Search For Gravitational Waves Research Articles

Improving pulsar timing precision through superior time-of-arrival creation

The measurement of pulsar pulse times-of-arrival (ToAs) is a crucial step in detecting low-frequency gravitational waves. To determine ToAs, we can use template-matching to compare each observed pulse profile with a standard template. However, using different combinations of templates and template-matching methods (TMMs) without careful consideration can lead to inconsistent results. In pulsar timing array (PTA) experiments, distinct ToAs from the same observations can be obtained due to the use of diverse templates and TMMs. In other words, employing diverse approaches can yield different timing results and would thus have a significant impact on subsequent gravitational wave searches. In this paper we examine several commonly used combinations to analyze their effect on pulse ToAs. We evaluated the potential impact of template and TMM selection on 13 typical millisecond pulsars within the European PTA. We employed pulsar timing methods, specifically the root mean square and reduced chi-square ($ of the residuals of the best timing solution, to assess the outcomes. Additionally, we evaluated the system-limited noise floor (SLNF) for each pulsar at various telescopes operating around 1.4 GHz using frequency-resolved templates. Our findings suggest that utilizing data-derived and smoothed templates in conjunction with the Fourier-domain with Markov chain Monte Carlo TMM is generally the most effective approach, though there may be exceptions that require further attention. Furthermore, we determine that pulse phase jitter noise does not significantly limit the current precision of the European PTA's timing, as jitter levels derived from other studies are much lower than the SLNF.

Neural network time-series classifiers for gravitational-wave searches in single-detector periods

The search for gravitational-wave (GW) signals is limited by non-Gaussian transient noises that mimic astrophysical signals. Temporal coincidence between two or more detectors is used to mitigate contamination by these instrumental glitches. However, when a single detector is in operation, coincidence is impossible, and other strategies have to be used. We explore the possibility of using neural network classifiers and present the results obtained with three types of architectures: convolutional neural network, temporal convolutional network, and inception time. The last two architectures are specifically designed to process time-series data. The classifiers are trained on a month of data from the LIGO Livingston detector during the first observing run (O1) to identify data segments that include the signature of a binary black hole merger. Their performances are assessed and compared. We then apply trained classifiers to the remaining three months of O1 data, focusing specifically on single-detector times. The most promising candidate from our search is 4 January 2016 12:24:17 UTC. Although we are not able to constrain the significance of this event to the level conventionally followed in GW searches, we show that the signal is compatible with the merger of two black holes with masses m1=50.7−8.9+10.4M⊙ and m2=24.4−9.3+20.2M⊙ at the luminosity distance of dL=564−338+812Mpc .

Hunting WIMPs with LISA: correlating dark matter and gravitational wave signals

The thermal freeze-out mechanism in its classical form is tightly connected to physics beyond the Standard Model around the electroweak scale, which has been the target of enormous experimental efforts. In this work we study a dark matter model in which freeze-out is triggered by a strong first-order phase transition in a dark sector, and show that this phase transition must also happen close to the electroweak scale, i.e. in the temperature range relevant for gravitational wave searches with the LISA mission. Specifically, we consider the spontaneous breaking of a U(1)′ gauge symmetry through the vacuum expectation value of a scalar field, which generates the mass of a fermionic dark matter candidate that subsequently annihilates into dark Higgs and gauge bosons. In this set-up the peak frequency of the gravitational wave background is tightly correlated with the dark matter relic abundance, and imposing the observed value for the latter implies that the former must lie in the milli-Hertz range. A peculiar feature of our set-up is that the dark sector is not necessarily in thermal equilibrium with the Standard Model during the phase transition, and hence the temperatures of the two sectors evolve independently. Nevertheless, the requirement that the universe does not enter an extended period of matter domination after the phase transition, which would strongly dilute any gravitational wave signal, places a lower bound on the portal coupling that governs the entropy transfer between the two sectors. As a result, the predictions for the peak frequency of gravitational waves in the LISA band are robust, while the amplitude can change depending on the initial dark sector temperature.

