论文标题
复杂物质字段通用模型，具有最佳缩放率用于解决组合优化问题
Complex matter field universal models with optimal scaling for solving combinatorial optimization problems
论文作者
论文摘要
我们基于经典复杂物质字段的通用模型开发了通用模型，该模型允许将许多现实生活中的NP-HARD组合优化问题最佳地映射到最小化旋转汉密尔顿的问题中。我们针对三个著名的问题明确地制定了一对一的映射：图形着色，旅行推销员和模块化N-Queens问题。我们表明，与标准Ising公式相比，这种公式可以在搜索全局最小值的搜索中有几个数量级的改善。同时，振幅动力学从当地的最小值中逸出。
We develop a universal model based on the classical complex matter fields that allow the optimal mapping of many real-life NP-hard combinatorial optimisation problems into the problem of minimising a spin Hamiltonian. We explicitly formulate one-to-one mapping for three famous problems: graph colouring, the travelling salesman, and the modular N-queens problem. We show that such a formulation allows for several orders of magnitude improvement in the search for the global minimum compared to the standard Ising formulation. At the same time, the amplitude dynamics escape from the local minima.
