In a previous article, we argued that angular non-stationarities of gamma-ray burst (GRB) jets can result in a statistical connection between the angle values deduced from jet break times and the variabilities of prompt light curves. The connection should be an anticorrelation if luminosity densities of jets follow a power-law or a uniform profile, and a correlation if they have a Gaussian profile. In this follow-up paper, we search for the connection by measuring Spearman’s rank correlation coefficient in a sample of 19 long GRBs observed by the Swift satellite. Using 16 of the GRBs with well-defined angle measurements, we find ρ=−0.38+0.1−0.1ρ=−0.38−0.1+0.1 and p=0.15+0.14−0.09p=0.15−0.09+0.14. Adding three more GRBs to the sample, each with a pair of equally possible angle values, can strengthen the anticorrelation to ρ=−0.46+0.09−0.08ρ=−0.46−0.08+0.09 and p=0.05+0.07−0.03p=0.05−0.03+0.07. We show that these results are incompatible with non-stationary jets having Gaussian profiles, and that ≳100 GRBs with observed afterglows would be needed to confirm the potential existence of the angle-variability anticorrelation with 3σ significance. If the connection is real, GRB jet angles would be constrainable from prompt gamma light curves, without the need of afterglow observations.

Our current understanding of the core-collapse supernova explosion mechanism is incomplete, with multiple viable models for how the initial shock wave might be energized enough to lead to a successful explosion. Detection of a gravitational-wave signal emitted in the initial few seconds after stellar core-collapse would provide unique and crucial insight into this process. With the Advanced LIGO and Advanced Virgo detectors expected to approach their design sensitivities soon, we could potentially detect this signal from a supernova within our galaxy. In anticipation of such a scenario, we study how well the BayesWave algorithm can recover the gravitational-wave signal from core-collapse supernova models in simulated advanced detector noise, and optimize its ability to accurately reconstruct the signal waveforms. We find that BayesWave can confidently reconstruct the signal from a range of supernova explosion models in Advanced LIGO-Virgo for network signal-to-noise ratios ≳30 , reaching maximum reconstruction accuracies of ∼90 % at SNR ∼100 . For low SNR signals that are not confidently recovered, our optimization efforts result in gains in reconstruction accuracy of up to 20%-40%, with typical gains of ∼10 %.

We present GLADE+, an extended version of the GLADE galaxy catalogue introduced in our previous paper for multimessenger searches with advanced gravitational-wave detectors. GLADE+ combines data from six separate but not independent astronomical catalogues: the GWGC, 2MPZ, 2MASS XSC, HyperLEDA, and WISExSCOSPZ galaxy catalogues, and the SDSS-DR16Q quasar catalogue. To allow corrections of CMB-frame redshifts for peculiar motions, we calculated peculiar velocities along with their standard deviations of all galaxies having B-band magnitude data within redshift z=0.05 using the “Bayesian Origin Reconstruction from Galaxies” formalism. GLADE+ is complete up to luminosity distance dL=47+4−2 Mpc in terms of the cumulative B-band luminosity of galaxies, and contains all of the brightest galaxies giving half of the total B-band luminosity up to dL≃250 Mpc. We include estimations of stellar masses and individual binary neutron star merger rates for galaxies with W1 magnitudes in GLADE+. These parameters can help in ranking galaxies in a given gravitational wave localization volume in terms of their likelihood of being hosts, thereby possibly reducing the number of pointings and total integration time needed to find the electromagnetic counterpart.

The aim of our research was to adapt Chuine’s unified model to estimate the beginning of blooming of three apricot cultivars (‘Ceglédi bíborkajszi’, ‘Gönci magyar kajszi’, and ‘Rózsakajszi C.1406’) in Hungary in the time period 1994–2020. The unified model is based on the collection of chilling and forcing units. The complexity of the model lies in the high number of parameters necessary to run it. Following the work of other researchers, we reduced the number of relevant model parameters (MP) to six. In order to estimate the six MPs, we used a simulated annealing optimization method (known for being effective in avoiding getting stuck in local minima). From the results, we determined the local optimum of six MPs, and the global optimum parameter vector for three apricot cultivars. With these global optimum parameter vectors, the beginning of blooming could be estimated with a root-mean-square error (RMSE) of less than 2.5 days, using the knowledge of the daily mean temperature in the time period 1994–2020.

