Gavrilov Momčilo, Bechhoefer John
Department of Physics, Simon Fraser University, Burnaby, British Columbia, Canada V5A 1S6.
Department of Physics, Simon Fraser University, Burnaby, British Columbia, Canada V5A 1S6
Philos Trans A Math Phys Eng Sci. 2017 Mar 6;375(2088). doi: 10.1098/rsta.2016.0217.
Feedback traps are tools for trapping and manipulating single charged objects, such as molecules in solution. An alternative to optical tweezers and other single-molecule techniques, they use feedback to counteract the Brownian motion of a molecule of interest. The trap first acquires information about a molecule's position and then applies an electric feedback force to move the molecule. Since electric forces are stronger than optical forces at small scales, feedback traps are the best way to trap single molecules without 'touching' them (e.g. by putting them in a small box or attaching them to a tether). Feedback traps can do more than trap molecules: they can also subject a target object to forces that are calculated to be the gradient of a desired potential function U(x). If the feedback loop is fast enough, it creates a virtual potential whose dynamics will be very close to those of a particle in an actual potential U(x). But because the dynamics are entirely a result of the feedback loop-absent the feedback, there is only an object diffusing in a fluid-we are free to specify and then manipulate in time an arbitrary potential U(x,t). Here, we review recent applications of feedback traps to studies on the fundamental connections between information and thermodynamics, a topic where feedback plays an even more fundamental role. We discuss how recursive maximum-likelihood techniques allow continuous calibration, to compensate for drifts in experiments that last for days. We consider ways to estimate work and heat, using them to measure fluctuating energies to a precision of ±0.03 kT over these long experiments. Finally, we compare work and heat measurements of the costs of information erasure, the Landauer limit of kT ln 2 per bit of information erased. We argue that, when you want to know the average heat transferred to a bath in a long protocol, you should measure instead the average work and then infer the heat using the first law of thermodynamics.This article is part of the themed issue 'Horizons of cybernetical physics'.
反馈阱是用于捕获和操纵单电荷物体（如溶液中的分子）的工具。作为光镊和其他单分子技术的替代方法，它们利用反馈来抵消感兴趣分子的布朗运动。该阱首先获取有关分子位置的信息，然后施加电反馈力来移动分子。由于在小尺度下电力比光力更强，反馈阱是在不“接触”分子的情况下（例如将它们放入小盒子或系在系链上）捕获单分子的最佳方法。反馈阱不仅可以捕获分子：它们还可以使目标物体受到根据所需势函数U(x)的梯度计算得出的力。如果反馈回路足够快，它会创建一个虚拟势，其动力学将非常接近实际势U(x)中的粒子的动力学。但由于动力学完全是反馈回路的结果——没有反馈时，只有一个物体在流体中扩散——我们可以自由指定并及时操纵任意势U(x,t)。在这里，我们回顾了反馈阱在信息与热力学基本联系研究中的最新应用，在这个主题中反馈起着更为根本的作用。我们讨论了递归最大似然技术如何实现连续校准，以补偿持续数天的实验中的漂移。我们考虑估计功和热的方法，在这些长时间实验中使用它们将波动能量测量到±0.03 kT的精度。最后，我们比较了信息擦除成本的功和热测量，即每擦除一位信息的兰道尔极限kT ln 2。我们认为，当你想知道在一个长协议中传递到热库的平均热量时，你应该测量平均功，然后使用热力学第一定律推断热量。本文是主题为“控制论物理的前沿”的特刊的一部分。
