In hierarchical searches for continuous gravitational waves, clustering of candidates is an important post-processing step because it reduces the number of noise candidates that are followed up at successive stages [J. Aasi et al., Phys. Rev. Lett. 88, 102002 (2013), 10.1103/PhysRevD.88.102002; B. Behnke, M. A. Papa, and R. Prix, Phys. Rev. D 91, 064007 (2015), 10.1103/PhysRevD.91.064007; M. A. Papa et al., Phys. Rev. D 94, 122006 (2016), 10.1103/PhysRevD.94.122006]. Previous clustering procedures bundled together nearby candidates ascribing them to the same root cause (be it a signal or a disturbance), based on a predefined cluster volume. In this paper, we present a procedure that adapts the cluster volume to the data itself and checks for consistency of such volume with what is expected from a signal. This significantly improves the noise rejection capabilities at fixed detection threshold, and at fixed computing resources for the follow-up stages, this results in an overall more sensitive search. This new procedure was employed in the first Einstein@Home search on data from the first science run of the advanced LIGO detectors (O1) [LIGO Scientific Collaboration and Virgo Collaboration, arXiv:1707.02669 [Phys. Rev. D (to be published)]].
Physical Review D
- Pub Date:
- October 2017
- General Relativity and Quantum Cosmology;
- Astrophysics - Instrumentation and Methods for Astrophysics;
- Mathematics - General Topology
- 11 pages, 9 figures, 2 tables