Theory and practice of simulation of optical tweezers
Ann A. M. Bui, Alexander B. Stilgoe, Isaac C. D. Lenton, Lachlan J., Gibson, Anatolii V. Kashchuk, Shu Zhang, Halina Rubinsztein-Dunlop, Timo A., Nieminen

TL;DR
This paper reviews the theoretical foundations and practical methods for simulating particle dynamics in optical tweezers, emphasizing the integration of optical, Brownian, and viscous forces for accurate modeling.
Contribution
It provides a comprehensive overview of simulation techniques for optical tweezers, including force calculation methods and solutions to equations of motion, highlighting open research challenges.
Findings
Effective simulation of optical tweezers requires combining optical, Brownian, and viscous forces.
Various numerical methods are discussed for solving particle motion equations.
Open problems include improving force models and simulation accuracy.
Abstract
Computational modelling has made many useful contributions to the field of optical tweezers. One aspect in which it can be applied is the simulation of the dynamics of particles in optical tweezers. This can be useful for systems with many degrees of freedom, and for the simulation of experiments. While modelling of the optical force is a prerequisite for simulation of the motion of particles in optical traps, non-optical forces must also be included; the most important are usually Brownian motion and viscous drag. We discuss some applications and examples of such simulations. We review the theory and practical principles of simulation of optical tweezers, including the choice of method of calculation of optical force, numerical solution of the equations of motion of the particle, and finish with a discussion of a range of open problems.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
