Contour-integral based quantum eigenvalue transformation: analysis and applications

Abstract:Eigenvalue transformations appear ubiquitously in scientific computation, ranging from matrix polynomials to differential equations, and are beyond the reach of the quantum singular value transformation framework. In this work, we study the efficiency of quantum algorithms based on contour integral representation for eigenvalue transformations from both theoretical and practical aspects. Theoretically, we establish a complete complexity analysis of the contour integral approach proposed in [Takahira, Ohashi, Sogabe, and Usuda. Quant. Inf. Comput., 22, 11\&12, 965--979 (2021)]. Moreover, we combine the contour integral approach and the sampling-based linear combination of unitaries to propose a quantum algorithm for estimating observables of eigenvalue transformations using only $3$ additional qubits. Practically, we design contour integral based quantum algorithms for linear ordinary differential equations, $\varphi$-functions, Fréchet derivatives of matrix functions, and matrix functions. In particular, we show that the contour integral algorithm can outperform all the existing quantum algorithms in the case of solving asymptotically stable differential equations.

Quantum Physics (quant-ph); Numerical Analysis (math.NA)

arXiv:2601.11959 [quant-ph]

(or arXiv:2601.11959v3 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2601.11959 Focus to learn more arXiv-issued DOI via DataCite

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