51 citations · 225 across the 21 of their papers we have counts for
27 papers
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…
Minor Embedding for Quantum Annealing with Reinforcement Learning
Riccardo Nembrini, Maurizio Ferrari Dacrema, Paolo Cremonesi
Quantum Annealing (QA) is a quantum computing paradigm for solving combinatorial optimization problems formulated as Quadratic Unconstrained Binary Optimization (QUBO) problems. An…
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…
Comment on arXiv:2307.08384 "Efficient Quantum State Preparation with Walsh Series"
Riccardo Pellini, Maurizio Ferrari Dacrema
In this paper, we discuss the Walsh Series Loader (WSL) algorithm, proposed by. In particular, we observe that the paper does not describe how to implement the term of order zero o…
A Worrying Reproducibility Study of Intent-Aware Recommendation Models
Faisal Shehzad, Maurizio Ferrari Dacrema, Dietmar Jannach
Lately, we have observed a growing interest in intent-aware recommender systems (IARS). The promise of such systems is that they are capable of generating better recommendations by…
An Empirical Analysis on the Effectiveness of the Variational Quantum Linear Solver
Gloria Turati, Alessia Marruzzo, Maurizio Ferrari Dacrema +1
Variational Quantum Algorithms (VQAs) have emerged as promising methods for tackling complex problems on near-term quantum devices. Among these algorithms, the Variational Quantum…