Li-Shing Lin

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 integral (OMI). To obtain the OMI, we use the Onsager-Machlup…

We use the Deep Q-Network with reinforcement learning to investigate the emergence of odd elasticity in an elastic microswimmer model. For an elastic microswimmer, it is challenging to obtain the optimized dynamics due to the intricate…

We perform numerical simulations of a model micromachine driven by catalytic chemical reactions. Our model includes a mechano-chemical coupling between the structural variables and the nonequilibrium variable describing the catalytic…

We perform numerical simulations of odd microswimmers consisting of three spheres and two odd springs. To describe the hydrodynamic interaction, both the Oseen-type and the Rotne-Prager-Yamakawa (RPY)-type mobilities are used. For the…

Using Onsager's variational principle, we derive dynamical equations for a nonequilibrium active system with odd elasticity. The elimination of the extra variable that is coupled to the nonequilibrium driving force leads to the…

We investigate the statistical properties of fluctuations in active systems that are governed by non-symmetric responses. Both an underdamped Langevin system with an odd resistance tensor and an overdamped Langevin system with an odd…

The variational principle of the Onsager-Machlup integral is used to describe the stochastic dynamics of a micromachine, such as an enzyme, characterized by odd elasticity. The obtained most probable path is found to become non-reciprocal…