Random projections in gravitational wave searches of compact binaries
Sumeet Kulkarni, Khun Sang Phukon, Amit Reza, Sukanta Bose, Anirban, Dasgupta, Dilip Krishnaswamy, Anand S. Sengupta

TL;DR
This paper introduces random projection techniques to enhance computational efficiency in gravitational wave searches for compact binaries, addressing increased data complexity due to detector upgrades.
Contribution
It presents novel RP-based methods for efficient template matrix factorization and correlation calculations, significantly reducing computational costs in gravitational wave data analysis.
Findings
Reduced computational cost by an order of magnitude for certain binary searches
Improved data analysis efficiency with RP-based matrix factorization and correlation methods
Facilitates more complex waveform searches by freeing computational resources
Abstract
Random projection (RP) is a powerful dimension reduction technique widely used in the analysis of high dimensional data. We demonstrate how this technique can be used to improve the computational efficiency of gravitational wave searches from compact binaries of neutron stars or black holes. Improvements in low-frequency response and bandwidth due to detector hardware upgrades pose a data analysis challenge in the advanced LIGO era as they result in increased redundancy in template databases and longer templates due to the higher number of signal cycles in-band. The RP-based methods presented here address both these issues within the same broad framework. We first use RP for an efficient, singular value decomposition inspired template matrix factorization and develop a geometric intuition for why this approach works. We then use RP to calculate approximate time-domain match correlations…
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