses depend on the environment (such as the number and properties of nearby radiation sources and the local baryonic streaming velocity) and on the metal enrichment and assembly history of the host galaxy. ▪ Distinguishing between assembly mechanisms will be difficult, but a combination of observations by the Laser Interferometer Space Antenna (probing massive BH growth via mergers) and by deep multiwavelength electromagnetic observations (probing growth via gas accretion) is particularly promising.
Expected final online publication date for the Annual Review of Astronomy, Volume 58 is August 18, 2020. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
As progenitors of gamma-ray bursts (GRBs), the core collapse of massive stars and the coalescence of compact object binaries are believed to be powerful sources of gravitational waves (GWs). In the collapsar scenario, a rotating stellar-mass black hole (BH) surrounded by a hyperaccretion disk might be active in the center of a massive collapsar, which is one of the plausible central engines of long GRBs. Such a BH hyperaccretion disk would be in a state of a neutrino-dominated accretion flow (NDAF) at the initial stage of the accretion process; meanwhile, the jets attempt to break out from the envelope and circumstellar medium to power GRBs. In addition to collapsars, BH hyperaccretion systems are important sources of neutrinos and GWs. In this paper, we investigate the GW emission generated by the anisotropic neutrino emission from NDAFs in collapsar scenarios. As the results indicate, the typical frequency of GWs is ∼1–100 Hz, and the masses and metallicities of the progenitor stars have slight effects on the GW strains. The GWs from NDAFs might be detected by operational or planned detectors at a distance of 10 kpc. Moreover, comparisons of the detectable GWs from collapsars, NDAFs, and GRB jets (internal shocks) are displayed. By combining the electromagnetic counterparts, neutrinos, and GWs, one may constrain the characteristics of collapsars and central BH accretion systems.
Gravitational-wave astronomy has been firmly established with the detection of gravitational waves from the merger of ten stellar-mass binary black holes and a neutron star binary. This paper reports on the all-sky search for gravitational waves from intermediate mass black hole binaries in the first and second observing runs of the Advanced LIGO and Virgo network. The search uses three independent algorithms: two based on matched filtering of the data with waveform templates of gravitational-wave signals from compact binaries, and a third, model-independent algorithm that employs no signal model for the incoming signal. No intermediate mass black hole binary event is detected in this search. Consequently, we place upper limits on the merger rate density for a family of intermediate mass black hole binaries. In particular, we choose sources with total masses M=m1+m2∈[120,800] M⊙ and mass ratios q=m2/m1∈[0.1,1.0]. For the first time, this calculation is done using numerical relativity waveforms (which include higher modes) as models of the real emitted signal. We place a most stringent upper limit of 0.20 Gpc−3 yr−1 (in comoving units at the 90% confidence level) for equal-mass binaries with individual masses m1,2=100 M⊙ and dimensionless spins χ1,2=0.8 aligned with the orbital angular momentum of the binary. This improves by a factor of ∼5 that reported after Advanced LIGO’s first observing run.
The Galactic center is dominated by the gravity of a super-massive black hole (SMBH), Sagittarius A*, and is suspected to contain a sizable population of binary stars. Such binaries form hierarchical triples with the SMBH, undergoing Eccentric Kozai–Lidov (EKL) evolution, which can lead to high-eccentricity excitations for the binary companions’ mutual orbit. This effect can lead to stellar collisions or Roche-lobe crossings, as well as orbital shrinking due to tidal dissipation. In this work we investigate the dynamical and stellar evolution of such binary systems, especially with regards to the binaries’ post-main-sequence evolution. We find that the majority of binaries (∼75%) is eventually separated into single stars, while the remaining binaries (∼25%) undergo phases of common-envelope evolution and/or stellar mergers. These objects can produce a number of different exotic outcomes, including rejuvenated stars, G2-like infrared-excess objects, stripped giant stars, Type Ia supernovae (SNe), cataclysmic variables, symbiotic binaries, or compact object binaries. We estimate that, within a sphere of 250 Mpc radius, about 7.5–15 SNe Ia per year should occur in galactic nuclei due to this mechanism, potentially detectable by the Zwicky Transient Facility and ASAS-SN. Likewise, we estimate that, within a sphere of 1 Gpc ³ volume, about 10–20 compact object binaries form per year that could become gravitational wave sources. Based on results of EKL-driven compact object binary mergers in galactic nuclei by Hoang et al., this compact object binary formation rate translates to about 15–30 events per year that are detectable by Advanced LIGO.
We study the gravitational wave (GW) signal from eight new 3D core-collapse supernova simulations. We show that the signal is dominated by f - and g -mode oscillations of the protoneutron star (PNS) and its frequency evolution encodes the contraction rate of the latter, which, in turn, is known to depend on the star’s mass, on the equation of state, and on transport properties in warm nuclear matter. A lower-frequency component of the signal, associated with the standing accretion shock instability, is found in only one of our models. Finally, we show that the energy radiated in GWs is proportional to the amount of turbulent energy accreted by the PNS.
