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Register a new userOptimization of model independent gravitational wave search using machine learning
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The Coherent WaveBurst (cWB) search algorithm identifies generic gravitational wave (GW) signals in the LIGO-Virgo strain data. We propose a machine learning (ML) method to optimize the pipeline sensitivity to the special class of GW signals known as binary black hole (BBH) mergers. Here, we test the ML-enhanced cWB search on strain data from the first and second observing runs of Advanced LIGO and successfully recover all BBH events previously reported by cWB, with higher significance. For simulated events found with a false alarm rate less than $1,mathrm{yr}^{-1}$, we demonstrate the improvement in the detection efficiency of 26% for stellar-mass BBH mergers and 16% for intermediate mass black hole binary mergers. To demonstrate the robustness of the ML-enhanced search for the detection of generic BBH signals, we show that it has the increased sensitivity to the spin precessing or eccentric BBH events, even when trained on simulated quasi-circular BBH events with aligned spins.
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The direct detection of gravitational waves will provide valuable astrophysical information about many celestial objects. The SCHENBERG has already undergone its first test run. It is expected to have its first scientific run soon. In this work a new data analysis approach is presented, called method of independent bars, which can be used with SCHENBERGs data . We test this method through the simulation of the detection of gravitational waves. With this method we find the sources direction without the need to have all six transducers operational. Also we show that the method is a generalization of another one, already described in the literature, known as the mode channels method.
Signal extraction out of background noise is a common challenge in high precision physics experiments, where the measurement output is often a continuous data stream. To improve the signal to noise ratio of the detection, witness sensors are often used to independently measure background noises and subtract them from the main signal. If the noise coupling is linear and stationary, optimal techniques already exist and are routinely implemented in many experiments. However, when the noise coupling is non-stationary, linear techniques often fail or are sub-optimal. Inspired by the properties of the background noise in gravitational wave detectors, this work develops a novel algorithm to efficiently characterize and remove non-stationary noise couplings, provided there exist witnesses of the noise source and of the modulation. In this work, the algorithm is described in its most general formulation, and its efficiency is demonstrated with examples from the data of the Advanced LIGO gravitational wave observatory, where we could obtain an improvement of the detector gravitational wave reach without introducing any bias on the source parameter estimation.
The observation of gravitational waves with a global network of interferometric detectors such as advanced LIGO, advanced Virgo, and KAGRA will make it possible to probe into the nature of space-time structure. Besides Einsteins 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, of which properties and number of modes are dependent on theories of gravity. This paper proposes a method to reconstruct the independent modes of polarization in time-series data of an advanced detector network. Since the method does not rely on any specific model, it gives model-independent test of alternative theories of gravity.
Gravitational wave echoes may provide a smoking gun signal for new physics in the immediate vicinity of black holes. As a quasi-periodic signal in time, echoes are characterized by the nearly constant time delay, and its precise measurement can help reveal a Planck scale deviation outside of the would-be horizon. Different search methods have been developed for this quasi-periodic signal, while the searches suffer from large theoretical uncertainties of the echo waveform associated with the near-horizon physics. On the other hand, a coherent combine of a large number of pulses gives rise to a generic narrow resonance structure for the echo amplitude in frequency. The quasi-periodic resonance structure sets a complementary search target for echoes, and the time delay is inversely related to the average resonance spacing. A uniform comb has been proposed to look for the resonance structure in a rather model independent way. In this paper, we develop a Bayesian algorithm to search for the resonance structure based on combs, where a phase-marginalized likelihood plays an essential role. The algorithm is validated with signal injections in detector noise from Advanced LIGO. With special treatments of the non-Gaussian artifacts, the noise outliers of the log Bayes factor distribution are properly removed. An echo signal not significantly below noise is detectable, and the time delay can be determined to very high precision. We perform the proposed search on real gravitational wave strain data of the first observing run of Advanced LIGO. We find no clear evidence of a comb-like structure for GW150914 and GW151012.
This work describes a template-free method to search gravitational waves (GW) using data from the LIGO observatories simultaneously. The basic idea of this method is that a GW signal is present in a short-duration data segment if the maximum correlation-coefficient between the strain signals is higher than a significant threshold and its time difference is lower than the 10 ms of inter-observatory light propagation time. Hence, this method can be used to carry out blind searches of any types of GW irrespective of the waveform and of the source type and sky location. An independent search of injected and real GW signals from compact binary coalescences (CBC) contained in the first observation run (O1) of advanced LIGO was carried out to asses its performance. On the basis of the results, the proposed method was able to detect GW produced by binary systems without making any assumption about them.
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