Laser Interferometer Gravitational-Wave Observatory Data Research Articles

WaveFormer: transformer-based denoising method for gravitational-wave data

With the advent of gravitational-wave astronomy and the discovery of more compact binary coalescences, data quality improvement techniques are desired to handle the complex and overwhelming noise in gravitational wave (GW) observational data. Though recent machine learning-based studies have shown promising results for data denoising, they are unable to precisely recover both the GW signal amplitude and phase. To address such an issue, we develop a deep neural network centered workflow, WaveFormer, for significant noise suppression and signal recovery on observational data from the Laser Interferometer Gravitational-Wave Observatory (LIGO). The WaveFormer has a science-driven architecture design with hierarchical feature extraction across a broad frequency spectrum. As a result, the overall noise and glitch are decreased by more than one order of magnitude and the signal recovery error is roughly 1% and 7% for the phase and amplitude, respectively. Moreover, on 75 reported binary black hole events of LIGO we obtain a significant improvement of inverse false alarm rate. Our work highlights the potential of large neural networks in GW data analysis and, while primarily demonstrated on LIGO data, its adaptable design indicates promise for broader application within the International Gravitational-Wave Observatories Network in future observational runs.

Search for postmerger gravitational waves from binary neutron star mergers using a matched-filtering statistic

In this paper, we present a new method to search for a short, a few tens of millis long, postmerger gravitational-wave (GW) signal following the merger of two neutron stars. Such a signal could follow the event GW170817 observed by Laser Interferometer Gravitational-Wave Observatory (LIGO) and Virgo detectors. Our method is based on a matched filtering statistic and an approximate template of the postmerger signal in the form of a damped sinusoid. We test and validate our method using postmerger numerical simulations from the CoRe database. We find no evidence of the short postmerger signal in the LIGO data following the GW170817 event and we obtain upper limits. For short postmerger signals investigated, our best upper limit on the root sum square of the GW strain emitted from 1.15 kHz to 4 kHz is at 50% detection efficiency. The distance corresponding to this best upper limit is 4.64 Mpc.

Deep learning detection and classification of gravitational waves from neutron star-black hole mergers

The Laser Interferometer Gravitational-Wave Observatory (LIGO) and Virgo Interferometer Collaborations have now detected all three classes of compact binary mergers: binary black hole (BBH), binary neutron star (BNS), and neutron star-black hole (NSBH). For coalescences involving neutron stars, the simultaneous observation of gravitational and electromagnetic radiation produced by an event, has broader potential to enhance our understanding of these events, and also to probe the equation of state (EOS) of dense matter. However, electromagnetic follow-up to gravitational wave (GW) events requires rapid real-time detection and classification of GW signals, and conventional detection approaches are computationally prohibitive for the anticipated rate of detection of next-generation GW detectors. In this work, we present the first deep learning based results of classification of GW signals from NSBH mergers in real LIGO data. We show for the first time that a deep neural network can successfully distinguish all three classes of compact binary mergers and separate them from detector noise. Specifically, we train a convolutional neural network (CNN) on ∼500,000 data samples of real LIGO noise with injected BBH, BNS, and NSBH GW signals, and we show that our network has high sensitivity and accuracy. Most importantly, we successfully recover the two confirmed NSBH events to-date (GW191219 and GW200115) and the two confirmed BNS mergers to-date (GW170817 and GW190425), together with ∼90% of all BBH candidate events from the third Gravitational Wave Transient Catalog, GWTC-3. These results are an important step towards low-latency real-time GW detection, enabling multi-messenger astronomy.

