A framework for optimal quantum spatial search using alternating phase-walks

TL;DR

This paper introduces an advanced quantum spatial search framework using alternating phase shifts and quantum walks, achieving optimal search times and overlaps on various periodic graphs, including complex rook graphs.

Contribution

It generalizes the Childs & Goldstone algorithm with a new alternating phase-walk approach, providing closed-form optimal parameters for periodic graphs and demonstrating improved search efficiency.

Findings

Achieves (\u221aN) search complexity on various graphs.

Provides closed-form expressions for optimal walk time and phase shifts.

Demonstrates superior performance on rook graphs compared to previous algorithms.

Abstract

We present a novel methodological framework for quantum spatial search, generalising the Childs & Goldstone ($\mathcal{CG}$) algorithm via alternating applications of marked-vertex phase shifts and continuous-time quantum walks. We determine closed form expressions for the optimal walk time and phase shift parameters for periodic graphs. These parameters are chosen to rotate the system about subsets of the graph Laplacian eigenstates, amplifying the probability of measuring the marked vertex. The state evolution is asymptotically optimal for any class of periodic graphs having a fixed number of unique eigenvalues. We demonstrate the effectiveness of the algorithm by applying it to obtain $\mathcal{O}(\sqrt{N})$ search on a variety of graphs. One important class is the $n \times n^3$ rook graph, which has $N=n^4$ vertices. On this class of graphs the $\mathcal{CG}$ algorithm performs suboptimally, achieving only $\mathcal{O}(N^{-1/8})$ overlap after time $\mathcal{O}(N^{5/8})$. Using the new alternating phase-walk framework, we show that $\mathcal{O}(1)$ overlap is obtained in $\mathcal{O}(\sqrt{N})$ phase-walk iterations.