Innovations in seismic sensors driven by the search for gravitational waves

Beker, M. G.; Campman, Xander; Oven, Jules van; Walk, Wim; Levell, Jack; Tang, Zijian; Danilouchkine, Mikhail G.; Smit, Dirk; Brand, J. van den; Koley, S.; Bader, M. K. M.

doi:10.1190/tle35070590.1

Cited by 8 publications

(7 citation statements)

References 4 publications

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“…It can be seen that the absolute residual spectra are relatively flat compared to the original spectra. The absolute residual of target sensor #30 is about a factor 10 above the specified instrument self-noise [15]. Flatness suggests that the residual is dominated by instrument self-noise which would mean that at least some of the seismometers in the array do not perform as well as expected.…”

Section: Wiener Filteringmentioning

confidence: 94%

“…Figure 1 shows the positions of indoor sensors: 14 are located near the walls of the WE tower, 9 near the tower platform, 13 on the tower platform and 2 in the basement of the tower platform. The sensors, manufactured by InnoSeis [15], are based on 5 Hz geophones and monitor the vertical ground velocity. The sensor package also contains a pre-amplifier and an analog-to-digital converter to avoid issues with excess electromagnetic (EM) noise coupling when transmitting analog signals through several meter long cables in an EM noisy environment.…”

Section: West End Building Seismometer Setupmentioning

confidence: 99%

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Seismic array measurements at Virgo’s west end building for the configuration of a Newtonian-noise cancellation system

Tringali

Bulik

Harms

et al. 2019

Class. Quantum Grav.

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Terrestrial gravity fluctuations produce so-called Newtonian noise (NN) which is expected to limit the low frequency sensitivity of existing gravitational-waves (GW) detectors LIGO and Virgo, when they will reach their full potential, and of next-generation detectors like the Einstein Telescope. In this paper, we present a detailed characterization of the seismic field at Virgo's West End Building as part of the development of a Newtonian noise cancellation system. The cancellation system will use optimally filtered data from a seismometer array to produce an estimate of the Newtonian-noise generated by the seismic field, and to subtract this estimate from the gravitational-wave channel of the detector. By using an array of 38 seismic sensors, we show that, despite the influence of the complexity of Virgo's infrastructure on the correlation across the array, Wiener filtering can still be very efficient in reconstructing the seismic field around the test-mass location. Taking into account the division of the building's foundations into separate concrete slabs, and the different properties of the seismic field across them, we conclude that the arrays to be used for the Newtoniannoise cancellation at Virgo will require a relatively large number of seismometers per test mass, i.e. significantly more than 10. Moreover, observed variations of the absolute noise residuals over time, related to the daily evolution of anthropogenic noise, suggest that the Wiener filter will need to be updated regularly, probably more often than every hour, to achieve stationarity of the background level after subtraction.

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Section: Wiener Filteringmentioning

confidence: 94%

Section: West End Building Seismometer Setupmentioning

confidence: 99%

Seismic array measurements at Virgo’s west end building for the configuration of a Newtonian-noise cancellation system

Tringali

Bulik

Harms

et al. 2019

Class. Quantum Grav.

Self Cite

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“…with frequency f in Hz [24]. For the underground seismometers the self noise is an order of magnitude less.…”

Section: Synthetic Data Generationmentioning

confidence: 99%

A study of deep neural networks for Newtonian noise subtraction at Terziet in Limburg—the Euregio Meuse-Rhine candidate site for Einstein Telescope

van Beveren,

Bader,

van den Brand

et al. 2023

Class. Quantum Grav.

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The Euregio Meuse-Rhine border region of Belgium, Germany and the Netherlands has been identified as a candidate site for hosting Einstein Telescope. Newtonian coupling of ground vibrations to the core optics of the detectors may limit the sensitivity of Einstein Telescope at frequencies below about 10 Hz. The contribution of Newtonian noise is site specific and depends on the ambient seismic field which in turn depends on the site’s geology and the distribution of surface and underground seismic-noise sources. We have investigated the application of machine learning in combination with the deployment of seismic sensor networks to predict seismic displacement noise at specific locations on the surface and underground. Moreover we have modeled a deep neural network that allows to subtract Newtonian noise from the strain data measured by Einstein Telescope. The seismic-field model is based on a complete solution of the elastodynamic wave equations for a horizontally-layered soil structure. The geology features soft-soil layers on hard-rock and was shown to be effective in attenuating Newtonian noise from surface waves below the required sensitivity. In addition our model includes a random background of body waves with all possible angles of incidence. We show that a deep neural network is effective in predicting Newtonian noise, whereas an Wiener filter approach is effective when surface boundary conditions dominate the Newtonian noise contributions.

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“…Seismometer signals were converted from volts to m/s, by using the appropriate conversion coefficient 5/(2 23 × 77.3). For more details see [31].…”

Section: Measuring Systemmentioning

confidence: 99%

Application of Spatio-Temporal Spectral Analysis for Detection of Seismic Waves in Gravitational-Wave Interferometer

et al. 2021

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Mixed spatio–temporal spectral analysis was applied for the detection of seismic waves passing through the west–end building of the Virgo interferometer. The method enables detection of a passing wave, including its frequency, length, direction, and amplitude. A thorough analysis aimed at improving sensitivity of the Virgo detector was made for the data gathered by 38 seismic sensors, in the two–week measurement period, from 24 January to 6 February 2018, and for frequency range 5–20 Hz. Two dominant seismic–wave frequencies were found: 5.5 Hz and 17.1 Hz. The presented method can be applied for a better understanding of the interferometer seismic environment, and by identifying noise sources, help the noise–hunting and mitigation work that eventually leads to interferometer noise suppression.

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Innovations in seismic sensors driven by the search for gravitational waves

Cited by 8 publications

References 4 publications

Seismic array measurements at Virgo’s west end building for the configuration of a Newtonian-noise cancellation system

Seismic array measurements at Virgo’s west end building for the configuration of a Newtonian-noise cancellation system

A study of deep neural networks for Newtonian noise subtraction at Terziet in Limburg—the Euregio Meuse-Rhine candidate site for Einstein Telescope

Application of Spatio-Temporal Spectral Analysis for Detection of Seismic Waves in Gravitational-Wave Interferometer

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