AI 中文总结
针对图着色这一工业优化建模的NP难题，提出量子编码框架，用含新型混合哈密顿量与顶点项的绝热演化计算色数，通过求解受限卡车装载问题验证了其鲁棒性。
AI 中文摘要
许多工业优化任务可建模为图着色问题，要求相邻顶点颜色不同，这一NP难题对大图极具挑战性。我们提出一种量子编码，所需量子比特数随颜色数量呈对数增长、随顶点数量呈线性增长。采用含新型混合哈密顿量与顶点项的绝热演化，计算色数并通过求解受限卡车装载问题验证其鲁棒性。
英文摘要
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.
Comments10 pages, 4 figures, 2 tables
