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The LIGO and Virgo scientific collaborations have cataloged ten confident detections from binary black holes and one from binary neutron stars in their first two observing runs, which has already brought up an immense desire among the scientists to study the universe and to extend the knowledge of astrophysics from these compact objects. One of the fundamental noise sources limiting the achievable detector bandwidth is given by Newtonian noise arising from terrestrial gravity fluctuations. It is important to model Newtonian noise spectra very accurately as it cannot be monitored directly using current technology. In this article, we show the reduction in the Newtonian noise curve obtained by more accurately modelling the current configuration of the Virgo observatory. In Virgo, there are clean rooms or recess like structures underneath each test mirror forming the main two Fabry-Perot arm cavities of the detector. We compute the displacements originating from an isotropic Rayleigh field including the recess structure. We find an overall strain noise reduction factor of 2 in the frequency band from 12 to about 15 Hz relative to previous models. The reduction factor depends on frequency and also varies between individual test masses.
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Fluctuations of gravitational forces cause so-called Newtonian noise (NN) in gravitational-wave (GW) detectors which is expected to limit their low-frequency sensitivity in upcoming observing runs. Seismic NN is produced by seismic waves passing near a detectors 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 Virgos 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 Hz - 20 Hz is very low ($lesssim$100,m/s), which has important consequences for Virgos 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.
High-contrast imaging enabled by a starshade in formation flight with a space telescope can provide a near-term pathway to search for and characterize temperate and small planets of nearby stars. NASAs Starshade Technology Development Activity to TRL5 (S5) is rapidly maturing the required technologies to the point at which starshades could be integrated into potential future missions. Here we reappraise the noise budget of starshade-enabled exoplanet imaging to incorporate the experimentally demonstrated optical performance of the starshade and its optical edge. Our analyses of stray light sources - including the leakage through micrometeoroid damage and the reflection of bright celestial bodies - indicate that sunlight scattered by the optical edge (i.e., the solar glint) is by far the dominant stray light. With telescope and observation parameters that approximately correspond to Starshade Rendezvous with Roman and HabEx, we find that the dominating noise source would be exozodiacal light for characterizing a temperate and Earth-sized planet around Sun-like and earlier stars and the solar glint for later-type stars. Further reducing the brightness of solar glint by a factor of 10 with a coating would prevent it from becoming the dominant noise for both Roman and HabEx. With an instrument contrast of 1E-10, the residual starlight is not a dominant noise; and increasing the contrast level by a factor 10 would not lead to any appreciable change in the expected science performance. If unbiased calibration of the background to the photon-noise limit can be achieved, Starshade Rendezvous with Roman could provide nearly photon-limited spectroscopy of temperate and Earth-sized planets of F, G, and K stars <4 parsecs away, and HabEx could extend this capability to many more stars <8 parsecs. (Abridged)
The 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.
Newtonian gravitational noise from seismic fields will become a limiting noise source at low frequency for second-generation, gravitational-wave detectors. It is planned to use seismic sensors surrounding the detectors test masses to coherently subtract Newtonian noise using Wiener filters derived from the correlations between the sensors and detector data. In this work, we use data from a seismometer array deployed at the corner station of the LIGO Hanford detector combined with a tiltmeter for a detailed characterization of the seismic field and to predict achievable Newtonian-noise subtraction levels. As was shown previously, cancellation of the tiltmeter signal using seismometer data serves as the best available proxy of Newtonian-noise cancellation. According to our results, a relatively small number of seismometers is likely sufficient to perform the noise cancellation due to an almost ideal two-point spatial correlation of seismic surface displacement at the corner station, or alternatively, a tiltmeter deployed under each of the two test masses of the corner station at Hanford will be able to efficiently cancel Newtonian noise. Furthermore, we show that the ground tilt to differential arm-length coupling observed during LIGOs second science run is consistent with gravitational coupling.
A methodology of adaptive time series analysis, based on Empirical Mode Decomposition (EMD), and on its time varying version tvf-EMD has been applied to strain data from the gravitational wave interferometer (IFO) Virgo in order to characterise scattered light noise affecting the sensitivity of the IFO in the detection frequency band. Data taken both during hardware injections, when a part of the IFO is put in oscillation for detector characterisation purposes, and during periods of science mode, when the IFO is fully locked and data are used for the detection of gravitational waves, were analysed. The adaptive nature of the EMD and tvf-EMD algorithms allows them to deal with nonlinear non-stationary data and hence they are particularly suited to characterise scattered light noise which is an intrinsically nonlinear and non-stationary noise. Obtained results show that tvf-EMD algorithm allows to obtain more precise results compared to the EMD algorithm, yielding higher cross-correlation values with the auxiliary channels that are the culprits of scattered light noise.
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