A stochastic template placement algorithm for gravitational wave data analysis

TL;DR

This paper introduces a stochastic algorithm for creating template banks in gravitational wave data analysis, demonstrating its effectiveness and comparing it to traditional deterministic methods.

Contribution

It proposes a novel stochastic placement algorithm for template banks and analyzes its properties and performance in gravitational wave searches.

Findings

Stochastic template banks are effective for gravitational wave detection.

The properties of stochastic banks are comparable to deterministic ones.

The method offers a flexible alternative for template placement.

Abstract

This paper presents an algorithm for constructing matched-filter template banks in an arbitrary parameter space. The method places templates at random, then removes those which are "too close" together. The properties and optimality of stochastic template banks generated in this manner are investigated for some simple models. The effectiveness of these template banks for gravitational wave searches for binary inspiral waveforms is also examined. The properties of a stochastic template bank are then compared to the deterministically placed template banks that are currently used in gravitational wave data analysis.