We study analytically the relaxation eigenmodes of a simple Monte Carlo algorithm, corresponding to a particle in a box which moves by uniform random jumps. Moves outside of the box are rejected. At long times, the system approaches the equilibrium probability density, which is uniform inside the box. We show that the relaxation towards this equilibrium is unusual: for a jump length comparable to the size of the box, the number of relaxation eigenmodes can be surprisingly small, one or two. We provide a complete analytic description of the transition between these two regimes. When only a single relaxation eigenmode is present, a suitable choice of the symmetry of the initial conditions gives a localizing decay to equilibrium. In this case, the deviation from equilibrium concentrates at the edges of the box where the rejection probability is maximal. Finally, in addition to the relaxation analysis of the master equation, we also describe the full eigen-spectrum of the master equation including its sub-leading eigen-modes.
翻译:我们用分析方式研究一个简单的蒙特卡洛算法的放松机能模式,该算法与一个以统一随机跳动方式移动的盒子中的粒子相对应。 框外的移动被否决。 长时间以来, 系统接近平衡概率密度, 与盒内相同。 我们显示, 向这个平衡的放松是不寻常的: 对于一个与盒大小相仿的跳动长度, 放松机能模式的数量可能令人惊讶地小, 一到两个。 我们给出了对这两个体系之间过渡的完整分析性描述。 当只有单一的放松机能模式存在时, 对初始条件的对应性做出适当的选择, 会使局部衰减到平衡。 在这种情况下, 偏向平衡点的偏移会集中在盒的边缘, 那里的拒绝机能最大。 最后, 除了主方程的放松分析外, 我们还描述了主方程的完全的eigen- pectrum, 包括它的次导eigen- mods。</s>