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This paper improves a numerical subroutine for computing QSP phase factors, replacing an unstable-prone Prony-based step with a logarithmic-derivative and Newton-Girard approach that runs in O(d log² d) time. For quantum algorithm developers, the practical value is a faster, simpler classical preprocessing step for Hamiltonian simulation, matrix inversion, and related workloads, with reported errors near 10⁻¹². Results are limited to the authors' benchmarks, so their impact on end-to-end quantum resource costs remains to be shown.
Sources coveringarXiv, Quantum Computing Report
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Quantum Signal Processing Phase Factorization via Logarithmic Derivatives

arXiv2 min read

arXiv:2610.14259v1 Announce Type: new Abstract: Quantum signal processing (QSP) requires the efficient computation of phase factors associated with a polynomial transformation. One existing stable factorization method avoids direct root finding but relies on Prony's method to recover a polynomial from weighted power sums of its roots (arXiv:2202.02671). We present a modification of this approach that eliminates Prony's method by using the logarithmic derivative of an associated polynomial. Because the logarithmic derivative has the same residue at every root after accounting for multiplicity, its Fourier coefficients directly yield the unweighted power sums of the roots inside the unit disk. The Newton--Girard identities then recover the coefficients of the corresponding polynomial without computing its roots. The resulting algorithm has $O(d\log^2 d)$ computational complexity and simplifies the factorization procedure of the original method. In numerical experiments on Hamiltonian simulation, eigenstate filtering, matrix inversion, and the Fermi--Dirac operator, our implementation computes phase factors in seconds with maximum errors on the order of $10^{-12}$.

Abstract:Quantum signal processing (QSP) requires the efficient computation of phase factors associated with a polynomial transformation. One existing stable factorization method avoids direct root finding but relies on Prony's method to recover a polynomial from weighted power sums of its roots (arXiv:2202.02671). We present a modification of this approach that eliminates Prony's method by using the logarithmic derivative of an associated polynomial. Because the logarithmic derivative has the same residue at every root after accounting for multiplicity, its Fourier coefficients directly yield the unweighted power sums of the roots inside the unit disk. The Newton--Girard identities then recover the coefficients of the corresponding polynomial without computing its roots. The resulting algorithm has $O(d\log^2 d)$ computational complexity and simplifies the factorization procedure of the original method. In numerical experiments on Hamiltonian simulation, eigenstate filtering, matrix inversion, and the Fermi--Dirac operator, our implementation computes phase factors in seconds with maximum errors on the order of $10^{-12}$.

12 pages, 5 figures. Code available at this https URL

arXiv:2610.14259 [quant-ph]

(or arXiv:2610.14259v1 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2610.14259 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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Full text under the publisher's open licence · 255 words

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