论文标题
随机系统中熵生产速率的下限远离平衡
Lower bound for entropy production rate in stochastic systems far from equilibrium
论文作者
论文摘要
我们表明，主方程中Schnakenberg的熵生产速率是由Markov图的重量的函数限制的，此处将其定义为边缘上概率电流的绝对值之和。结果对于时间依赖性的非平衡熵生产率有效。此外，在一个一般框架中，我们证明了一个定理表明，分布之间的kullback-leibler分歧$ p（s）$和$ p'（s）：= p（m（s））$，其中$ m $是$ m（m（m（s））= s $，由$ p $ $ p $ $ p $ $ m的函数较低，代表$ p $ $ p'的范围。界限很紧，它可以改善Pinsker的不平等现象。该结果说明了非平衡热力学与图形论与有趣的应用之间的联系。
We show that the Schnakenberg's entropy production rate in a master equation is lower bounded by a function of the weight of the Markov graph, here defined as the sum of the absolute values of probability currents over the edges. The result is valid for time-dependent nonequilibrium entropy production rates. Moreover, in a general framework, we prove a theorem showing that the Kullback-Leibler divergence between distributions $P(s)$ and $P'(s):=P(m(s))$, where $m$ is an involution, $m(m(s))=s$, is lower bounded by a function of the total variation of $P$ and $P'$, for any $m$. The bound is tight and it improves on Pinsker's inequality for this setup. This result illustrates a connection between nonequilibrium thermodynamics and graph theory with interesting applications.