The details of the physical mechanism that drives core-collapse supernovae (CCSNe) remain uncertain. While there is an emerging consensus on the qualitative outcome of detailed CCSN mechanism simulations in 2D, only recently have high-fidelity 3D simulations become possible. Here we present the results of an extensive set of 3D CCSN simulations using high-fidelity multidimensional neutrino transport, high-resolution hydrodynamics, and approximate general relativistic gravity. We employ a state-of-the-art 20 M progenitor generated using Modules for Experiments in Stellar Astrophysics, and the SFHo equation of state. While none of our 3D CCSN simulations explode within ∼500 ms after core bounce, we find that the presence of large-scale aspherical motion in the Si and O shells aid shock expansion and bring the models closer to the threshold of explosion. We also find some dependence on resolution and geometry (octant versus full 4π). As has been noted in other recent works, we find that the post-shock turbulence plays an important role in determining the overall dynamical evolution of our simulations. We find a strong standing accretion shock instability (SASI) that develops at late times. The SASI produces transient shock expansions, but these do not result in any explosions. We also report that for a subset of our simulations, we find conclusive evidence for the lepton-number emission self-sustained asymmetry, which until now has not been confirmed by independent simulation codes. Both the progenitor asphericities and the SASI-induced transient shock expansion phases generate transient gravitational waves and neutrino signal modulations via perturbations of the protoneutron star by turbulent motions. © 2018. The American Astronomical Society. All rights reserved.
The central engines of some superluminous supernovae (SLSNe) are generally suggested to be newly born fast rotating magnetars, which spin down mainly through magnetic dipole radiation and gravitational wave emission. We calculate the magnetar-powered SLSNe light curves (LCs) with the tilt angle evolution of newly born magnetars involved. We show that, depending on the internal toroidal magnetic fields B¯t, the initial spin periods Pi, and the radii RDU of direct Urca (DU) cores of newly born magnetars, as well as the critical temperature Tc for P23 neutron superfluidity, bumps could appear in the SLSNe LCs after the maximum lights when the tilt angles grow to π/2. The value of Tc determines the arising time and the relative amplitude of a bump. The quantity RDU can affect the arising time and the luminosity of a bump, as well as the peak luminosity of a LC. For newly born magnetars with dipole magnetic fields Bd=5×1014 G, B¯t=4.6×1016 G, and Pi=1 ms, there are no bumps in the LCs if Tc=2×109 K, or RDU=1.5×105 cm. Moreover, it is interesting that a stronger B¯t will lead to both a brighter peak and a brighter bump in a LC. While keeping other quantities unchanged, the bump in the LC disappears for the magnetar with smaller Pi. We suggest that, once the SLSNe LCs with such kinds of bumps are observed, by fitting these LCs with our model, not only Bd and Pi of newly born magnetars but also the crucial physical quantities B¯t, RDU, and Tc could be determined. Nonobservation of SLSNe LCs with such kinds of bumps hitherto may already put some (though very rough) constraints on B¯t, Pi, RDU, and Tc. Therefore, observation of SLSNe LCs may provide a new approach to probe the physics of newly born magnetars.
Gravitational-wave detections have revealed a previously unknown population of stellar mass black holes with masses above . These observations provide a new way to test models of stellar evolution for massive stars. By considering the astrophysical processes likely to determine the shape of the binary black hole mass spectrum, we construct a parameterized model to capture key features that can relate gravitational-wave data to theoretical stellar astrophysics. Pulsational pair-instability supernovae are expected to cause all stars with initial mass to form black holes. This would cause a cut-off in the black hole mass spectrum along with an excess of black holes near . First, our method can be used to measure the minimum and maximum stellar black hole mass (if the mass spectrum is characterized by one or more sharp cut-offs). Second, we determine the spectral index of the black hole mass distribution. Third, we measure the presence of a peak due, for example, to pair-instability supernovae. Finally, we show how inadequate models of the black hole mass spectrum lead to biased estimates of the merger rate.
The first observation of a binary neutron star (NS) coalescence by the Advanced LIGO and Advanced Virgo gravitational-wave (GW) detectors offers an unprecedented opportunity to study matter under the most extreme conditions. After such a merger, a compact remnant is left over whose nature depends primarily on the masses of the inspiraling objects and on the equation of state of nuclear matter. This could be either a black hole (BH) or an NS, with the latter being either long-lived or too massive for stability implying delayed collapse to a BH. Here, we present a search for GWs from the remnant of the binary NS merger GW170817 using data from Advanced LIGO and Advanced Virgo. We search for short- (≾1 s) and intermediate-duration (≾500 s) signals, which include GW emission from a hypermassive NS or supramassive NS, respectively. We find no signal from the post-merger remnant. Our derived strain upper limits are more than an order of magnitude larger than those predicted by most models. For short signals, our best upper limit on the root sum square of the GW strain emitted from 1–4 kHz is h^(50%)_(rss) = 2.1 x 10^(-22) Hz^(-1/2) at 50% detection efficiency. For intermediate-duration signals, our best upper limit at 50% detection efficiency is h^(50%)_(rss) = 8.4 x 10^(-22) Hz^(-1/2) for a millisecond magnetar model, and h^(50%)_(rss) = 5.9 x 10^(-22) Hz^(-1.2) for a bar-mode model. These results indicate that post-merger emission from a similar event may be detectable when advanced detectors reach design sensitivity or with next-generation detectors.