Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userGW150914: First results from the search for binary black hole coalescence with Advanced LIGO
174
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
On September 14, 2015 at 09:50:45 UTC the two detectors of the Laser Interferometer Gravitational-wave Observatory (LIGO) simultaneously observed the binary black hole merger GW150914. We report the results of a matched-filter search using relativistic models of compact-object binaries that recovered GW150914 as the most significant event during the coincident observations between the two LIGO detectors from September 12 to October 20, 2015. GW150914 was observed with a matched filter signal-to-noise ratio of 24 and a false alarm rate estimated to be less than 1 event per 203 000 years, equivalent to a significance greater than 5.1 {sigma}.
rate research
Read More
In Advanced LIGO, detection and astrophysical source parameter estimation of the binary black hole merger GW150914 requires a calibrated estimate of the gravitational-wave strain sensed by the detectors. Producing an estimate from each detectors differential arm length control loop readout signals requires applying time domain filters, which are designed from a frequency domain model of the detectors gravitational-wave response. The gravitational-wave response model is determined by the detectors opto-mechanical response and the properties of its feedback control system. The measurements used to validate the model and characterize its uncertainty are derived primarily from a dedicated photon radiation pressure actuator, with cross-checks provided by optical and radio frequency references. We describe how the gravitational-wave readout signal is calibrated into equivalent gravitational-wave-induced strain and how the statistical uncertainties and systematic errors are assessed. Detector data collected over 38 calendar days, from September 12 to October 20, 2015, contain the event GW150914 and approximately 16 of coincident data used to estimate the event false alarm probability. The calibration uncertainty is less than 10% in magnitude and 10 degrees in phase across the relevant frequency band 20 Hz to 1 kHz.
We compare GW150914 directly to simulations of coalescing binary black holes in full general relativity, accounting for all the spin-weighted quadrupolar modes, and separately accounting for all the quadrupolar and octopolar modes. Consistent with the posterior distributions reported in LVC_PE[1] (at 90% confidence), we find the data are compatible with a wide range of nonprecessing and precessing simulations. Followup simulations performed using previously-estimated binary parameters most resemble the data. Comparisons including only the quadrupolar modes constrain the total redshifted mass Mz in [64 - 82M_odot], mass ratio q = m2/m1 in [0.6,1], and effective aligned spin chi_eff in [-0.3, 0.2], where chi_{eff} = (S1/m1 + S2/m2) cdothat{L} /M. Including both quadrupolar and octopolar modes, we find the mass ratio is even more tightly constrained. Simulations with extreme mass ratios and effective spins are highly inconsistent with the data, at any mass. Several nonprecessing and precessing simulations with similar mass ratio and chi_{eff} are consistent with the data. Though correlated, the components spins (both in magnitude and directions) are not significantly constrained by the data. For nonprecessing binaries, interpolating between simulations, we reconstruct a posterior distribution consistent with previous results. The final black holes redshifted mass is consistent with Mf,z between 64.0 - 73.5M_odot and the final black holes dimensionless spin parameter is consistent with af = 0.62 - 0.73. As our approach invokes no intermediate approximations to general relativity and can strongly reject binaries whose radiation is inconsistent with the data, our analysis provides a valuable complement to LVC_PE[1].
The first observational run of the Advanced LIGO detectors, from September 12, 2015 to January 19, 2016, saw the first detections of gravitational waves from binary black hole mergers. In this paper we present full results from a search for binary black hole merger signals with total masses up to $100 M_odot$ and detailed implications from our observations of these systems. Our search, based on general-relativistic models of gravitational wave signals from binary black hole systems, unambiguously identified two signals, GW150914 and GW151226, with a significance of greater than $5sigma$ over the observing period. It also identified a third possible signal, LVT151012, with substantially lower significance, and with an 87% probability of being of astrophysical origin. We provide detailed estimates of the parameters of the observed systems. Both GW150914 and GW151226 provide an unprecedented opportunity to study the two-body motion of a compact-object binary in the large velocity, highly nonlinear regime. We do not observe any deviations from general relativity, and place improved empirical bounds on several high-order post-Newtonian coefficients. From our observations we infer stellar-mass binary black hole merger rates lying in the range $9-240 mathrm{Gpc}^{-3} mathrm{yr}^{-1}$. These observations are beginning to inform astrophysical predictions of binary black hole formation rates, and indicate that future observing runs of the Advanced detector network will yield many more gravitational wave detections.
We present a novel Machine Learning (ML) based strategy to search for compact binary coalescences (CBCs) in data from ground-based gravitational wave (GW) observatories. This is the first ML-based search that not only recovers all the binary black hole mergers in the first GW transients calalog (GWTC-1), but also makes a clean detection of GW151216, which was not significant enough to be included in the catalogue. Moreover, we achieve this by only adding a new coincident ranking statistic (MLStat) to a standard analysis that was used for GWTC-1. In CBC searches, reducing contamination by terrestrial and instrumental transients, which create a loud noise background by triggering numerous false alarms, is crucial to improving the sensitivity for detecting true events. The sheer volume of data and and large number of expected detections also prompts the use of ML techniques. We perform transfer learning to train InceptionV3, a pre-trained deep neural network, along with curriculum learning to distinguish GW signals from noisy events by analysing their continuous wavelet transform (CWT) maps. MLStat incorporates information from this ML classifier into the standard coincident search likelihood used by the conventional search. This leads to at least an order of magnitude improvement in the inverse false-alarm-rate (IFAR) for the previously low significance events GW151012, GW170729 and GW151216. The confidence in detection of GW151216 is further strengthened by performing its parameter estimation using SEOBNRv4HM_ROM. Considering the impressive ability of the statistic to distinguish signals from glitches, the list of marginal events from MLStat could be quite reliable for astrophysical population studies and further follow-up. This work demonstrates the immense potential and readiness of MLStat for finding new sources in current data and possibility of its adaptation in similar searches.
Presented is the description of a new and general method used to search for $gamma$-ray counterparts to gravitational-wave (GW) triggers. This method is specifically applied to single GW detector triggers. Advanced LIGO data from observing runs O1 and O2 were analyzed, thus each GW trigger comes from either the LIGO-Livingston or the LIGO-Hanford interferometer. For each GW trigger, Fermi Gamma-ray Burst Monitor data is searched and the most significant subthreshold signal counterpart is selected. Then, a methodology is defined in order to establish which of GW-$gamma$-ray pairs are likely to have a common origin. For that purpose an association ranking statistic is calculated from which a false alarm rate is derived. The events with the highest ranking statistics are selected for further analysis consisting of LIGO detector characterization and parameter estimation. The $gamma$-ray signal characteristics are also evaluated. We find no significant candidates from the search.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
