论文标题
轨迹类波动定理
Trajectory Class Fluctuation Theorem
论文作者
论文摘要
轨迹类波动定理（TCFT）实质上增强了热力学的第二定律 - 事实上，这可能是对资源通量的相当微弱的结合。实际上，它改善了自由能量的经验估计，这项已知在统计上具有挑战性的任务，并在实验实验的Josephson-Junction-Junction-Junction信息引擎中诊断出了成功和失败的信息处理。这里的发展证明了经验分析的合理性，阐明了其数学基础。 TCFT揭示了针对每个可测量的系统轨迹的宏观系统转换引起的热力学。在此，它直接打击了主导热力学计算的极罕见事件的统计挑战。并且，它揭示了新形式的自由能 - 可以解决分析和实际估计的形式。从概念上讲，TCFT统一了一系列先前建立的波动定理，从骗子的详细波动定理（单轨迹）到jarzynski的平等（轨迹结合）。
The Trajectory Class Fluctuation Theorem (TCFT) substantially strengthens the Second Law of Thermodynamics -- that, in point of fact, can be a rather weak bound on resource fluxes. Practically, it improves empirical estimates of free energies, a task known to be statistically challenging, and has diagnosed successful and failed information processing in experimentally-implemented Josephson-junction information engines. The development here justifies that empirical analysis, explicating its mathematical foundations. The TCFT reveals the thermodynamics induced by macroscopic system transformations for each measurable subset of system trajectories. In this, it directly combats the statistical challenge of extremely rare events that dominate thermodynamic calculations. And, it reveals new forms of free energy -- forms that can be solved for analytically and practically estimated. Conceptually, the TCFT unifies a host of previously-established fluctuation theorems, interpolating from Crooks' Detailed Fluctuation Theorem (single trajectories) to Jarzynski's Equality (trajectory ensembles).
