论文标题
通过自动分化对非平衡系统的最佳控制
Optimal control of nonequilibrium systems through automatic differentiation
论文作者
论文摘要
控制非平衡系统以最大程度地减少耗散热量或工作的演变是设计纳米技术和生物学的关键目标。迄今为止，计算最佳协议的进展仅限于简单系统或接近平衡的演变。在这里，我们提出了一种基于自动差异化计算最佳协议的方法。我们的方法适用于复杂的系统和多维协议，并且远离均衡是有效的。我们通过在随着时变的谐波陷阱中复制布朗粒子的理论最佳方案来验证我们的方法。我们还计算了与近平衡行为的偏离行为，以逆转在一个晶格上的磁化逆转，以及由谐波陷阱驱动的屏障横穿，该谐波陷阱已被用来代表一系列生物学过程，包括生物分子展开反应。基于自动分化的算法优于远程磁化磁化强度逆转和驱动屏障交叉的近平衡理论。与近平衡理论方案相比，发现越过10KT的能源景观屏障的最佳方案可加快障碍区域的方法，并减慢障碍区域的出发方法。
Controlling the evolution of nonequilibrium systems to minimize dissipated heat or work is a key goal for designing nanodevices, both in nanotechnology and biology. Progress in computing optimal protocols has thus far been limited to either simple systems or near-equilibrium evolution. Here, we present an approach for computing optimal protocols based on automatic differentiation. Our methodology is applicable to complex systems and multidimensional protocols and is valid arbitrarily far from equilibrium. We validate our method by reproducing theoretical optimal protocols for a Brownian particle in a time-varying harmonic trap. We also compute departures from near-equilibrium behaviour for magnetization reversal on an Ising lattice and for barrier crossing driven by a harmonic trap, which has been used to represent a range of biological processes including biomolecular unfolding reactions. Algorithms based on automatic differentiation outperform the near-equilibrium theory for far-from-equilibrium magnetization reversal and driven barrier crossing. The optimal protocol for crossing an energy landscape barrier of 10kT is found to hasten the approach to, and slow the departure from, the barrier region compared to the near-equilibrium theoretical protocol.
