The author introduces structured quantum search algorithms to address the k-SAT problem efficiently, focusing on satisfiable instances. The approach combines k-local quantum search and adiabatic variants to improve efficiency.
This paper proposes a novel Two-Step Quantum Search (TSQS) algorithm for solving the Traveling Salesman Problem (TSP) that leverages Higher-Order Unconstrained Binary Optimization (HOBO) encoding to achieve efficient initial state preparation and a quadratic speedup compared to classical methods.