The NANOGrav 12.5-Year Data Set: Dispersion Measure Misestimations with Varying Bandwidths

Noise characterization for pulsar-timing applications accounts for interstellar dispersion by assuming a known frequency dependence of the delay it introduces in the times of arrival (TOAs). However, calculations of this delay suffer from misestimations due to other chromatic effects in the observations. The precision in modeling dispersion is dependent on the observed bandwidth. In this work, we calculate the offsets in infinite-frequency TOAs due to misestimations in the modeling of dispersion when using varying bandwidths at the Green Bank Telescope. We use a set of broadband observations of PSR J1643−1224, a pulsar with unusual chromatic timing behavior. We artificially restricted these observations to a narrowband frequency range, then used both the broad- and narrowband data sets to calculate residuals with a timing model that does not account for time variations in the dispersion. By fitting the resulting residuals to a dispersion model and comparing the fits, we quantify the error introduced in the timing parameters due to using a reduced frequency range. Moreover, by calculating the autocovariance function of the parameters, we obtained a characteristic timescale over which the dispersion misestimates are correlated. For PSR J1643−1224, which has one of the highest dispersion measures (DM) in the NANOGrav pulsar timing array, we find that the infinite-frequency TOAs suffer from a systematic offset of ∼22 μs due to incomplete frequency sampling, with correlations over about one month. For lower-DM pulsars, the offset is ∼7 μs. This error quantification can be used to provide more robust noise modeling in the NANOGrav data, thereby increasing the sensitivity and improving the parameter estimation in gravitational wave searches.

Vortex Effects in Merging Black Holes and Saturons.

Vorticity has recently been suggested to be a property of highly spinning black holes. The connection between vorticity and limiting spin represents a universal feature shared by objects of maximal microstate entropy, so-called saturons. Using Q-ball-like saturons as a laboratory for black holes, we study the collision of two such objects and find that vorticity can have a large impact on the emitted radiation as well as on the charge and angular momentum of the final configuration. As black holes belong to the class of saturons, we expect that the formation of vortices can cause similar effects in black hole mergers, leading to macroscopic deviations in gravitational radiation. This could leave unique signatures detectable with upcoming gravitational-wave searches, which can thereby serve as a portal to macroscopic quantum effects in black holes.

Search for continuous gravitational waves directed at subthreshold radiometer candidates in O3 LIGO data

Search for continuous gravitational waves directed at subthreshold radiometer candidates in O3 LIGO data

Symmetries and selection rules: optimising axion haloscopes for Gravitational Wave searches

In the presence of electromagnetic fields, both axions and gravitational waves (GWs) induce oscillating magnetic fields: a potentially detectable fingerprint of their presence. We demonstrate that the response is largely dictated by the symmetries of the instruments used to search for it. Focussing on low mass axion haloscopes, we derive selection rules that determine the parametric sensitivity of different detector geometries to axions and GWs, and which further reveal how to optimise the experimental geometry to maximise both signals. The formalism allows us to forecast the optimal sensitivity to GWs in the range of 100 kHz to 100 MHz for instruments such as ABRACADABRA, BASE, ADMX SLIC, SHAFT, WISPLC, and DMRadio.

Testing strengths, limitations, and biases of current pulsar timing arrays’ detection analyses on realistic data

State-of-the-art searches for gravitational waves (GWs) in pulsar timing array (PTA) datasets model the signal as an isotropic, Gaussian, and stationary process described by a power law. In practice, none of these properties are expected to hold for an incoherent superposition of GWs generated by a cosmic ensemble of supermassive black hole binaries (SMBHBs). This stochastic signal is usually referred to as the GW background (GWB) and is expected to be the primary signal in the PTA band. We performed a systematic investigation of the performance of current search algorithms, using a simple power-law model to characterise GW signals in realistic datasets. We used, as the baseline dataset, synthetic realisations of timing residuals mimicking the European PTA (EPTA) second data release (DR2). Thus, we included in the dataset uneven time stamps, achromatic and chromatic red noise, and multi-frequency observations. We then injected timing residuals from an ideal isotropic, Gaussian, single power-law stochastic process and from a realistic population of SMBHBs, performing a methodical investigation of the recovered signal. We found that current search models are efficient at recovering the GW signal, but several biases can be identified due to the signal-template mismatch, which we identified via probability-probability (P–P) plots and quantified using Kolmogorov-Smirnov (KS) statistics. We discuss our findings in light of the signal observed in the EPTA DR2 and corroborate its consistency with a SMBHB origin.

The NANOGrav 12.5 yr Data Set: A Computationally Efficient Eccentric Binary Search Pipeline and Constraints on an Eccentric Supermassive Binary Candidate in 3C 66B

