论文标题

三种异质随机模型的无限厄贡理论,并应用于子recoil激光冷却

Infinite ergodic theory for three heterogeneous stochastic models with application to subrecoil laser cooling

论文作者

Akimoto, Takuma, Barkai, Eli, Radons, Günter

论文摘要

我们比较了子固体激光冷却气体的三个随机模型的动能的厄乳外性能。一个模型基于异质随机步行(HRW),另一个模型是带有远距离跳跃的HRW(指数模型),另一个是指数模型(确定性模型)的均值近似值。所有模型在长期限制中均显示动量的积累,而正式的稳态不能归一化,即存在无限的不变密度。我们获得了指数和确定性模型的无限不变密度和缩放函数的确切形式,并为HRW模型中的动量分布设计了有用的近似值。尽管这些模型在动力学上是非相同的,但自然要想知道它们的厄贡特性是否具有共同的特征,因为它们都是通过无限不变密度描述的。我们表明,这个问题的答案取决于所研究的可观察到的类型。如果可观察到的是可以集成的,则如darling-kac定理所描述的,诸如时间平均的统计行为之类的诸如时代平均的统计行为。相反,对于不可综合的可观察物,这些模型一般表现出非相同的统计定律。这意味着着眼于不可融合的可观察到,我们发现了冷却过程的非宇宙特征,希望可以更好地理解最适合该过程统计描述的特定模型。除激光冷却之外,预计此结果将对许多其他系统保持原样。

We compare ergodic properties of the kinetic energy for three stochastic models of subrecoil-laser-cooled gases. One model is based on a heterogeneous random walk (HRW), another is an HRW with long-range jumps (the exponential model), and the other is a mean-field-like approximation of the exponential model (the deterministic model). All the models show an accumulation of the momentum at zero in the long-time limit, and a formal steady state cannot be normalized, i.e., there exists an infinite invariant density. We obtain the exact form of the infinite invariant density and the scaling function for the exponential and deterministic models and devise a useful approximation for the momentum distribution in the HRW model. While the models are kinetically non-identical, it is natural to wonder whether their ergodic properties share common traits, given that they are all described by an infinite invariant density. We show that the answer to this question depends on the type of observable under study. If the observable is integrable, the ergodic properties such as the statistical behavior of the time averages are universal as they are described by the Darling-Kac theorem. In contrast, for non-integrable observables, the models in general exhibit non-identical statistical laws. This implies that focusing on non-integrable observables, we discover non-universal features of the cooling process, that hopefully can lead to a better understanding of the particular model most suitable for a statistical description of the process. This result is expected to hold true for many other systems, beyond laser cooling.

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