Gravitational wave echoes search with combs
arXiv:2108.01820 · doi:10.1103/PhysRevD.104.124023
Abstract
Gravitational wave echoes may provide a smoking gun signal for new physics in the immediate vicinity of black holes. As a quasiperiodic signal in time, echoes are characterized by the nearly constant time delay, and its precise measurement can help reveal a Planck-scale deviation outside of the would-be horizon. Different search methods have been developed for this quasiperiodic signal, while the searches suffer from large theoretical uncertainties of the echo waveform associated with the near-horizon physics. On the other hand, a coherent combination of a large number of pulses gives rise to a generic narrow resonance structure for the echo amplitude in frequency. The quasiperiodic resonance structure sets a complementary search target for echoes, and the time delay is inversely related to the average resonance spacing. A uniform comb has been proposed to look for the resonance structure in a rather model-independent way. In this paper, we develop a Bayesian algorithm to search for the resonance structure based on combs, where a phase-marginalized likelihood plays an essential role. The algorithm is validated with signal injections in detector noise from Advanced LIGO. With special treatments of the non-Gaussian artifacts, the noise outliers of the log Bayes factor distribution are properly removed. An echo signal not significantly below noise is detectable, and the time delay can be determined to very high precision. We perform the proposed search on real gravitational wave strain data of the first observing run of Advanced LIGO. We find no clear evidence of a comblike structure for GW150914 and GW151012.
arXiv comment25 pages, 10 figures, 2 tables; v2: matches version to be published in PRD, new plots in Figs.5 and 6 added to show the robustness of the algorithm in detecting echo signals of different shapes, bottom right panel in Fig.7 updated after correcting a typo (other results unchanged), appendix expanded for more on analysis of Advanced LIGO data
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