Search for gravitational waves from Scorpius X-1 with a hidden Markov model in O3 LIGO data

Results are presented for a semicoherent search for continuous gravitational waves from the low-mass x-ray binary Scorpius X-1, using a hidden Markov model (HMM) to allow for spin wandering. This search improves on previous HMM-based searches of Laser Interferometer Gravitational-Wave Observatory data by including the orbital period in the search template grid, and by analyzing data from the latest (third) observing run. In the frequency range searched, from 60 to 500 Hz, we find no evidence of gravitational radiation. This is the most sensitive search for Scorpius X-1 using a HMM to date. For the most sensitive subband, starting at 256.06 Hz, we report an upper limit on gravitational wave strain (at 95% confidence) of h095%=6.16×10−26, assuming the orbital inclination angle takes its electromagnetically restricted value ι=44°. The upper limits on gravitational wave strain reported here are on average a factor of ∼3 lower than in the second observing run HMM search. This is the first Scorpius X-1 HMM search with upper limits that reach below the indirect torque-balance limit for certain subbands, assuming ι=44°.Received 26 January 2022Accepted 26 August 2022DOI:https://doi.org/10.1103/PhysRevD.106.062002© 2022 American Physical SocietyPhysics Subject Headings (PhySH)Research AreasGravitational wavesPhysical SystemsBinary starsNeutron stars & pulsarsGravitation, Cosmology & Astrophysics

Gravitational wave signal recognition and ring-down time estimation via Artificial Neural Networks

Laser Interferometer Gravitational-Wave Observatory (LIGO) was the first laboratory to measure the gravitational waves successfully. An exceptional experimental design was needed to measure distance changes less than an atomic nucleus. In the same way, the data analyses to confirm and extract information is a tremendously challenging task. This article shows a computational procedure based on Artificial Neural Networks (ANN) to recognize a black hole-black hole gravitation wave event signal from the LIGO data. With the ANN introduced methodology, it is possible to define a numerical score, like a thermometer. High score values are associated with gravitational wave observation and small values with noise. Building a time series from these scores values, physical information about the astronomical system’s damping time, the ring-down time, can be estimated at a first approximation, based on a damped harmonic oscillator modeling. Here, the ring-down time is estimated, at a first approximation, with a direct data measure on the ANN score time series, without using numerical relativity techniques and high computational power.

Accelerated, scalable and reproducible AI-driven gravitational wave detection

The development of reusable artificial intelligence (AI) models for wider use and rigorous validation by the community promises to unlock new opportunities in multi-messenger astrophysics. Here we develop a workflow that connects the Data and Learning Hub for Science, a repository for publishing AI models, with the Hardware Accelerated Learning (HAL) cluster, using funcX as a universal distributed computing service. Using this workflow, an ensemble of four openly available AI models can be run on HAL to process an entire month's worth (August 2017) of advanced Laser Interferometer Gravitational-Wave Observatory data in just seven minutes, identifying all four all four binary black hole mergers previously identified in this dataset and reporting no misclassifications. This approach combines advances in AI, distributed computing, and scientific data infrastructure to open new pathways to conduct reproducible, accelerated, data-driven discovery.

Gravitational waves LIGO data sourced by spin-1 and spin-0 torsion propagating modes in teleparallelism

Spin-1 and spin-0 torsion wave modes in linearized teleparallelism are obtained where the totally skew-symmetric complex contortion tensor generates scalar torsion waves and the symmetric contortion in the last two indices generates gravitational waves (GW) as gravitational perturbations in flat spacetime with contortion tensor. A gedanken experiment with this gravitational-torsion wave hitting a ring of spinless particles is proposed which allows us to use the estimate of contortion at the Earth and comparing with results of strain found by Abbott et al., laser interferometer gravitational wave observatory (LIGO) collaboration from merger of a pair of Black holes (Phys Rev Lett 116:06102, 2016) of $$\frac{{\delta }l}{l}=10^{-21}$$ which agrees with the estimate found in this paper. This lends support to the model presented in this paper. Collapsing star GW frequency are used to estimate the relative expansion or contraction of the arms in the experiment from well-known estimates on Earth contortion of $$10^{-24}\,\mathrm{s}^{-1}$$ . The physical implications of the model are investigated in detail by computing the stochastic pseudo-tensor of GW energy and using spatial and tensor components of axial torsion vector, to obtain different strain values, with distinct contortion components. Stochastic pseudo-tensor of GW depends nonlinearly on the contortion.

