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Reversible causal graph dynamics: invertibility, block representation, vertex-preservation

机译:可逆因果图动态:可逆性,块表示,顶点保存

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Causal Graph Dynamics extend Cellular Automata to arbitrary time-varying graphs of bounded degree. The whole graph evolves in discrete time steps, and this global evolution is required to have a number of symmetries: shift-invariance (it acts everywhere the same) and causality (information has a bounded speed of propagation). We add a further physics-like symmetry, namely reversibility. In particular, we extend two fundamental results on reversible cellular automata, by proving that the inverse of a causal graph dynamics is a causal graph dynamics, and that these reversible causal graph dynamics can be represented as finite-depth circuits of local reversible gates. We also show that reversible causal graph dynamics preserve the size of all but a finite number of graphs.
机译:因果图动态将蜂窝自动机扩展到有界度的任意时变图。整个图表在离散时间步骤中发展,并且需要这种全局演变具有许多对称性:移位不变性(它到处都是相同的)和因果关系(信息具有界限传播速度)。我们添加了一种进一步的物理样对称性,即可逆性。特别是,我们通过证明因果图动力学的反比是一种因果图动态的反向的两个基本结果,并且这些可逆因果图动态可以表示为局部可逆门的有限深度电路。我们还表明可逆因果图动态保留了所有图数的所有图数。

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