The motility of living things and synthetic self-propelled objects is often described using Active Brownian particles. To capture the interaction of these particles with their often complex environment, this model can be augmented with empirical forces or torques, for example, to describe their alignment with an obstacle or wall after a collision. Here, we assess the quality of these empirical models by comparing their output predictions with trajectories of rod-shaped active particles that scatter sterically at a flat wall. We employ a classical least-squares method to evaluate the instantaneous torque. In addition, we lay out a Bayesian inference procedure to construct the posterior distribution of plausible model parameters. In contrast to the least squares fit, the Bayesian approach does not require orientational data of the active particle and can readily be applied to experimental tracking data.
Exact dynamics and dimensional effects in torque-driven trapped active Brownian particles
Indian Institute of Science Education and Research Mohali（印度科学教育研究学院莫哈利分校）；Tata Institute of Fundamental Research（塔塔基础研究所）；University of Vermont（佛蒙特大学）；Institute of Physics（物理研究所）；Homi Bhabha National Institute（霍米·巴巴国民研究所）
Taylor Dispersion in Sedimentation of an Axisymmetric Brownian Particle with Centre Offset
Wenzhou Institute, University of Chinese Academy of Sciences（中国科学院大学温州研究所）；Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health)（瓯江实验室（浙江省再生医学、视觉与脑健康实验室））；Graduate School of Information Science, University of Hyogo（兵库大学信息科学研究院）
