论文标题
基于统计力学的细胞自动机分类
Classification of Cellular Automata based on Statistical Mechanics
论文作者
论文摘要
蜂窝自动机是离散空间中的一组计算模型，该计算模型具有由社区规则定义的离散时间演变。它们通常用于模拟物理和科学中的许多复杂系统。在这项工作中，统计力学和热力学用于分析一大批全套外部二维细胞自动机。热力学变量和电势是根据三种不同方法得出和计算的，以确定细胞自动机规则是否代表类似于理想气体的系统，在热力学平衡中或从热力学平衡中。建议这种分类足够强大，可以预测特定规则集的有趣属性。
Cellular automata are a set of computational models in discrete space that have a discrete time evolution defined by neighbourhood rules. They are used to simulate many complex systems in physics and science in general. In this work, statistical mechanics and thermodynamics are used to analyse a large set of outer totalistic two-dimensional cellular automata. Thermodynamic variables and potentials are derived and computed according to three different approaches to determine if a cellular automaton rule is representing a system akin to the ideal gas, in or out of the thermodynamical equilibrium. It is suggested that this classification is sufficiently robust and predictive of interesting properties for particular set of rules.
