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quant-ph2026

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…

quant-ph2026

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…

quant-ph2026

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…

quant-ph2026

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…

quant-ph2026

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…

quant-ph2025

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…