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Matched-filtering gravitational wave search pipelines identify gravitationalwave signals by computing correlations, i.e., signal-to-noise ratios, betweengravitational wave detector data and gravitational wave template waveforms.Intrinsic parameters, the component masses and spins, of the gravitational wavewaveforms are often stored in "template banks", and the construction of adensely populated template bank is essential for some gravitational wave searchpipelines. This paper presents a template bank that is currently being used bythe GstLAL-based compact binary search pipeline in the fourth observing run ofthe LIGO, Virgo, and KAGRA collaboration, and was generated with a new binarytree approach of placing templates, {\fontfamily{qcr}\selectfont manifold}. Thetemplate bank contains $1.8 \times 10^6$ sets of template parameters coveringplausible neutron star and black hole systems up to a total mass of $400$$M_\odot$ with component masses between $1$-$200$ $M_\odot$ and mass ratiosbetween $1$ and $20$ under the assumption that each component object's angularmomentum is aligned with the orbital angular momentum. We validate the templatebank generated with our new method, {\fontfamily{qcr}\selectfont manifold}, bycomparing it with a template bank generated with the previously used stochastictemplate placement method. We show that both template banks have similareffectualness. The {\fontfamily{qcr}\selectfont GstLAL} search pipelineperforms singular value decomposition (SVD) on the template banks to reduce thenumber of filters used. We describe a new grouping of waveforms that improvesthe computational efficiency of SVD by nearly $5$ times as compared topreviously reported SVD sorting schemes.

Template bank for compact binary mergers in the fourth observing run of Advanced LIGO, Advanced Virgo, and KAGRA