We present a comprehensive study on how well gravitational-wave signals of binary black holes (BBHs) with nonzero eccentricities can be recovered with state of the art model-independent waveform reconstruction and parameter estimation techniques. For this we use BayesWave, a Bayesian algorithm used by the LIGO–Virgo Collaboration for unmodeled reconstructions of signal waveforms and parameters. We used two different waveform models to produce simulated signals of BBHs with eccentric orbits and embed them in samples of simulated noise of design-sensitivity Advanced LIGO detectors. We studied the network overlaps and point estimates of central moments of signal waveforms recovered by BayesWave as a function of e, the eccentricity of the binary at 8 Hz orbital frequency. BayesWave recovers signals of near-circular (e lesssim 0.2) and highly eccentric (e gsim 0.7) binaries with network overlaps similar to that of circular (e = 0) ones, however it produces lower network overlaps for binaries with e ∈ [0.2, 0.7]. Estimation errors on central frequencies and bandwidths (measured relative to bandwidths) are nearly independent from e, while estimation errors on central times and durations (measured relative to durations) increase and decrease with e above e gsim 0.5, respectively. We also tested how BayesWave performs when reconstructions are carried out using generalized wavelets with linear frequency evolution (chirplets) instead of sine-Gaussian wavelets. We have found that network overlaps improve by ~10–20 percent when chirplets are used, and the improvement is the highest at low (e < 0.5) eccentricities. There is however no significant change in the estimation errors of central moments when the chirplet base is used.

We show that for detections of gravitational-wave transients, constraints can be given on physical parameters of the source without using any specific astrophysical models. Relying only on fundamental principles of general relativity, we can set upper limits on the size, mass, and distance of the source solely from characteristics of the observed waveform. If the distance of the source is known from independent (e.g. electromagnetic) observations, we can also set lower limits on the mass and size. As a demonstration, we tested these constraints on binary black hole signals observed by the LIGO and Virgo detectors during their first and second observing runs, as well as on simulated binary black hole and core-collapse supernova signals reconstructed from simulated detector data. We have found that our constraints are valid for all analyzed source types, but their efficiency (namely, how far they are from the true parameter values) strongly depends on the source type, ranging from being in the same order of magnitude to a several orders of magnitude difference. In cases when a gravitational-wave signal is reconstructed without waveform templates and no astrophysical model on the source is available, these constraints provide the only quantitative characterization of the source that can guide the astrophysical modeling process.

We propose a method to detect possible non-stationarities of gamma-ray burst jets. Assuming that the dominant source of variability in the prompt gamma light curve is the non-stationarity of the jet, we show that there should be a connection between the variability measure and the characteristic angle of the jet derived from the jet break time of the afterglow. We carried out Monte Carlo simulations of long gamma-ray burst observations assuming three radial luminosity density profiles for jets and randomizing all burst parameters, and created samples of gamma light curves by simulating jets undergoing Brownian motions with linear restoring forces. We were able to demonstrate that the connection between the variability and the characteristic angle is an anticorrelation in case of uniform and power-law jet profiles, and a correlation in case of a Gaussian profile. We have found that as low as 50 (144) gamma-ray burst observations with jet angle measurements can be sufficient for a 3σ (5σ) detection of the connection. The number of observations required for the detection depends on the underlying jet beam profile, ranging from 50 (144) to 237 (659) for the four specific profile models we tested.

Galactic nuclei are expected to be one of the main sites for formations of eccentric binary black holes (EBBHs), with an estimated detection rate of O(1−100 yr−1) with Advanced LIGO (aLIGO) detectors operating at design sensitivity. Two of the main formation channels of these binaries are gravitational capture and the secular Kozai-Lidov mechanism, with expectedly commensurable formation rates. We used Monte Carlo simulations to construct the eccentricity distributions of EBBHs formed through these channels in galactic nuclei, at the time their gravitational-wave signals enter the aLIGO band at 10 Hz. We have found that the proportion of binary black holes entering the aLIGO band with eccentricities larger than 0.1 is ∼10 percent for the secular Kozai-Lidov mechanism, and ∼90 percent for gravitational capture. We show that if future EBBH detection rates with aLIGO will be dominated by EBBHs formed in galactic nuclei, then the proportions of EBBHs formed through the two main channels can be constrained to a ΔF=0.2 wide one-sigma confidence interval with a few tens of observations, even if parameter estimation errors are taken into account at realistic levels.

