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Quantum phase discrimination with applications to quantum search on graphs

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Guanzhong Li, Lvzhou Li, Jingquan Luo (Apr 22 2025).
Abstract: We study the phase discrimination problem, in which we want to decide whether the eigenphase θ∈(−π,π]\theta\in(-\pi,\pi]θ∈(−π,π] of a given eigenstate ∣ψ⟩|\psi\rangle∣ψ⟩ with eigenvalue eiθe^{i\theta}eiθ is zero or not, using applications of the unitary UUU provided as a black box oracle.We propose a quantum algorithm named \it quantum phase discrimination(QPD) for this task, with optimal query complexity Θ(1λlog⁡1δ)\Theta(\frac{1}{\lambda}\log\frac{1}{\delta})Θ(λ1​logδ1​) to the oracle UUU, where λ\lambdaλ is the gap between zero and non-zero eigenphases and δ\deltaδ the allowed one-sided error. The quantum circuit is simple, consisting of only one ancillary qubit and a sequence of controlled-UUU interleaved with single qubit YYY rotations, whose angles are given by a simple analytical formula. Quantum phase discrimination could become a fundamental subroutine in other quantum algorithms, as we present two applications to quantum search on graphs: i) Spatial search on graphs. Inspired by the structure of QPD, we propose a new quantum walk model, and based on them we tackle the spatial search problem, obtaining a novel quantum search algorithm. For any graph with any number of marked vertices, the quantum algorithm that can find a marked vertex with probability Ω(1)\Omega(1)Ω(1) in total evolution time O(1λε) O(\frac{1}{\lambda \sqrt{\varepsilon}})O(λε​1​) and query complexity O(1ε) O(\frac{1}{\sqrt{\varepsilon}})O(ε​1​), where λ\lambdaλ is the gap between the zero and non-zero eigenvalues of the graph Laplacian and ε\varepsilonε is a lower bound on the proportion of marked vertices. ii) Path-finding on graphs. By using QPD, we reduce the query complexity of a path-finding algorithm proposed by Li and Zur [arxiv: 2311.07372] from O~(n11)\tilde{O}(n^{11})O~(n11) to O~(n8)\tilde{O}(n^8)O~(n8), in a welded-tree circuit graph with Θ(n2n)\Theta(n2^n)Θ(n2n) vertices. Besides these two applications, we argue that more quantum algorithms might benefit from QPD.
Arxiv: https://arxiv.org/abs/2504.15194

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