Search for Eccentric Binary Neutron Star Mergers in the First and Second Observing Runs of Advanced LIGO

Abstract We present a search for gravitational waves from merging binary neutron stars (BNSs) which have non-negligible eccentricity as they enter the Laser Interferometer Gravitational Wave Observatory (LIGO) observing band. We use the public Advanced LIGO data which covers the period from 2015 through 2017 and contains ∼164 days of LIGO–Hanford and LIGO–Livingston coincident observing time. The search was conducted using matched-filtering using the PyCBC toolkit. We find no significant BNS candidates beyond GW170817, which has previously been reported by searches for binaries in circular orbits. We place a 90% upper limit of ∼1700 mergers Gpc−3 yr−1 for eccentricities ≲0.43 at a dominant-mode gravitational-wave frequency of 10 Hz. The absence of a detection with these data is consistent with theoretical predictions of eccentric BNS merger rates. Using our measured rate we estimate the sensitive volume of future gravitational-wave detectors and compare this to theoretical rate predictions. We find that, in the absence of a prior detection, the rate limits set by six months of Cosmic Explorer observations would constrain all current plausible models of eccentric BNS formation.

Search for Gravitational Waves Associated with Gamma-Ray Bursts during the First Advanced LIGO Observing Run and Implications for the Origin of GRB 150906B

Abstract We present the results of the search for gravitational waves (GWs) associated with γ-ray bursts detected during the first observing run of the Advanced Laser Interferometer Gravitational-Wave Observatory (LIGO). We find no evidence of a GW signal for any of the 41 γ-ray bursts for which LIGO data are available with sufficient duration. For all γ-ray bursts, we place lower bounds on the distance to the source using the optimistic assumption that GWs with an energy of were emitted within the – Hz band, and we find a median 90% confidence limit of 71 Mpc at 150 Hz. For the subset of 19 short/hard γ-ray bursts, we place lower bounds on distance with a median 90% confidence limit of 90 Mpc for binary neutron star (BNS) coalescences, and 150 and 139 Mpc for neutron star–black hole coalescences with spins aligned to the orbital angular momentum and in a generic configuration, respectively. These are the highest distance limits ever achieved by GW searches. We also discuss in detail the results of the search for GWs associated with GRB 150906B, an event that was localized by the InterPlanetary Network near the local galaxy NGC 3313, which is at a luminosity distance of Mpc (z = 0.0124). Assuming the γ-ray emission is beamed with a jet half-opening angle , we exclude a BNS and a neutron star–black hole in NGC 3313 as the progenitor of this event with confidence >99%. Further, we exclude such progenitors up to a distance of 102 Mpc and 170 Mpc, respectively.

Quantum correlation measurements in interferometric gravitational-wave detectors

Quantum fluctuations in the phase and amplitude quadratures of light set limitations on the sensitivity of modern optical instruments. The sensitivity of the interferometric gravitational wave detectors, such as the Advanced Laser Interferometer Gravitational wave Observatory (LIGO), is limited by quantum shot noise, quantum radiation pressure noise, and a set of classical noises. We show how the quantum properties of light can be used to distinguish these noises using correlation techniques. Particularly, in the first part of the paper we show estimations of the coating thermal noise and gas phase noise, hidden below the quantum shot noise in the Advanced LIGO sensitivity curve. We also make projections on the observatory sensitivity during the next science runs. In the second part of the paper we discuss the correlation technique that reveals the quantum radiation pressure noise from the background of classical noises and shot noise. We apply this technique to the Advanced LIGO data, collected during the first science run, and experimentally estimate the quantum correlations and quantum radiation pressure noise in the interferometer for the first time.

GPU accelerated low latency gravitational wave data processing

To enable prompt electromagnetic (EM) follow-up observations of GW events, it is very critical to identify the gravitational wave signal in real time so we can investigate the astrophysical events completely. In this paper we first described the LIGO (Laser Interferometer Gravitational-Wave Observatory) SPIIR (Summed Parallel Infinite Impulse Response) online data processing pipeline which can reduce the latency to meet real time requirement on GPU (Graphics Processing Unit) with multiple optimization methods. Moreover, to achieve extremely low latency for advanced LIGO data processing, this paper also presents the proposed computational method, performance optimization method and visualization tool.