We perform a statistical standard siren analysis of GW170817. Our analysis does not utilize knowledge of NGC 4993 as the unique host galaxy of the optical counterpart to GW170817. Instead, we consider each galaxy within the GW170817 localization region as a potential host; combining the redshift from each galaxy with the distance estimate from GW170817 provides an estimate of the Hubble constant, H0. We then combine the H0 values from all the galaxies to provide a final measurement of H0. We explore the dependence of our results on the thresholds by which galaxies are included in our sample, as well as the impact of weighting the galaxies by stellar mass and star-formation rate. Considering all galaxies brighter than 0.01L⋆B as equally likely to host a BNS merger, we find H0=76+48−23 km s−1 Mpc−1 (maximum a posteriori and 68.3% highest density posterior interval; assuming a flat H0prior in the range [10,220] km s−1 Mpc−1). Restricting only to galaxies brighter than 0.626L⋆B tightens the measurement to H0=77+37−18 km s−1 Mpc−1. We show that weighting the host galaxies by stellar mass or star-formation rate provides entirely consistent results with potentially tighter constraints. While these statistical estimates are inferior to the value from the counterpart standard siren measurement utilizing NGC 4993 as the unique host, H0=76+19−13 km s−1 Mpc−1 (determined from the same publicly available data), our analysis is a proof-of-principle demonstration of the statistical approach first proposed by Bernard Schutz over 30 years ago.

We introduce a value-added full-sky catalogue of galaxies, named as Galaxy List for the Advanced Detector Era, or GLADE. The purpose of this catalogue is to (i) help identifications of host candidates for gravitational-wave events, (ii) support target selections for electromagnetic follow-up observations of gravitational-wave candidates, (iii) provide input data on the matter distribution of the local universe for astrophysical or cosmological simulations, and (iv) help identifications of host candidates for poorly localised electromagnetic transients, such as gamma-ray bursts observed with the InterPlanetary Network. Both being potential hosts of astrophysical sources of gravitational waves, GLADE includes inactive and active galaxies as well. GLADE was constructed by cross-matching and combining data from five separate (but not independent) astronomical catalogues: GWGC, 2MPZ, 2MASS XSC, HyperLEDA and SDSS-DR12Q. GLADE is complete up to dL=37+3−4 Mpc in terms of the cumulative B-band luminosity of galaxies within luminosity distance dL, and contains all of the brightest galaxies giving half of the total B-band luminosity up to dL=91 Mpc. As B-band luminosity is expected to be a tracer of binary neutron star mergers (currently the prime targets of joint GW+EM detections), our completeness measures can be used as estimations of completeness for containing all binary neutron star merger hosts in the local universe.

Mergers of binary black holes on eccentric orbits are among the targets for second generation ground-based gravitational-wave detectors. These sources may commonly form in galactic nuclei due to gravitational-wave emission during close flyby events of single objects. We determine the distributions of initial orbital parameters for a population of these gravitational-wave sources. Our results show that the initial dimensionless pericenter distance systematically decreases with the binary component masses and the mass of the central supermassive black hole, and its distribution depend sensitively on the highest possible black hole mass in the nuclear star cluster. For a multi-mass black hole population with masses between 5 Msun and 80 Msun, more than 40% of sources have an eccentricity greater than 0.1 when the gravitational-wave signal reaches 10 Hz or if it forms at higher frequencies, but only 7% of the sources with binary component masses less than 30 Msun remain eccentric at this level near the last stable orbit (LSO). The eccentricity at LSO is typically between 0.005-0.05 for the lower mass BHs, and 0.1-0.2 for the highest mass BHs. Thus, due to the limited low-frequency sensitivity, the currently known six quasicircular LIGO/Virgo sources are compatible with this originally highly eccentric source population. At the design sensitivity of these instruments, the measurement of the eccentricity and mass distribution of merger events may be a useful diagnostic to distinguish among different astrophysical binary formation channels.

