137 research outputs found
Fractal Analysis of Data from Seismometer Array Monitoring Virgo Interferometer
No full textThe local Hurst exponent H(t) has been computed for an array of 38 seismometers, deployed at the Virgo West End Building for Newtonian Noise characterisation purposes. The analysed period is from January 31st, 2018 to February 5th, 2018. The Hurst exponent H is a fractal index quantifying the persistent behaviour of a time series, higher H corresponding to higher persistency. The adopted methodology makes use of the local Hurst exponent computed using small sliding windows, in order to characterise the properties of the seismometers. Hourly averages and averages of H(t) have been computed over the whole analysed period. Results show that seismometers placed on a concrete slab closer to the centre of the room systematically exhibit higher persistency than the ones that are not placed on it. Seismometers placed next to the outer walls also exhibit higher persistency. The seismometer placed on a thin metal plate exhibits instead very low values of persistency during the analysed period, compared to the rest of the array
Characterization of the seismic field at Virgo and improved estimates of Newtonian-noise suppression by recesses
No full textFluctuations of gravitational forces cause so-called Newtonian noise (NN) in gravitational-wave detectors which is expected to limit their low-frequency sensitivity in upcoming observing runs. Seismic NN is produced by seismic waves passing near a detector's suspended test masses. It is predicted to be the strongest contribution to NN. Modeling this contribution accurately is a major challenge. Arrays of seismometers were deployed at the Virgo site to characterize the seismic field near the four test masses. In this paper, we present results of a spectral analysis of the array data from one of Virgo's end buildings to identify dominant modes of the seismic field. Some of the modes can be associated with known seismic sources. Analyzing the modes over a range of frequencies, we provide a dispersion curve of Rayleigh waves. We find that the Rayleigh speed in the NN frequency band 10-20 Hz is very low (≲100 m s-1), which has important consequences for Virgo's seismic NN. Using the new speed estimate, we find that the recess formed under the suspended test masses by a basement level at the end buildings leads to a 10 fold reduction of seismic NN
Machine learning for gravitational-wave detection: Surrogate Wiener filtering for the prediction and optimized cancellation of Newtonian noise at Virgo
No full textThe cancellation of noise from terrestrial gravity fluctuations, also known as Newtonian noise (NN), in gravitational-wave detectors is a formidable challenge. Gravity fluctuations result from density perturbations associated with environmental fields, e.g., seismic and acoustic fields, which are characterized by complex spatial correlations. Measurements of these fields necessarily provide incomplete information, and the question is how to make optimal use of available information for the design of a noise-cancellation system. In this paper, we present a machine-learning approach to calculate a surrogate model of a Wiener filter. The model is used to calculate optimal configurations of seismometer arrays for a varying number of sensors, which is the missing keystone for the design of NN cancellation systems. The optimization results indicate that efficient noise cancellation can be achieved even for complex seismic fields with relatively few seismometers provided that they are deployed in optimal configurations. In the form presented here, the optimization method can be applied to all current and future gravitational-wave detectors located at the surface and with minor modifications also to future underground detectors
Adaptive algorithms for low-latency cancellation of seismic Newtonian-noise at the Virgo gravitational-wave detector
No full textA system was recently implemented in the Virgo detector to cancel noise in its data produced by seismic waves directly coupling with the suspended test masses through gravitational interaction. The data from seismometers are being filtered to produce a coherent estimate of the associated gravitational noise also known as Newtonian noise. The first implementation of the system uses a time-invariant (static) Wiener filter, which is the optimal filter for Newtonian-noise cancellation assuming that the noise is stationary. However, time variations in the form of transients and slow changes in correlations between sensors are possible and while time-variant filters are expected to cope with these variations better than a static Wiener filter, the question is what the limitations are of time-variant noise cancellation. In this study, we present a framework to study the performance limitations of time-variant noise cancellation filters and carry out a proof of concept with adaptive filters on seismic data at the Virgo site. We demonstrate that the adaptive filters, at least those with superior architecture, indeed significantly outperform the static Wiener filter with the residual noise remaining above the statistical error bound
Design and implementation of a seismic Newtonian noise cancellation system for the Virgo gravitational-wave detector
No full textTerrestrial gravity perturbations caused by seismic fields produce the so-called Newtonian noise in gravitational-wave detectors, which is predicted to limit their sensitivity in the upcoming observing runs. In the past, this noise was seen as an infrastructural limitation, i.e., something that cannot be overcome without major investments to improve a detector’s infrastructure. However, it is possible to have at least an indirect estimate of this noise by using the data from a large number of seismometers deployed around a detector’s suspended test masses. The noise estimate can be subtracted from the gravitational-wave data, a process called Newtonian noise cancellation (NNC). In this article, we present the design and implementation of the first NNC system at the Virgo detector as part of its AdV+ upgrade. It uses data from 110 vertical geophones deployed inside the Virgo buildings in optimized array configurations. We use a separate tiltmeter channel to test the pipeline in a proof-of-principle. The system has been running with good performance over months
Searches for Continuous Gravitational Waves from 15 Supernova Remnants and Fomalhaut b with Advanced LIGO
No full textInternational audienceWe describe directed searches for continuous gravitational waves (GWs) from 16 well-localized candidate neutron stars, assuming none of the stars has a binary companion. The searches were directed toward 15 supernova remnants and Fomalhaut b, a directly imaged extrasolar planet candidate that has been suggested to be a nearby old neutron star. Each search covered a broad band of frequencies and first and second time derivatives. After coherently integrating spans of data from the first Advanced LIGO observing run of 3.5–53.7 days per search, applying data-based vetoes, and discounting known instrumental artifacts, we found no astrophysical signals. We set upper limits on intrinsic GW strain as strict as 1 × 10−25, fiducial neutron star ellipticity as strict as 2 × 10−9, and fiducial r-mode amplitude as strict as 3 × 10−8
Erratum: Searches for continuous gravitational waves from 15 supernova remnants and fomalhaut b with advanced LIGO (ApJ (2019) 875 (122) DOI: 10.3847/1538-4357/ab113b)
No full textEquation (5) of the published article?(Abbott et al. 2019) is in error; it should read (Formula Presented) The upper limits on ò presented in the published article are unaffected by this error
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