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The speedup of heavy numerical tasks by quantum computing is now activelyinvestigated in various fields including data analysis in physics andastronomy. In this paper, we propose a new quantum algorithm for matchedfiltering in gravitational wave (GW) data analysis based on the previous workby Gao et al., Phys. Rev. Research 4, 023006 (2022) [arXiv:2109.01535]. Ourapproach uses the quantum algorithm for Monte Carlo integration for thesignal-to-noise ratio (SNR) calculation instead of the fast Fourier transformused in Gao et al. and searches signal templates with high SNR by quantumamplitude amplification. In this way, we achieve an exponential reduction ofthe qubit number compared with Gao et al.'s algorithm, keeping a quadraticspeedup over classical GW matched filtering with respect to the templatenumber.

Gravitational wave matched filtering by quantum Monte Carlo integration and quantum amplitude amplification