通过趋性和群体感应相互作用的活性粒子的涨落流体动力学：静态与动态特性
Fluctuating hydrodynamics of active particles interacting via taxis and quorum sensing: static and dynamics
AI总结：
该研究推导并验证了通过趋性与群体感应作用的活性粒子的涨落流体动力学理论，证实其可准确预测多类活性粒子体系的大尺度静动态特性，揭示了相关相分离行为的宏观普适性与微观起源判定的局限性。
摘要：
本文推导并验证了通过趋性和群体感应相互作用的活性粒子的涨落流体动力学描述，研究对象既包括单分散体系，也包括多种活性粒子共存的混合体系。我们计算了存在空间运动调控时的平均稳态密度分布，以及相互作用体系的结构因子和中间散射函数。通过将理论预测与微观数值模拟结果对比，我们证明该涨落流体动力学理论可正确预测体系的大尺度静态与动态特性。我们还讨论了当尺度小于或相当于粒子持续长度的结构出现时，该理论失效的情况。当密度场是体系唯一的流体动力学模式时，我们发现通过群体感应或趋化作用相互作用的活性布朗粒子（active Brownian particles）、奔跑翻滚粒子（run-and-tumble particles）和活性奥恩斯坦-乌伦贝克粒子（active Ornstein-Uhlenbeck particles），表现出难以区分的大尺度特性。这种普适性意味着预测的物理规律具有有趣的鲁棒性，但也说明仅通过大尺度的图案观测不足以判断其微观起源。特别地，我们的结果预测，趋化诱导的相分离与运动诱导的相分离在宏观尺度上应具有很强的定性相似性。
英文摘要：
In this article we derive and test the fluctuating hydrodynamic description of active particles interacting via taxis and quorum sensing, both for mono-disperse systems and for mixtures of co-existing species of active particles. We compute the average steady-state density profile in the presence of spatial motility regulation, as well as the structure factor and intermediate scattering function for interacting systems. By comparing our predictions to microscopic numerical simulations, we show that our fluctuating hydrodynamics correctly predicts the large-scale static and dynamical properties of the system. We also discuss how the theory breaks down when structures emerge at scales smaller or comparable to the persistence length of the particles. When the density field is the unique hydrodynamic mode of the system, we show that active Brownian particles, run-and-tumble particles and active Ornstein-Uhlenbeck particles, interacting via quorum-sensing or chemotactic interactions, display undistinguishable large-scale properties. This form of universality implies an interesting robustness of the predicted physics but also that large-scale observations of patterns are insufficient to assess their microscopic origins. In particular, our results predict that chemotaxis-induced and motility-induced phase separation should share strong qualitative similarities at the macroscopic scale.
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