7 papers
Neural optimization of the most probable paths of 3D active Brownian particles
Bin Zheng, Zhongqiang Xiong, Changhao Li +7
We develop a variational neural-network framework to determine the most probable path (MPP) of a 3D active Brownian particle (ABP) by directly minimizing the Onsager-Machlup integr…
Geometric formulation of state-dependent Langevin dynamics using scalar free energy
Kento Yasuda, Zhongqiang Xiong, Zhanglin Hou +3
Stochastic dynamics with state-dependent diffusion are widely used for Brownian motion in confined, anisotropic, and hydrodynamically coupled systems. The conventional Langevin for…
Covariant Onsager and Onsager-Machlup principles for active and inertial dynamics
Kento Yasuda, Bin Zheng, Zhongqiang Xiong +5
The Onsager principle provides a variational route to the phenomenological equations of dissipative dynamics through the minimization of the Rayleighian. We develop a covariant for…
Fokker-Planck description of an active Brownian particle with rotational inertia
Lingyi Wang, Ziluo Zhang, Zhongqiang Xiong +3
We develop a perturbative framework to calculate the mean-squared displacement (MSD) of active Brownian particles (ABPs) with a finite moment of inertia. Starting from the correspo…
Ornstein-Uhlenbeck information particle: A new candidate of active agent
Xin Song, Xiji Shao, Yanwen Zhu +4
An information particle can acquire active-like motion through transforming the information entropy into effective self-propulsion velocity/force using the attached information eng…
Thermally driven two-sphere microswimmer with internal feedback control
Jun Li, Ziluo Zhang, Zhanglin Hou +4
We discuss the locomotion of a thermally driven elastic two-sphere microswimmer with internal feedback control that is realized by the position-dependent friction coefficients. In…