Tree Search and Quantum Computation

TL;DR

This paper explores integrating classical tree search concepts with quantum algorithms like Grover's to enhance search efficiency, examining effects of variable branching and heuristic methods in hybrid quantum search systems.

Contribution

It introduces a hybrid quantum-classical tree search framework that considers variable branching factors and heuristic strategies, advancing quantum search applications.

Findings

Quantum search speedup is affected by branching factors.

Heuristic integration influences quantum search efficiency.

Hybrid models offer new avenues for problem solving.

Abstract

Traditional tree search algorithms supply a blueprint for modeling problem solving behaviour. A diverse spectrum of problems can be formulated in terms of tree search. Quantum computation, in particular Grover's algorithm, has aroused a great deal of interest since it allows for a quadratic speedup to be obtained in search procedures. In this work we consider the impact of incorporating classical search concepts alongside Grover's algorithm into a hybrid quantum search system. Some of the crucial points examined include: (1) the reverberations of contemplating the use of non-constant branching factors; (2) determining the consequences of incorporating an heuristic perspective into a quantum tree search model.