Gaussian white noise as a resource for work extraction
Gaussian white noise as a resource for work extraction
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高斯白噪声作为功提取的资源
DOI：
10.1103/physreve.95.032132
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
and Shin-ichi Sasa
中科院分区：
文献类型：
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作者：
Andreas Dechant;Adrian Baule;and Shin-ichi Sasa
我们表明，不相关的高斯噪声可以驱动系统的平衡，可以作为一种资源，从中可以提取的工作。我们考虑一个过阻尼粒子在一个周期性的潜力与内部自由度和状态依赖的摩擦，耦合到一个平衡浴。施加额外的高斯白色噪声驱动系统进入非平衡稳态，并导致有限的电流，如果电位是空间不对称的。因此，该模型作为一个布朗棘轮，其电流，我们计算明确在三个互补的限制。由于粒子电流仅由加性高斯白色噪声驱动，这表明后者可以潜在地对外部负载做功。通过比较提取的功率的能量注入由于噪声，我们讨论了这样的棘轮的效率。
We show that uncorrelated Gaussian noise can drive a system out of equilibrium and can serve as a resource from which work can be extracted. We consider an overdamped particle in a periodic potential with an internal degree of freedom and a state-dependent friction, coupled to an equilibrium bath. Applying additional Gaussian white noise drives the system into a nonequilibrium steady state and causes a finite current if the potential is spatially asymmetric. The model thus operates as a Brownian ratchet, whose current we calculate explicitly in three complementary limits. Since the particle current is driven solely by additive Gaussian white noise, this shows that the latter can potentially perform work against an external load. By comparing the extracted power to the energy injection due to the noise, we discuss the efficiency of such a ratchet.