A Unified Complexity Framework for Quantum Property Testing

Abstract

We develop a unified framework for analyzing the complexity of quantum property testing through functionals of the form ${\mathcal{L}}_{\varphi }(\rho )=\mathrm{tr}(\varphi (d\rho ))/d$, where $\rho$ is an unknown $d$-dimensional quantum state and $\varphi$ is a given function. A master theorem is established that derives sample complexity lower bounds for estimating ${\mathcal{L}}_{\varphi }(\rho )$ from properties of $\varphi$, combining Haar-random moment encoding with moment matching and best polynomial approximation. Corresponding query complexity lower bounds follow from quantum sample-to-query lifting. The framework yields nearly tight bounds for a broad class of problems, including entropy estimation (von Neumann, Rényi, and Tsallis), closeness estimation (trace distance and Uhlmann fidelity), spectrum estimation, rank testing (operator rank, Schmidt rank, and matrix product states). Combined with known upper bounds, these results resolve several open problems and establish the optimality of 31 quantum algorithms since 2015, up to polylogarithmic factors.

arXiv comment46 pages, 2 tables. Title changed and more references added; added Schmidt rank testing and matrix product state (MPS) testing; restructured the Abstract, Introduction, and the master theorem; improved the precision-regime for Renyi and Tsallis entropy estimation; refined the proofs