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arXiv 2211.04789cond-mat.stat-mechphysics.bio-phq-bio.QM
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反常扩散的稳健判据

Towards a robust criterion of anomalous diffusion

Vittoria Sposini, Diego Krapf, Enzo Marinari, Raimon Sunyer, Felix Ritort, Fereydoon Taheri, Christine Selhuber-Unkel, Rebecca Benelli, Matthias Weiss, Ralf Metzler, Gleb Oshanin

摘要:

反常扩散是扩散粒子的扩散动力学与传统布朗运动定律的背离,是大量复杂软物质和生物系统的特征。异常扩散的出现是由于各种物理机制,例如,捕获相互作用或环境的粘弹性。然而,有时系统动力学被错误地认为是反常的,尽管事实上真正的运动是布朗运动,反之亦然。在确定动态是正常还是异常时的这种模糊性可能具有深远的影响,例如,反应或弛豫定律的预测。证明一个系统表现出正常或非正常扩散是非常可取的大量应用。在这里,我们提出了一个标准的单轨迹的功率谱分析的方法的基础上的扩散。该准则的鲁棒性研究分数布朗运动的轨迹,一个无处不在的随机过程的描述的随机扩散,在存在两种类型的测量误差。特别是,我们发现,我们的标准是非常强大的subdiffusion。在不存在或存在额外的位置噪声的情况下,对替代数据的各种测试证明了该方法在实际环境中的有效性。最后,我们提供了一个概念验证的基础上,表现出正常和非正常扩散的各种实验。

英文摘要:

Anomalous-diffusion, the departure of the spreading dynamics of diffusing particles from the traditional law of Brownian-motion, is a signature feature of a large number of complex soft-matter and biological systems. Anomalous-diffusion emerges due to a variety of physical mechanisms, e.g., trapping interactions or the viscoelasticity of the environment. However, sometimes systems dynamics are erroneously claimed to be anomalous, despite the fact that the true motion is Brownian -- or vice versa. This ambiguity in establishing whether the dynamics as normal or anomalous can have far-reaching consequences, e.g., in predictions for reaction- or relaxation-laws. Demonstrating that a system exhibits normal- or anomalous-diffusion is highly desirable for a vast host of applications. Here, we present a criterion for anomalous-diffusion based on the method of power-spectral analysis of single trajectories. The robustness of this criterion is studied for trajectories of fractional-Brownian-motion, a ubiquitous stochastic process for the description of anomalous-diffusion, in the presence of two types of measurement errors. In particular, we find that our criterion is very robust for subdiffusion. Various tests on surrogate data in absence or presence of additional positional noise demonstrate the efficacy of this method in practical contexts. Finally, we provide a proof-of-concept based on diverse experiments exhibiting both normal and anomalous-diffusion.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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