Mergers of stellar-mass black holes on highly eccentric orbits are among the targets for ground-based gravitational-wave detectors, including LIGO, VIRGO, and KAGRA. These sources may commonly form through gravitational-wave emission in high velocity dispersion systems or through the secular Kozai-Lidov mechanism in triple systems. Gravitational waves carry information about the binaries’ orbital parameters and source location. Using the Fisher matrix technique, we determine the measurement accuracy with which the LIGO-VIRGO-KAGRA network could measure the source parameters of eccentric binaries using a matched filtering search of the repeated burst and eccentric inspiral phases of the waveform. We account for general relativistic precession and the evolution of the orbital eccentricity and frequency during the inspiral. We find that the signal-to-noise ratio and the parameter measurement accuracy may be significantly higher for eccentric sources than for circular sources. This increase is sensitive to the initial pericenter distance, the initial eccentricity, and component masses. For instance, compared to a 30 Msun-30 Msun non-spinning circular binary, the chirp mass and sky localization accuracy can improve for an initially highly eccentric binary by a factor of ~129 (38) and ~2 (11) assuming an initial pericenter distance of 20 Mtot (10 Mtot).

We introduce two novel time-dependent figures of merit for both online and offline optimizations of advanced gravitational-wave (GW) detector network operations with respect to (i) detecting continuous signals from known source locations and (ii) detecting GWs of neutron star binary coalescences from known local galaxies, which thereby have the highest potential for electromagnetic counterpart detection. For each of these scientific goals, we characterize an N-detector network, and all its (N  −  1)-detector subnetworks, to identify subnetworks and individual detectors (key contributors) that contribute the most to achieving the scientific goal. Our results show that aLIGO-Hanford is expected to be the key contributor in 2017 to the goal of detecting GWs from the Crab pulsar within the network of LIGO and Virgo detectors. For the same time period and for the same network, both LIGO detectors are key contributors to the goal of detecting GWs from the Vela pulsar, as well as to detecting signals from 10 high interest pulsars. Key contributors to detecting continuous GWs from the Galactic Center can only be identified for finite time intervals within each sidereal day with either the 3-detector network of the LIGO and Virgo detectors in 2017, or the 4-detector network of the LIGO, Virgo, and KAGRA detectors in 2019–2020. Characterization of the LIGO-Virgo detectors with respect to goal (ii) identified the two LIGO detectors as key contributors. Additionally, for all analyses, we identify time periods within a day when lock losses or scheduled service operations could result with the least amount of signal-to-noise or transient detection probability loss for a detector network.

We provide a comprehensive multi-aspect study on the performance of a pipeline used by the LIGO-Virgo Collaboration for estimating parameters of gravitational-wave bursts. We add simulated signals with four different morphologies (sine-Gaussians, Gaussians, white-noise bursts, and binary black hole signals) to simulated noise samples representing noise of the two Advanced LIGO detectors during their first observing run. We recover them with the BayesWave (BW) pipeline to study its accuracy in sky localization, waveform reconstruction, and estimation of model-independent waveform parameters. BW localizes sources with a level of accuracy comparable for all four morphologies, with the median separation of actual and estimated sky locations ranging from 25.1∘ to 30.3∘. This is a reasonable accuracy in the two-detector case, and is comparable to accuracies of other localization methods studied previously. As BW reconstructs generic transient signals with sine-Gaussian wavelets, it is unsurprising that BW performs the best in reconstructing sine-Gaussian and Gaussian waveforms. BW’s accuracy in waveform reconstruction increases steeply with network signal-to-noise ratio (SNRnet), reaching a 85% and 95% match between the reconstructed and actual waveform below SNRnet≈20 and SNRnet≈50, respectively, for all morphologies. BW’s accuracy in estimating central moments of waveforms is only limited by statistical errors in the frequency domain, and is affected by systematic errors too in the time domain as BW cannot reconstruct low-amplitude parts of signals overwhelmed by noise. The figures of merit we introduce can be used in future characterizations of parameter estimation pipelines.

