3 papers
quant-ph2026
Separating Ansatz Discovery from Deployment on Larger Problems: Reinforcement Learning for Modular Circuit Design
Gloria Turati, Simone FoderÃ, Riccardo Nembrini +2
As quantum computing continues to gain attention, there is growing interest in how classical machine learning can assist quantum workflows in practice. Automated circuit design, so…
quant-ph2025
Quantum Approaches to Urban Logistics: From Core QAOA to Clustered Scalability
F. Picariello, G. Turati, R. Antonelli +10
The Traveling Salesman Problem (TSP) is a fundamental challenge in combinatorial optimization, widely applied in logistics and transportation. As the size of TSP instances grows, t…
quant-ph2025
Hamiltonian Expressibility for Ansatz Selection in Variational Quantum Algorithms
Filippo Brozzi, Gloria Turati, Maurizio Ferrari Dacrema +2
In the context of Variational Quantum Algorithms (VQAs), selecting an appropriate ansatz is crucial for efficient problem-solving. Hamiltonian expressibility has been introduced as…