光激发转移系统中概率混沌涨落加速扩散
Accelerated diffusion by chaotic fluctuation in probability in photoexcitation transfer system
摘要：
我们报告了一种新的加速扩散现象，它是由一维随机行走产生的，其中两个方向之一的飞行概率（即，偏置）以周期、准周期和混沌方式动态振荡。在量子点网络中的纳米级光激发转移过程中，可以观察到量子点网络中激子在量子点底能级上存在的概率随参数的变化而发生不同程度的振荡.我们评估从量子点网络模型获得的时间序列的时间平均均方位移（ETMSD）的系综平均，该量子点网络模型产生各种振荡行为，因为ETMSD表现出取决于波动偏置的特征变化;在正常扩散的情况下，ETMSD的渐近行为与时间成比例（即，线性增长函数），而在超扩散的情况下，它以大于1的指数非线性增长。我们发现，当涨落偏压具有弱混沌特性时，由于涨落偏压的瞬态非平稳性，其频谱在低频处具有高功率，从而可以显著加速扩散.通过引入一个简化的模型，我们的随机行走，它表现出超扩散以及正常扩散，我们解释了加速扩散的机制，通过分析均方位移。
英文摘要：
We report a new accelerated diffusion phenomenon that is produced by a one-dimensional ran- dom walk in which the flight probability to one of the two directions (i.e., bias) oscillates dynam- ically in periodic, quasiperiodic, and chaotic manners. The probability oscillation dynamics can be physically observed in nanoscale photoexcitation transfer in a quantum-dot network, where the existence probability of an exciton at the bottom energy level of a quantum dot fluctuates dif- ferently with a parameter setting. We evaluate the ensemble average of the time-averaged mean square displacement (ETMSD) of the time series obtained from the quantum-dot network model that generates various oscillatory behaviors because the ETMSD exhibits characteristic changes depending on the fluctuating bias; in the case of normal diffusion, the asymptotic behavior of the ETMSD is proportional to the time (i.e., a linear growth function), whereas it grows nonlinearly with an exponent greater than 1 in the case of superdiffusion. We find that the diffusion can be accelerated significantly when the fluctuating bias is characterized as weak chaos owing to the transient nonstationarity of its biases, in which the spectrum contains high power at low frequen- cies. By introducing a simplified model of our random walk, which exhibits superdiffusion as well as normal diffusion, we explain the mechanism of the accelerated diffusion by analyzing the mean square displacement.
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