We propose an observational test for gravitationally recoiling supermassive black holes (BHs) in active galactic nuclei, based on a correlation between the velocities of BHs relative to their host galaxies, |Δv|, and their obscuring dust column densities, Σ_dust (both measured along the line of sight). We use toy models for the distribution of recoil velocities, BH trajectories, and the geometry of obscuring dust tori in galactic centres, to simulate 2.5 × 10⁵ random observations of recoiling quasars. BHs with recoil velocities comparable to the escape velocity from the galactic centre remain bound to the nucleus, and do not fully settle back to the centre of the torus due to dynamical friction in a typical quasar lifetime. We find that |Δv| and Σ_dust for these BHs are positively correlated. For obscured (Σ_dust > 0) and for partially obscured (0 < Σ_dust ≲ 2.3 g m^-2) quasars with |Δv| ≥ 45 km s^-1, the sample correlation coefficient between log₁₀(|Δv|) and Σ_dust is r₄₅ = 0.28 ± 0.02 and r₄₅ = 0.13 ± 0.02, respectively. Allowing for random ± 100 km s^{– 1} errors in |Δv| unrelated to the recoil dilutes the correlation for the partially obscured quasars to r₄₅ = 0.026 ± 0.004 measured between |Δv| and Σ_dust. A random sample of ≳ 3500 obscured quasars with |Δv| ≥ 45 km s^-1would allow rejection of the no-correlation hypothesis with 3σ significance 95 per cent of the time. Finally, we find that the fraction of obscured quasars, {F_obs} (|Δv|), decreases with |Δv| from {F_obs} (<10 km s^-1) ≳ 0.8 to {F_obs} (>10³ km s^-1) ≲ 0.4. This predicted trend can be compared to the observed fraction of type II quasars, and can further test combinations of recoil, trajectory, and dust torus models.

We consider the optimal site selection of future generations of gravitational wave (GW) detectors. Previously, Raffai et al optimized a two-detector network with a combined figure of merit (FoM). This optimization was extended to networks with more than two detectors in a limited way by first fixing the parameters of all other component detectors. In this work we now present a more general optimization that allows the locations of all detectors to be simultaneously chosen. We follow the definition of Raffai et al on the metric that defines the suitability of a certain detector network. Given the locations of the component detectors in the network, we compute a measure of the network’s ability to distinguish the polarization, constrain the sky localization and reconstruct the parameters of a GW source. We further define the ‘flexibility index’ for a possible site location, by counting the number of multi-detector networks with a sufficiently high FoM that include that site location. We confirm the conclusion of Raffai et al, that in terms of the flexibility index as defined in this work, Australia hosts the best candidate site to build a future generation GW detector. This conclusion is valid for either a three-detector network or a five-detector network. For a three-detector network, site locations in Northern Europe display a comparable flexibility index to sites in Australia. However, for a five-detector network, Australia is found to be a clearly better candidate than any other location.

We aim to find the optimal site locations for a hypothetical network of 1-3 triangular gravitational-wave telescopes. We define the following N-telescope figures of merit (FoMs) and construct three corresponding metrics: (a) capability of reconstructing the signal polarization; (b) accuracy in source localization; and (c) accuracy in reconstructing the parameters of a standard binary source. We also define a combined metric that takes into account the three FoMs with practically equal weight. After constructing a geomap of possible telescope sites, we give the optimal 2-telescope networks for the four FoMs separately in example cases where the location of the first telescope has been predetermined. We found that based on the combined metric, placing the first telescope to Australia provides the most options for optimal site selection when extending the network with a second instrument. We suggest geographical regions where a potential second and third telescope could be placed to get optimal network performance in terms of our FoMs. Additionally, we use a similar approach to find the optimal location and orientation for the proposed LIGO-India detector within a five-detector network with Advanced LIGO (Hanford), Advanced LIGO (Livingston), Advanced Virgo, and KAGRA. We found that the FoMs do not change greatly in sites within India, though the network can suffer a significant loss in reconstructing signal polarizations if the orientation angle of an L-shaped LIGO-India is not set to the optimal value of ~58.2°( + k × 90°) (measured counterclockwise from East to the bisector of the arms).

