Sliding coherence window technique for hierarchical detection of continuous gravitational waves

TL;DR

This paper introduces a sliding coherence window technique for hierarchical searches of continuous gravitational waves, significantly improving sensitivity and computational efficiency over traditional methods by adaptively combining data segments.

Contribution

The novel sliding coherence window method enhances hierarchical gravitational wave searches by efficiently combining data segments, allowing longer data analysis with improved sensitivity.

Findings

Numerical simulations confirm the analytical sensitivity improvements.

The method requires analyzing 50-100% longer data sets for equivalent sensitivity.

Enhanced computational efficiency compared to standard hierarchical approaches.

Abstract

A novel hierarchical search technique is presented for all-sky surveys for continuous gravitational-wave sources, such as rapidly spinning nonaxisymmetric neutron stars. Analyzing yearlong detector data sets over realistic ranges of parameter space using fully coherent matched-filtering is computationally prohibitive. Thus more efficient, so-called hierarchical techniques are essential. Traditionally, the standard hierarchical approach consists of dividing the data into nonoverlapping segments of which each is coherently analyzed and subsequently the matched-filter outputs from all segments are combined incoherently. The present work proposes to break the data into subsegments shorter than the desired maximum coherence time span (size of the coherence window). Then matched-filter outputs from the different subsegments are efficiently combined by sliding the coherence window in time: Subsegments whose timestamps are closer than coherence window size are combined coherently, otherwise incoherently. Compared to the standard scheme at the same coherence time baseline, data sets longer by about 50-100% would have to be analyzed to achieve the same search sensitivity as with the sliding coherence window approach. Numerical simulations attest to the analytically estimated improvement.