Year: 2026
Type: preprint
Abstract: 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 present a quantum encoding requiring qubits that scale logarithmically with the number of colors and linearly with vertices. Using adiabatic evolution with a novel mixer Hamiltonian and vertex terms, we compute the chromatic number and demonstrate robustness by solving constrained truck loading problems.
Source: arXiv (Cornell University)
Authors: Turro, Francesco, Dragoni, Daniele
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7202207863
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