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A laser strainmeter with a 1500-m baseline was constructed at an underground site in Kamioka, Gifu Prefecture, Japan, and has been operating since August 2016. The laser interferometer measures the change in distance between two retroreflectors housed in two vacuum chambers with a separation of 1500 m. The retroreflectors are fixed to the ground in the tunnel of the KAGRA gravitational wave telescope. A high-frequency-stabilized laser is used as a light source; it achieves an Allan variance of 3 × 10−13. Since operations began, ground motions with large amplitude and timescale variations have been detected. The recorded tidal waveform almost agrees with the theoretical waveform; however, a slight difference of ~13% in amplitude is found, likely due to a topographic effect. The strain spectrum of the observed data for the 1500-m strainmeter indicates that the lowest background noise attained is less than 10−12in the mHz band. Seismic waves up to 6 × 10−7in amplitude have been observed without saturation or fringe steps. The strainmeter, with its excellent resolution, dynamic range, and bandwidth performance, provides a new method for observing low-frequency ground motion on seismic, geodetic, and intermediate timescales.Graphical AbstractA 1500-m laser strainmeter constructed at an underground site in Kamioka (left), calculated and observed earth tides (top right), and seismic waveform of an earthquake (Fukushima, Mw 6.9) occurred at 20:59:49 (UTC) on Nov. 21, 2016 (bottom right).

The observation of gravitational waves with a global network of interferometric detectors such as advanced LIGO, advanced Virgo, and KAGR A will make it possible to probe into the nature of space-time structure. Besides Einstein's general theory of relativity, there are several theories of gravitation that passed experimental tests so far. The gravitational-wave observation provides a new experimental test of alternative theories of gravity because a gravitational wave may have at most six independent modes of polarization whose properties and number of modes are dependent on theories of gravity. This paper develops a method to reconstruct an arbitrary number of modes of polarization in time-series data of an advanced detector network. The method does not rely on any specific model, which gives a model-independent test of alternative theories of gravity. [ABSTRACT FROM AUTHOR]

For gravitational wave searches using an interferometric detector, non-stationary noise in data causes degradation of data condition and detection efficiency. We propose a wavelet-based online data analysis method to monitor and estimate non-stationary signals automatically without prior information about their waveforms. In this paper, we demonstrate our method by applying it to the data of TAMA300.

DECi-hertz Interferometer Gravitational wave Observatory (DECIGO) is the future Japanese space gravitational wave antenna. It aims at detecting various kinds of gravitational waves between 1 mHz and 100 Hz frequently enough to open a new window of observation for gravitational wave astronomy. The pre-conceptual design of DECIGO consists of three drag-free satellites, 1000 km apart from each other, whose relative displacements are measured by a Fabry-Perot Michelson interferometer. We plan to launch DECIGO in 2024 after a long and intense development phase, including two pathfinder missions for verification of required technologies.

We present the results of observations with the TAMA300 gravitational-wave detector, targeting burst signals from stellar-core collapse events. We used an excess-power filter to extract gravitational-wave candidates, and developed two methods to reduce fake events caused by non-stationary noises of the detector. These analysis methods were applied to real data from the TAMA300 interferometric gravitational wave detector. We compared the data-processed results with those of a Monte Carlo simulation with an assumed galactic-event distribution model and with burst waveforms expected from numerical simulations of stellar-core collapses, in order to interpret the event candidates from an astronomical viewpoint. We set an upper limit of 5.0 × 103events s?1on the burst gravitational-wave event rate in our galaxy with a confidence level of 90%.

This paper proposes a data analysis method to reduce the binary confusion noise. We analyse characteristics of the binary confusion noise in a wavelet space and extract a typical level of this noise. Using this level, we reduce the binary confusion noise and drive an approximate form of a burst signal subject to the confusion noise. We show that our method can reduce the influence of confusion noise and obtain an approximate waveform of the desired signal with high accuracy.

This paper proposes a wavelet-based method to detect Type II supernovae signals, which are burst-like signals that are poorly-predicted. The proposed method can approximate the burst signals non-parametrically, and the estimator is nearly optimal even, if we do not use the prior information about the waveforms. Therefore it is believed that this method is suitable for detecting such burst signals. In order to study the performance of this method, we demonstrate the detection of supernovae signals subject to Gaussian white noise using the catalog of waveforms provided recently by Dimmelmeier et al. as target supernovae signals, and we compare its performance with that of the Wiener estimator. We obtain two main results: First, our method is superior to that of the Wiener filter for all the supernovae signals in the catalog. Second, the performance of our method does not depend on the duration of the bursts. By contrast, the performance of the Wiener estimator becomes worse as the duration of the burst signals decreases.

It is expected that proposed space-based interferometers, such as LISA and DECIGO, will detect so many gravitational wave signals from compact binaries that it will not be possible to resolve these gravitational wave signals in the low frequency band. Such unresolved signals result in confusion noise in detecting other gravitational wave signals, such as signals from merger, and ringdown of super-massive black holes, and so on. In this paper, we analyze characteristics of this confusion noise in wavelet space and extract a typical level of this noise. then, we propose a data analysis method to reduce the confusion noise using a typical noise level and derive an approximate form of a burst signal subject to such confusion noise. By use of a computer simulation, we show that our method can reduce the influence of confusion noise and obtain an approximate waveform of the desired signal with high accuracy.