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