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arXiv 1808.04796cond-mat.soft
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胶体粘滞耦合动力学中记忆出现的定量分析

A quantitative analysis of the emergence of memory in the viscously coupled dynamics of colloids

Shuvojit Paul, Randhir Kumar, Ayan Banerjee

摘要:

我们提供了一个定量描述的记忆进化从显然是随机马尔可夫动力学的一对光学捕获的胶体微粒在水中。粒子被捕获在彼此非常接近的位置,使得所得的流体动力学相互作用导致非马尔可夫签名,其由每个粒子的布朗运动的双指数自关联函数表现。在这个系统中的内存的出现,我们量化的能量存储和证明,一对马尔可夫粒子-限制在单独的光阱中的粘性流体-可以描述在一个单一的布朗粒子的框架中的粘弹性介质。我们定义和量化的两个粒子系统的等效存储和损耗模量,并通过实验表明,记忆效应减少与增加颗粒分离和增加与一个歪斜的刚度比之间的陷阱。

英文摘要:

We provide a quantitative description of the evolution of memory from the apparently random Markovian dynamics of a pair of optically trapped colloidal microparticles in water. The particles are trapped in very close proximity of each other so that the resultant hydrodynamic interactions lead to non-Markovian signatures manifested by the double exponential auto-correlation function for the Brownian motion of each particle. In connection with the emergence of memory in this system, we quantify the storage of energy and demonstrate that a pair of Markovian particles - confined in individual optical traps in a viscous fluid - can be described in the framework of a single Brownian particle in a viscoelastic medium. We define and quantify the equivalent storage and loss moduli of the two-particle system, and show experimentally that the memory effects reduce with increasing particle separation and increase with a skewed stiffness ratio between the traps.

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