Quantum Approximate Optimization Algorithm (QAOA) and Variational Quantum Algorithms (VQA)

About

These research activities focus on the application of Quantum Approximate Optimization Algorithms (QAOA) and Variational Quantum Algorithms (VQAs) to complex combinatorial optimization problems, including flow shop scheduling, satellite scheduling, the Traveling Salesman Problem (TSP), Partial Max-CSP, and qubit routing. A portion of the research is also dedicated to ansatz optimization using metaheuristic techniques, such as simulated annealing, with the aim of improving the computational efficiency and solution quality produced by VQAs.

These activities are primarily carried out in collaboration with Professor Marco Baioletti, PhD student Nicolò Vescera, and researchers Angelo Oddi, Riccardo Rasconi, and Fabrizio Fagiolo.