From Einstein's general theory of relativity to gravitational‐wave astronomy

In his 1916 article [1] predicting the existence of gravitational waves, Einstein wrote that they were too weak to be of any consequence. A century later, the world’s attention was captured by the February 11th announcement, demonstrating how wrong this was. In a landmark publication in Physical Review Letters [2], an international team reports the first direct detection of the gravitational waves emitted by a pair of black holes (29 and 36 solar masses) during their final few orbits before merging to form a single 62 solar-mass black hole. Physicists love extremes, because pushing the limits leads to insight and understanding. This discovery, a short chirp lasting about a quarter-second (see Fig. 1, adapted from [2]), pushes the limits in many different directions. Let’s start with the human side. The first unsuccessful attempts to detect gravitational waves were smallinvestigator experiments made about fifty years ago. In contrast, the discovery paper had about 1000 authors (20% are from the Max Planck Institute for Gravitational Physics, for which I am the Managing Director). Some of these authors have worked towards the discovery for more than forty years. The detector technology also pushes the limits. The advanced Laser Interferometer Gravitational-Wave Observatory (LIGO) instruments are located 3000 km apart, in Hanford, Washington and Livingston, Louisiana. The effect of the gravitational waves is to distort the effective path length between pairs of mirrors hanging 4 km apart in a seismically-isolated high-vacuum system. At the peak of the signal the measured length change in each detector arm is about 0.002 femtometers, 1/1000 the diameter of a hydrogen nucleus. This is a fractional precision of a part in 1021; analogous to measuring the distance to the nearest star (Proxima Centuri) to an accuracy of 40 μm. I don’t know of any other measurement done with comparable precision. The binary system we observed was about one billion light years distant from earth; over some tens of milliseconds it converted about three solar masses of gravitational binding energy into gravitational waves. During that brief time, the system emitted more power than the optical luminosity of every star in every galaxy in the visible universe. My kids, jaded by generations of Star Wars movies, were unimpressed until I told them that in comparison with this, the “Death Star”, capable of vaporizing entire planets, is child’s toy, a harmless plaything. Three solarmasses is enough energy to vaporize every planet in many galaxies! Binary black hole systems like this one could not have been detected in any other way, because (being black!) they do not emit any light or electromagnetic energy. But there are intriguing reports [3] that a team analyzing data from the Gamma-ray Burst Monitor (GBM) detector on board NASA’s Fermi satellite observed a gammaray burst 0.4 seconds after the merger. So Nature might still surprise us. Could such systems be surrounded by clouds of gas or dust? We can’t be sure now, but within a few years, I am confident that we will know the answer to this and to many other questions. The rate at which our knowledge will now increase is breathtaking. In their first observing run the advanced LIGOdetectors were a factor of three below their final design sensitivity. That doesn’t seem like much, but keep in mind that the expected number of sources/detections is proportional to the observable volume of space, which scales like the cube of the sensitivity. So the second observing run, starting this September and lasting six months, should observe about a dozen black hole mergers, and the third observing run, starting in 2017, should see about one hundred. It’s going to be quite a ride – a golden age of gravitational wave astronomy. By the end of it, we’ll know themass distribution and spatial density of these stellarmass black hole binary systems. And perhaps our catalog of observations will include new extremes, such as systemswith high spin, or neutron-star/black-hole binaries, or other surprises.

Improving the data quality of Advanced LIGO based on early engineering run results

The Advanced Laser Interferometer Gravitational-wave Observatory (LIGO) detectors have completed their initial upgrade phase and will enter the first observing run in late 2015, with detector sensitivity expected to improve in future runs. Through the combined efforts of on-site commissioners and the Detector Characterization Group of the LIGO Scientific Collaboration, interferometer performance, in terms of data quality, at both LIGO observatories has vastly improved from the start of commissioning efforts to present. Advanced LIGO has already surpassed Enhanced LIGO in sensitivity, and the rate of noise transients, which would negatively impact astrophysical searches, has improved. Here we give details of some of the work which has taken place to better the quality of the LIGO data ahead of the first observing run.