The radio galaxy 3C 66B has been hypothesized to host a supermassive black hole binary (SMBHB) at its center based on electromagnetic observations. Its apparent 1.05 yr period and low redshift (∼0.02) make it an interesting testbed to search for low-frequency gravitational waves (GWs) using pulsar timing array (PTA) experiments. This source has been subjected to multiple searches for continuous GWs from a circular SMBHB, resulting in progressively more stringent constraints on its GW amplitude and chirp mass. In this paper, we develop a pipeline for performing Bayesian targeted searches for eccentric SMBHBs in PTA data sets, and test its efficacy by applying it to simulated data sets with varying injected signal strengths. We also search for a realistic eccentric SMBHB source in 3C 66B using the NANOGrav 12.5 yr data set employing PTA signal models containing Earth term-only as well as Earth+pulsar term contributions using this pipeline. Due to limitations in our PTA signal model, we get meaningful results only when the initial eccentricity e 0 < 0.5 and the symmetric mass ratio η > 0.1. We find no evidence for an eccentric SMBHB signal in our data, and therefore place 95% upper limits on the PTA signal amplitude of 88.1 ± 3.7 ns for the Earth term-only and 81.74 ± 0.86 ns for the Earth+pulsar term searches for e 0 < 0.5 and η > 0.1. Similar 95% upper limits on the chirp mass are (1.98 ± 0.05) × 109 and (1.81 ± 0.01) × 109 M ☉. These upper limits, while less stringent than those calculated from a circular binary search in the NANOGrav 12.5 yr data set, are consistent with the SMBHB model of 3C 66B developed from electromagnetic observations.

Improved Upper Limits on Gravitational-wave Emission from NS 1987A in SNR 1987A

We report on a new search for continuous gravitational waves from NS 1987A, the neutron star born in SN 1987A, using open data from Advanced LIGO and Virgo’s third observing run (O3). The search covered frequencies from 35–1050 Hz, more than 5 times the band of the only previous gravitational-wave search to constrain NS 1987A. Our search used an improved code and coherently integrated from 5.10 to 14.85 days depending on frequency. No astrophysical signals were detected. By expanding the frequency range and using O3 data, this search improved on strain upper limits from the previous search and was sensitive at the highest frequencies to ellipticities of 1.6 × 10−5 and r-mode amplitudes of 4.4 × 10−4, both an order of magnitude improvement over the previous search and both well within the range of theoretical predictions.

Gravitational Wave Search through Electromagnetic Telescopes

Abstract We study the graviton–photon conversion in the magnetic fields of the Earth, the Milky Way, and intergalactic regions. Requiring that the photon flux converted from gravitons does not exceed the observed photon flux with telescopes, we derive upper limits on the stochastic gravitational waves in frequency ranges from 107–1035 Hz. Remarkably, the upper limits on h2ΩGW could be less than unity in the frequency range of 1018–1023 Hz in a specific case. The detection of gravitational waves using telescopes could open up a new avenue for high frequency gravitational wave observations.

Targeted search for gravitational waves from highly spinning light compact binaries

Abstract Searches for gravitational waves from compact-binary mergers, which to date have reported ∼100 observations, have previously ignored binaries whose components are both consistent with the mass of neutron stars (1M⊙ to 2M⊙) and have high dimensionless spin &amp;gt;0.05. While previous searches targeted sources that are representative of observed neutron star binaries in the galaxy, it is already known that neutron stars can regularly be spun up to a dimensionless spin of ∼0.4, and in principle reach up to ∼0.7 before breakup would occur. Furthermore, there may be primordial black hole binaries or exotic formation mechanisms to produce light black holes. In these cases, it is possible for the binary constituent to be spun up beyond that achievable by a neutron star. A single detection of this type of source would reveal a novel formation channel for compact-binaries. To determine if there is evidence for any such sources, we use PyCBC to conduct a targeted search of LIGO and Virgo data for light compact objects with high spin. Our analysis detects previously known observations GW170817 and GW200115; however, we report no additional mergers. The most significant candidate, not previously known, is consistent with the noise distribution, and so we constrain the merger rate of spinning light binaries.

Piecewise frequency model for searches for long-transient gravitational waves from young neutron stars

Piecewise frequency model for searches for long-transient gravitational waves from young neutron stars

Adapting the PyCBC pipeline to find and infer the properties of gravitational waves from massive black hole binaries in LISA

The laser interferometer space antenna (LISA), due for launch in the mid 2030s, is expected to observe gravitational waves (GWs) from merging massive black hole binaries (MBHBs). These signals can last from days to months, depending on the masses of the black holes, and are expected to be observed with high signal to noise ratios (SNRs) out to high redshifts. We have adapted the PyCBC software package to enable a template bank search and inference of GWs from MBHBs. The pipeline is tested on the LISA data challenge’s Challenge 2a (‘Sangria’), which contains MBHBs and thousands of galactic binaries (GBs) in simulated instrumental LISA noise. Our search identifies all six MBHB signals with more than 92% of the optimal SNR. The subsequent parameter inference step recovers the masses and spins within their 90% confidence interval. Sky position parameters have eight high likelihood modes which are recovered but often our posteriors favour the incorrect sky mode. We observe that the addition of GBs biases the parameter recovery of masses and spins away from the injected values, reinforcing the need for a global fit pipeline which will simultaneously fit the parameters of the GB signals before estimating the parameters of MBHBs.

