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We demonstrate a new geometric method for fast template placement forsearches for gravitational waves from the inspiral, merger and ringdown ofcompact binaries. The method is based on a binary tree decomposition of thetemplate bank parameter space into non-overlapping hypercubes. We use anumerical approximation of the signal overlap metric at the center of eachhypercube to estimate the number of templates required to cover the hypercubeand determine whether to further split the hypercube. As long as the expectednumber of templates in a given cube is greater than a given threshold, we splitthe cube along its longest edge according to the metric. When the expectednumber of templates in a given hypercube drops below this threshold, thesplitting stops and a template is placed at the center of the hypercube. Usingthis method, we generate aligned-spin template banks covering the mass rangesuitable for a search of Advanced LIGO data. The aligned-spin bank required ~24CPU-hours and produced 2 million templates. In general, we find that othermethods, namely stochastic placement, produces a more strictly bounded loss inmatch between waveforms, with the same minimal match between waveformsrequiring about twice as many templates with our proposed algorithm. Though wenote that the average match is higher, which would lead to a higher detectionefficiency. Our primary motivation is not to strictly minimize the number oftemplates with this algorithm, but rather to produce a bank with usefulgeometric properties in the physical parameter space coordinates. Suchproperties are useful for population modeling and parameter estimation.

A binary tree approach to template placement for searches for gravitational waves from compact binary mergers