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Register a new userObtaining Gravitational Waves from Inspiral Binary Systems using LIGO data
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The discovery of the astrophysical events GW150926 and GW151226 has experimentally confirmed the existence of gravitational waves (GW) and has demonstrated the existence of binary stellar-mass black hole systems. This finding marks the beginning of a new era that will reveal unexpected features of our universe. This work presents a basic insight to the fundamental theory of GW emitted by inspiral binary systems and describes the scientific and technological efforts developed to measure these waves using the interferometer-based detector called LIGO. Subsequently, the work presents a comprehensive data analysis methodology based on the matched filter algorithm, which aims to recovery GW signals emitted by inspiral binary systems of astrophysical sources. This algorithm was evaluated with freely available LIGO data containing injected GW waveforms. Results of the experiments performed to assess detection accuracy showed the recovery of 85% of the injected GW.
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One of the key challenges of real-time detection and parameter estimation of gravitational waves from compact binary mergers is the computational cost of conventional matched-filtering and Bayesian inference approaches. In particular, the application of these methods to the full signal parameter space available to the gravitational-wave detectors, and/or real-time parameter estimation is computationally prohibitive. On the other hand, rapid detection and inference are critical for prompt follow-up of the electromagnetic and astro-particle counterparts accompanying important transients, such as binary neutron-star and black-hole neutron-star mergers. Training deep neural networks to identify specific signals and learn a computationally efficient representation of the mapping between gravitational-wave signals and their parameters allows both detection and inference to be done quickly and reliably, with high sensitivity and accuracy. In this work we apply a deep-learning approach to rapidly identify and characterize transient gravitational-wave signals from binary neutron-star mergers in real LIGO data. We show for the first time that artificial neural networks can promptly detect and characterize binary neutron star gravitational-wave signals in real LIGO data, and distinguish them from noise and signals from coalescing black-hole binaries. We illustrate this key result by demonstrating that our deep-learning framework classifies correctly all gravitational-wave events from the Gravitational-Wave Transient Catalog, GWTC-1 [Phys. Rev. X 9 (2019), 031040]. These results emphasize the importance of using realistic gravitational-wave detector data in machine learning approaches, and represent a step towards achieving real-time detection and inference of gravitational waves.
We present results of an all-sky search for continuous gravitational waves (CWs), which can be produced by fast-spinning neutron stars with an asymmetry around their rotation axis, using data from the second observing run of the Advanced LIGO detectors. We employ three different semi-coherent methods ($textit{FrequencyHough}$, $textit{SkyHough}$, and $textit{Time-Domain $mathcal{F}$-statistic}$) to search in a gravitational-wave frequency band from 20 to 1922 Hz and a first frequency derivative from $-1times10^{-8}$ to $2times10^{-9}$ Hz/s. None of these searches has found clear evidence for a CW signal, so we present upper limits on the gravitational-wave strain amplitude $h_0$ (the lowest upper limit on $h_0$ is $1.7times10^{-25}$ in the 123-124 Hz region) and discuss the astrophysical implications of this result. This is the most sensitive search ever performed over the broad range of parameters explored in this study.
We present the results of a search in LIGO O2 public data for continuous gravitational waves from the neutron star in the low-mass X-ray binary Scorpius X-1. We search for signals with $approx$ constant frequency in the range 40-180 Hz. Thanks to the efficiency of our search pipeline we can use a long coherence time and achieve unprecedented sensitivity, significantly improving on existing results. This is the first search that has been able to probe gravitational wave amplitudes that could balance the accretion torque at the neutron star radius. Our search excludes emission at this level between 67.5 Hz and 131.5 Hz, for an inclination angle $44^circ pm 6^circ$ derived from radio observations (Fomalont et al. 2001), and assuming that the spin axis is perpendicular to the orbital plane. If the torque arm is $approx $ 26 km -- a conservative estimate of the alfven radius -- our results are more constraining than the indirect limit across the band. This allows us to exclude certain mass-radius combinations and to place upper limits on the strength of the stars magnetic field. We also correct a mistake that appears in the literature in the equation that gives the gravitational wave amplitude at the torque balance (Abbott et al. 2017b, 2019a) and we re-interpret the associated latest LIGO/Virgo results in light of this.
We demonstrate an all-sky search for persistent, narrowband gravitational waves using mock data. The search employs radiometry to sidereal-folded data in order to uncover persistent sources of gravitational waves with minimal assumptions about the signal model. The method complements continuous-wave searches, which are finely tuned to search for gravitational waves from rotating neutron stars while providing a means of detecting more exotic sources that might be missed by dedicated continuous-wave techniques. We apply the algorithm to simulated Gaussian noise at the level of LIGO design sensitivity. We project the strain amplitude sensitivity for the algorithm for a LIGO network in the first observing run to be $h_0 approx 1.2 times 10^{-24}$ ($1%$ false alarm probability, $10%$ false dismissal probability). We include treatment of instrumental lines and detector artifacts using time-shifted LIGO data from the first observing run.
Rapid detection of compact binary coalescence (CBC) with a network of advanced gravitational-wave detectors will offer a unique opportunity for multi-messenger astronomy. Prompt detection alerts for the astronomical community might make it possible to observe the onset of electromagnetic emission from (CBC). We demonstrate a computationally practical filtering strategy that could produce early-warning triggers before gravitational radiation from the final merger has arrived at the detectors.
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