Rapid Localization of Gravitational Wave Sources from Compact Binary Coalescences Using Deep Learning

The mergers of neutron star–neutron star and neutron star–black hole binaries (NSBHs) are the most promising gravitational wave (GW) events with electromagnetic (EM) counterparts. The rapid detection, localization, and simultaneous multimessenger follow-up of these sources are of primary importance in the upcoming science runs of the LIGO-Virgo-KAGRA Collaboration. While prompt EM counterparts during binary mergers can last less than 2 s, the timescales of existing localization methods that use Bayesian techniques, vary from seconds to days. In this paper, we propose the first deep learning–based approach for rapid and accurate sky localization of all types of binary coalescences, including neutron star–neutron star and NSBHs for the first time. Specifically, we train and test a normalizing flow model on matched-filtering output from GW searches to obtain sky direction posteriors in around 1 s using a single P100 GPU, which is several orders of magnitude faster than full Bayesian techniques.

Correction to: Precision Ephemerides for Gravitational-wave Searches – IV. Corrected and refined ephemeris for Scorpius X-1

Correction to: Precision Ephemerides for Gravitational-wave Searches – IV. Corrected and refined ephemeris for Scorpius X-1

Towards a robust and reliable deep learning approach for detection of compact binary mergers in gravitational wave data

The ability of deep learning (DL) approaches to learn generalised signal and noise models, coupled with their fast inference on GPUs, holds great promise for enhancing gravitational-wave (GW) searches in terms of speed, parameter space coverage, and search sensitivity. However, the opaque nature of DL models severely harms their reliability. In this work, we meticulously develop a DL model stage-wise and work towards improving its robustness and reliability. First, we address the problems in maintaining the purity of training data by deriving a new metric that better reflects the visual strength of the ‘chirp’ signal features in the data. Using a reduced, smooth representation obtained through a variational auto-encoder (VAE), we build a classifier to search for compact binary coalescence (CBC) signals. Our tests on real LIGO data show an impressive performance of the model. However, upon probing the robustness of the model through adversarial attacks, its simple failure modes were identified, underlining how such models can still be highly fragile. As a first step towards bringing robustness, we retrain the model in a novel framework involving a generative adversarial network (GAN). Over the course of training, the model learns to eliminate the primary modes of failure identified by the adversaries. Although absolute robustness is practically impossible to achieve, we demonstrate some fundamental improvements earned through such training, like sparseness and reduced degeneracy in the extracted features at different layers inside the model. We show that these gains are achieved at practically zero loss in terms of model performance on real LIGO data before and after GAN training. Through a direct search on days of LIGO data, we recover two significant CBC events from GWTC-2.1 (Abbott et al 2022 2108.01045 [gr-qc]), GW190519_153544 and GW190521_074359. We also report the search sensitivity obtained from an injection study.

Improving the spin-down limits of the continuous gravitational waves emitted from rotating triaxial pulsars

The spin-down limit of the continuous gravitational wave strain from pulsars assumed to be triaxial stars rotating about a principal moment of inertia axis depends upon the value of the intrinsic spin frequency derivative of the pulsar, among other parameters. In order to get more accurate intrinsic spin frequency derivative values, dynamical effects contributing to the measured spin frequency derivative values must be estimated via more realistic approaches. In this work, we calculated improved values for the spin-down limit of the continuous gravitational wave strain (assuming that pulsars are triaxial stars rotating about a principal moment of inertia axis) for a set of 237 pulsars for which a targeted search for continuous gravitational waves was recently carried out by the LIGO-Virgo-KAGRA (LVK) Collaboration. We used ‘GalDynPsr’, a Python-based public package, to calculate more realistic values for the intrinsic spin frequency derivatives and, consequently, we get more realistic values of the spin-down limit. The realistic values that we obtain for the intrinsic spin frequency derivatives can also provide a valuable contribution to improving the sensitivity of searches for continuous gravitational waves from known pulsars.

Banks of templates for directed and all-sky narrow-band searches of continuous gravitational waves from spinning neutron stars with several spindowns

We construct efficient banks of templates suitable for searches of continuous gravitational waves from isolated spinning neutron stars. We assume that the search algorithm is based on the time-domain maximum-likelihood -statistic and we consider narrow-band searches with several spindown parameters included. Our template banks are suitable for both all-sky and directed searches and they enable the usage of the fast Fourier transform in the computation of the -statistic as well as, in the case of all-sky searches, efficient resampling of data to barycentric time.

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.