We have performed an in-depth concept study of a gravitational wave data analysis method which targets repeated long quasimonochromatic transients (triggers) from cosmic sources. The algorithm concept can be applied to multitrigger data sets in which the detector-source orientation and the statistical properties of the data stream change with time, and does not require the assumption that the data is Gaussian. Reconstructing or limiting the energetics of potential gravitational wave emissions associated with quasiperiodic oscillations observed in the x-ray lightcurve tails of soft gamma repeater flares might be an interesting endeavor of the future. Therefore we chose this in a simplified form to illustrate the flow, capabilities, and performance of the method. We investigate performance aspects of a multitrigger based data analysis approach by using O(100s) long stretches of mock data in coincidence with the times of observed quasiperiodic oscillations, and by using the known sky location of the source. We analytically derive the probability density function of the background distribution and compare to the results obtained by applying the concept to simulated Gaussian noise, as well as off-source playground data collected by the 4-km Hanford detector during LIGO’s fifth science run (S5). We show that the transient glitch rejection and adaptive differential energy comparison methods we apply succeed in rejecting outliers in the fifth science run background data. Finally, we discuss how to extend the method to a network containing multiple detectors, and as an example, tune the method to maximize sensitivity to soft gamma repeater 1806-20 flare times.

We present the baseline multimessenger analysis method for the joint observations of gravitational waves (GW) and high-energy neutrinos (HEN), together with a detailed analysis of the expected science reach of the joint search. The analysis method combines data from GW and HEN detectors, and uses the blue-luminosity-weighted distribution of galaxies. We derive expected GW+HEN source rate upper limits for a wide range of source parameters covering several emission models. Using published sensitivities of externally triggered searches, we derive joint upper limit estimates both for the ongoing analysis with the initial LIGO-Virgo GW detectors with the partial IceCube detector (22 strings) HEN detector and for projected results to advanced LIGO-Virgo detectors with the completed IceCube (86 strings). We discuss the constraints these upper limits impose on some existing GW+HEN emission models.

We present an experimental opportunity for the future to measure possible violations to Newton’s 1/r² law in the 0.1-10 m range using dynamic gravity field generators (DFG) and taking advantage of the exceptional sensitivity of modern interferometric techniques. The placement of a DFG in proximity to one of the interferometer’s suspended test masses generates a change in the local gravitational field that can be measured at a high signal to noise ratio. The use of multiple DFGs in a null-experiment configuration allows us to test composition-independent non-Newtonian gravity significantly beyond the present limits. Advanced and third-generation gravitational-wave detectors are representing the state-of-the-art in interferometric distance measurement today, therefore, we illustrate the method through their sensitivity to emphasize the possible scientific reach. Nevertheless, it is expected that due to the technical details of gravitational-wave detectors, DFGs shall likely require dedicated custom-configured interferometry. However, the sensitivity measure we derive is a solid baseline indicating that it is feasible to consider probing orders of magnitude into the pristine parameter well beyond the present experimental limits significantly cutting into the theoretical parameter space.

Searches for gravitational waves (GWs) traditionally focus on persistent sources (e.g., pulsars or the stochastic background) or on transients sources (e.g., compact binary inspirals or core-collapse supernovae), which last for time scales of milliseconds to seconds. We explore the possibility of long GW transients with unknown waveforms lasting from many seconds to weeks. We propose a novel analysis technique to bridge the gap between short O(s) “burst” analyses and persistent stochastic analyses. Our technique utilizes frequency-time maps of GW strain cross power between two spatially separated terrestrial GW detectors. The application of our cross power statistic to searches for GW transients is framed as a pattern recognition problem, and we discuss several pattern-recognition techniques. We demonstrate these techniques by recovering simulated GW signals in simulated detector noise. We also recover environmental noise artifacts, thereby demonstrating a novel technique for the identification of such artifacts in GW interferometers. We compare the efficiency of this framework to other techniques such as matched filtering.

