• Open Access

Deep-learning continuous gravitational waves: Multiple detectors and realistic noise

Christoph Dreissigacker and Reinhard Prix
Phys. Rev. D 102, 022005 – Published 6 July 2020

Abstract

The sensitivity of wide-parameter-space searches for continuous gravitational waves is limited by computational cost. Recently it was shown that deep neural networks (DNNs) can perform all-sky searches directly on (single-detector) strain data [C. Dreissigacker , Phys. Rev. D 100, 044009 (2019)], potentially providing a low-computing-cost search method that could lead to a better overall sensitivity. Here we expand on this study in two respects: (i) using (simulated) strain data from two detectors simultaneously, and (ii) training for directed (i.e., single sky-position) searches in addition to all-sky searches. For a data time span of T=105s, the all-sky two-detector DNN is about 7% less sensitive (in amplitude h0) at low frequency (f=20Hz), and about 51% less sensitive at high frequency (f=1000Hz) compared to fully-coherent matched-filtering (using weave). In the directed case the sensitivity gap compared to matched-filtering ranges from about 7%–14% at f=20Hz to about 37%–49% at f=1500Hz. Furthermore we assess the DNN’s ability to generalize in signal frequency, spin down and sky-position, and we test its robustness to realistic data conditions, namely gaps in the data and using real LIGO detector noise. We find that the DNN performance is not adversely affected by gaps in the test data or by using a relatively undisturbed band of LIGO detector data instead of Gaussian noise. However, when using a more disturbed LIGO band for the tests, the DNN’s detection performance is substantially degraded due to the increase in false alarms, as expected.

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  • Received 11 May 2020
  • Accepted 17 June 2020

DOI:https://doi.org/10.1103/PhysRevD.102.022005

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. Open access publication funded by the Max Planck Society.

Published by the American Physical Society

Physics Subject Headings (PhySH)

Gravitation, Cosmology & Astrophysics

Authors & Affiliations

Christoph Dreissigacker* and Reinhard Prix

  • Max Planck Institute for Gravitational Physics (Albert-Einstein-Institute), D-30167 Hannover, Germany and Leibniz Universität Hannover, D-30167 Hannover, Germany

  • *Corresponding author. christoph.dreissigacker@aei.mpg.de

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Issue

Vol. 102, Iss. 2 — 15 July 2020

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