Palindromic structure of depth-efficient quantum search algorithms

Abstract

Grover's algorithm is optimal in query complexity, but not necessarily in circuit depth. We formulate unstructured quantum search as a circuit-depth optimization problem and identify a critical depth ratio separating query optimality from depth optimality. The resulting depth-efficient search operators exhibit a palindromic structure, in which shallow diffusion-like operators symmetrically replace selected Grover diffusion layers while preserving efficient amplitude amplification. This structure yields a simple depth-efficiency criterion and an analytic expression for the minimal expected depth. Applying the framework to $X$-type mixers, local diffusion operators, and nested local diffusion operators, we obtain substantial depth reductions over standard Grover search. In particular, nested local constructions reduce the total circuit depth by about $40\%$ when the oracle and Grover diffusion operators have comparable depth. These results reveal the resource-dependent nature of quantum-search optimality and establish palindromic constructions as a systematic route to depth-efficient quantum search algorithms.