We derive a conservative coincidence time window for joint searches of gravitational-wave (GW) transients and high-energy neutrinos (HENs, with energies ≳100 GeV), emitted by gamma-ray bursts (GRBs). The last are among the most interesting astrophysical sources for coincident detections with current and near-future detectors. We take into account a broad range of emission mechanisms. We take the upper limit of GRB durations as the 95% quantile of the T₉₀‘s of GRBs observed by BATSE, obtaining a GRB duration upper limit of ˜150 s. Using published results on high-energy (>100 MeV) photon light curves for 8 GRBs detected by Fermi LAT, we verify that most high-energy photons are expected to be observed within the first ˜150 s of the GRB. Taking into account the breakout-time of the relativistic jet produced by the central engine, we allow GW and HEN emission to begin up to 100 s before the onset of observable gamma photon production. Using published precursor time differences, we calculate a time upper bound for precursor activity, obtaining that 95% of precursors occur within ˜250 s prior to the onset of the GRB. Taking the above different processes into account, we arrive at a time window of t_HEN – t_GW ∈ [-500 s, +500 s]. Considering the above processes, an upper bound can also be determined for the expected time window of GW and/or HEN signals coincident with a detected GRB, t_GW – t_GRB ≈ t_HEN– t_GRB ∈ [-350 s, +150 s]. These upper bounds can be used to limit the coincidence time window in multimessenger searches, as well as aiding the interpretation of the times of arrival of measured signals.

We have developed advanced seismic attenuation systems for Gravitational Wave (GW) detectors. The design consists of an Inverted Pendulum (IP) holding stages of Geometrical Anti-Spring Filters (GASF) and pendula, which isolate the test mass suspension from ground noise. The ultra-low-frequency IP suppresses the horizontal seismic noise, while the GASF suppresses the vertical ground vibrations. The three legs of the IP are supported by cylindrical maraging steel flexural joints. The IP can be tuned to very low frequencies by carefully adjusting its load. As a best result, we have achieved an ultra low, ~12 mHz pendulum frequency for the system prototype made for Advanced LIGO (Laser Interferometer Gravitational Wave Observatory). The measured quality factor, Q, of this IP, ranging from Q~2500 (at 0.45 Hz) to Q~2 (at 12 mHz), is compatible with structural damping, and is proportional to the square of the pendulum frequency. Tunable counterweights allow for precise center-of-percussion tuning to achieve the required attenuation up to the first leg internal resonance (~60 Hz for advanced LIGO prototype). All measurements are in good agreement with our analytical models. We therefore expect good attenuation in the low-frequency region, from ~0.1 to ~50 Hz, covering the micro-seismic peak. The extremely soft IP requires minimal control force, which simplifies any needed actuation.

We present two general methods, the so-called Locust and the generalized Hough algorithm, to search for narrow-band signals of moderate frequency evolution and limited duration in datastreams of gravitational wave detectors. Some models of long gamma-ray bursts (e.g. van Putten et al 2004 Phys. Rev. D 69 044007) predict narrow-band gravitational wave burst signals of limited duration emitted during the gamma-ray burst event. These types of signals give rise to curling traces of local maxima in the time frequency space that can be recovered via image processing methods (Locust and Hough). Tests of the algorithms in the context of the van Putten model were carried out using injected simulated signals into Gaussian white noise and also into LIGO-like data. The Locust algorithm has the relative advantage of having higher speed and better general sensitivity; however, the generalized Hough algorithm is more tolerant of trace discontinuities. A combination of the two algorithms increases search robustness and sensitivity at the price of execution speed.

We present an approach to experimentally evaluate gravity gradient noise, a potentially limiting noise source in advanced interferometric gravitational wave (GW) detectors. In addition, the method can be used to provide sub-percent calibration in phase and amplitude of modern interferometric GW detectors. Knowledge of calibration to such certainties shall enhance the scientific output of the instruments in case of an eventual detection of GWs. The method relies on a rotating symmetrical two-body mass, a Dynamic gravity Field Generator (DFG). The placement of the DFG in the proximity of one of the interferometer’s suspended test masses generates a change in the local gravitational field detectable with current interferometric GW detectors.