4,804 research outputs found

    Deep Learning for Real-time Gravitational Wave Detection and Parameter Estimation: Results with Advanced LIGO Data

    Full text link
    The recent Nobel-prize-winning detections of gravitational waves from merging black holes and the subsequent detection of the collision of two neutron stars in coincidence with electromagnetic observations have inaugurated a new era of multimessenger astrophysics. To enhance the scope of this emergent field of science, we pioneered the use of deep learning with convolutional neural networks, that take time-series inputs, for rapid detection and characterization of gravitational wave signals. This approach, Deep Filtering, was initially demonstrated using simulated LIGO noise. In this article, we present the extension of Deep Filtering using real data from LIGO, for both detection and parameter estimation of gravitational waves from binary black hole mergers using continuous data streams from multiple LIGO detectors. We demonstrate for the first time that machine learning can detect and estimate the true parameters of real events observed by LIGO. Our results show that Deep Filtering achieves similar sensitivities and lower errors compared to matched-filtering while being far more computationally efficient and more resilient to glitches, allowing real-time processing of weak time-series signals in non-stationary non-Gaussian noise with minimal resources, and also enables the detection of new classes of gravitational wave sources that may go unnoticed with existing detection algorithms. This unified framework for data analysis is ideally suited to enable coincident detection campaigns of gravitational waves and their multimessenger counterparts in real-time.Comment: 6 pages, 7 figures; First application of deep learning to real LIGO events; Includes direct comparison against matched-filterin

    Importance of including small body spin effects in the modelling of intermediate mass-ratio inspirals. II Accurate parameter extraction of strong sources using higher-order spin effects

    Full text link
    We improve the numerical kludge waveform model introduced in [1] in two ways. We extend the equations of motion for spinning black hole binaries derived by Saijo et al. [2] using spin-orbit and spin-spin couplings taken from perturbative and post-Newtonian (PN) calculations at the highest order available. We also include first-order conservative self-force corrections for spin-orbit and spin-spin couplings, which are derived by comparison to PN results. We generate the inspiral evolution using fluxes that include the most recent calculations of small body spin corrections, spin-spin and spin-orbit couplings and higher-order fits to solutions of the Teukolsky equation. Using a simplified version of this model in [1], we found that small body spin effects could be measured through gravitational wave observations from intermediate-mass ratio inspirals (IMRIs) with mass ratio eta ~ 0.001, when both binary components are rapidly rotating. In this paper we study in detail how the spin of the small/big body affects parameter measurement using a variety of mass and spin combinations for typical IMRIs sources. We find that for IMRI events of a moderately rotating intermediate mass black hole (IMBH) of ten thousand solar masses, and a rapidly rotating central supermassive black hole (SMBH) of one million solar masses, gravitational wave observations made with LISA at a fixed signal-to-noise ratio (SNR) of 1000 will be able to determine the inspiralling IMBH mass, the central SMBH mass, the SMBH spin magnitude, and the IMBH spin magnitude to within fractional errors of ~0.001, 0.001, 0.0001, and 9%, respectively. LISA can also determine the location of the source in the sky and the SMBH spin orientation to within ~0.0001 steradians. We show that by including conservative corrections up to 2.5PN order, systematic errors no longer dominate over statistical errors for IMRIs with typical SNR ~1000.Comment: 21 pages, 7 figures. v2: three references added, edits in Sections II-V, including additional results in Section V to address comments by the referee. v3: mirrors version accepted to PR

    Importance of including small body spin effects in the modelling of extreme and intermediate mass-ratio inspirals

    Full text link
    We explore the ability of future low-frequency gravitational wave detectors to measure the spin of stellar mass and intermediate mass black holes that inspiral onto super-massive Kerr black holes (SMBHs). We develop a kludge waveform model based on the equations of motion derived by Saijo et al. [Phys Rev D 58, 064005, 1998] for spinning BH binaries, augmented with spin-orbit and spin-spin couplings taken from perturbative and post-Newtonian (PN) calculations, and the associated conservative self-force corrections, derived by comparison to PN results. We model the inspiral phase using accurate fluxes which include perturbative corrections for the spin of the inspiralling body, spin-spin couplings and higher-order fits to solutions of the Teukolsky equation. We present results of Monte Carlo simulations of parameter estimation errors and of the model errors that arise when we omit conservative corrections from the waveform template. For a source 5000+10^6 solar mass observed with an SNR of 1000, LISA will be able to determine the two masses to within a fractional error of ~0.001, measure the SMBH spin magnitude, q, and the spin magnitude of the inspiralling BH to 0.0001, 10%, respectively, and determine the location of the source in the sky and the SMBH spin orientation to within 0.0001 steradians. For a 10+10^6 solar mass system observed with SNR of 30, LISA will not be able to determine the spin magnitude of the inspiralling BH, although the measurement of the other waveform parameters is not significantly degraded by the presence of spin. The model errors which arise from ignoring conservative corrections become significant for mass-ratios above 0.0001, but including these corrections up to 2PN order may be sufficient to reduce these systematic errors to an acceptable level.Comment: 24 pages, 11 figures. v2 mirrors published version in PRD. Edits in Sections V and VI in response to comments from refere
    • …
    corecore