Searching for Gravitational Waves from the Coalescence of High-mass Black Hole Binaries

We search for gravitational waves from the coalescence (inspiral, merger and ringdown) of binary black holes with data from the Laser Interferometer Gravitational-Wave Observatory (LIGO). Provided with well-described waveform models from General Relativity, matched filtering is employed in the GSTLAL analysis pipeline as the optimal detection technique for weak signals in Gaussian noise. The GSTLAL analysis pipeline filters data with waveform template banks, identifies triggers with SNR greater than 4, forms coincident triggers between multiple detectors in the LSC-Virgo Collaboration, and attempts to optimally separate signal from detector background noise fluctuations using a Chisquared test. We analyze high-statistics simulations of binary merger waveforms injected into LIGO recolored S6 data to evaluate the pipeline search sensitivity and to test the readiness of the pipeline for Advanced LIGO. With Advanced LIGO fully in operation by 2015 and the upgraded analysis pipelines, the expected detection rate is increased to as much as 100 events/year or more as compared to 0.01–1 events/year in Initial LIGO. Our work will make it possible to detect gravitational waves from binary black hole coalescence in Advanced LIGO data with high confidence. KEYWORDS: LIGO, Gravitational Waves, General Relativity, Coalescence, Black Hole Binaries, Noise Fluctuations, Matched Filtering, Chi-squared Test, Simulations, GSTLAL Analysis Pipeline

Observing complete gravitational wave signals from dynamical capture binaries

We assess the detectability of the gravitational wave signals from highly eccentric compact binaries. We use a simple model for the inspiral, merger, and ringdown of these systems. The model is based on mapping the binary to an effective single black hole system described by a Kerr metric, thereby including certain relativistic effects such as zoom-whirl-type behavior. The resultant geodesics source quadrupolar radiation and, in turn, are evolved under its dissipative effects. At the light ring, we attach a merger model that was previously developed for quasicircular mergers but also performs well for eccentric mergers with little modification. We apply this model to determine the detectability of these sources for initial, Enhanced, and Advanced laser interferometer gravitational-wave observatory across the parameter space of nonspinning close capture compact binaries. We conclude that, should these systems exist in nature, the vast majority will be missed by conventional burst searches or by quasicircular waveform templates in the advanced detector era. Other methods, such as eccentric templates or, more practically, a stacked excess power search, must be developed to avoid losing these sources. These systems would also have been missed frequently in the initial laser interferometer gravitational-wave observatory data analysis. Thus, previous null coincidence results with detected gamma-ray bursts cannot exclude the possibility of coincident gravitational wave signals from eccentric binaries.

Parameter estimation for signals from compact binary inspirals injected into LIGO data

During the fifth science run of the Laser Interferometer Gravitational-Wave Observatory (LIGO), signals modelling the gravitational waves emitted by coalescing non-spinning compact-object binaries were injected into the LIGO data stream. We analysed the data segments into which such injections were made using a Bayesian approach, implemented as a Markov-chain Monte Carlo technique in our code SPINspiral. This technique enables us to determine the physical parameters of such a binary inspiral, including masses and spin, following a possible detection trigger. For the first time, we publish the results of a realistic parameter-estimation analysis of waveforms embedded in real detector noise. We used both spinning and non-spinning waveform templates for the data analysis and demonstrate that the intrinsic source parameters can be estimated with an accuracy of better than 1–3% in the chirp mass and 0.02–0.05 (8–20%) in the symmetric mass ratio if non-spinning waveforms are used. We also find a bias between the injected and recovered parameters, and attribute it to the difference in the post-Newtonian orders of the waveforms used for injection and analysis.

LIGO data analysis

Abstract Gravitational waves promise to provide new information about massive astrophysical objects in the universe. Technological advances and engineering experience have finally made it feasible to construct detectors with sufficient sensitivity to detect the extremely weak waves which are believed to reach Earth. The Laser Interferometer Gravitational-Wave Observatory (LIGO) project has constructed two “observatories” in the United States which are poised to begin collecting scientifically interesting data. The LIGO Data Analysis System has been designed to support various types of scientific analysis to be performed using this data; its components include an interface to the raw data archive, a “Beowulf” cluster of PCs for parallel processing, and a database to store data analysis products. Attention has also been paid to the deployment of client interface programs and utility software to scientists throughout the LIGO Scientific Collaboration.