3 citations · 7 across the 12 of their papers we have counts for
13 papers
Combinatorial optimization of connected UAV communication bridges for emergency response
Matteo Vandelli, Daniele Dragoni
We present a combinatorial optimization problem for the strategic deployment of UAVs equipped with 5G antennas to assist rescue operations in regions hit by natural disasters. Our…
Quantum Computing for Industrial Electromagnetics: Applicability and Case Studies in Solving Maxwell's Equations
Francesco Turro, Marco Maronese, Daniele Dragoni
Computational electromagnetics plays a central role in many industrial applications but often requires substantial computational resources, particularly when fine spatial discretiz…
A Resource-Efficient Quantum Framework for Graph Coloring and Chromatic Number Estimation
Francesco Turro, Daniele Dragoni
Many industrial optimization tasks can be modeled as graph coloring, where adjacent vertices must have different colors. This NP-hard problem is challenging for large graphs. We pr…
Feasibility-driven QAOA with penalty scheduling
Francesco Ferrari, Matteo Vandelli, Daniele Dragoni
Most available quantum algorithms address constrained optimization problems by treating constraints as soft penalty terms within a QUBO formulation. This approach requires careful…
Emergency hub placement with a neutral-atom quantum computer
Sara Tarquini, Matteo Vandelli, Francesco Ferrari +2
We study the problem of emergency operation center placement in disaster response, where a minimal number of hubs must be selected to ensure timely coverage of all affected locatio…
Drone delivery packing problem on a neutral-atom quantum computer
Sara Tarquini, Matteo Vandelli, Francesco Ferrari +2
Quantum architectures based on neutral atoms have gained significant attention in recent years as specialized computational machines due to their ability to directly encode the ind…
Constraint-preserving quantum algorithm for the multi-frequency antenna placement problem
Matteo Vandelli, Francesco Ferrari, Daniele Dragoni
Quantum algorithms for combinatorial optimization typically encode constraints as soft penalties within the objective function, which can reduce efficiency and scalability compared…
High-expressibility Quantum Neural Networks using only classical resources
Marco Maronese, Francesco Ferrari, Matteo Vandelli +1
Quantum neural networks (QNNs), as currently formulated, are near-term quantum machine learning architectures that leverage parameterized quantum circuits with the aim of improving…
Practical Application of the Quantum Carleman Lattice Boltzmann Method in Industrial CFD Simulations
Francesco Turro, Alessandra Lignarolo, Daniele Dragoni
Computational Fluid Dynamics simulations are crucial in industrial applications but require extensive computational resources, particularly for extreme turbulent regimes. While cla…
Parallel splitting method for large-scale quadratic programs
Matteo Vandelli, Francesco Ferrari, Daniele Dragoni
Current algorithms for large-scale industrial optimization problems typically face a trade-off: they either require exponential time to reach optimal solutions, or employ problem-s…
Quantum machine learning algorithms for anomaly detection: A review
Sebastiano Corli, Lorenzo Moro, Daniele Dragoni +2
The advent of quantum computers has justified the development of quantum machine learning algorithms , based on the adaptation of the principles of machine learning to the formalis…
Testing Quantum and Simulated Annealers on the Drone Delivery Packing Problem
Sara Tarquini, Daniele Dragoni, Matteo Vandelli +1
Using drones to perform human-related tasks can play a key role in various fields, such as defense, disaster response, agriculture, healthcare, and many others. The drone delivery…
Evaluating the Practicality of Quantum Optimization Algorithms for Prototypical Industrial Applications
Matteo Vandelli, Alessandra Lignarolo, Carlo Cavazzoni +1
The optimization of the power consumption of antenna networks is a problem with a potential impact in the field of telecommunications. In this work, we investigate the application…