Central limit theorem and large deviations for run and tumble particles on a lattice
Bart van Gisbergen, Frank Redig

TL;DR
This paper analyzes run and tumble particles on a lattice, deriving explicit formulas for their diffusion and large deviation properties in both discrete and continuum models, including effects of external fields and higher dimensions.
Contribution
It provides explicit calculations of the large deviation free energy and diffusion constants for run and tumble particles on lattices and extends the analysis to higher dimensions with a variational formula.
Findings
Explicit formulas for diffusion constants and large deviation free energy.
Large deviation free energy in continuum models with external fields.
Generalization to higher dimensions with eigenvalue-based computation.
Abstract
We study run and tumble particles on the one-dimensional lattice . We explicitly compute the Fourier-Laplace transform of the position of the particle and as a consequence obtain explicit expressions for the diffusion constant and the large deviation free energy function. We also do the same computations in a corresponding continuum model. In the latter, when adding an external field, we can explicitly compute the large deviation free energy, and the deviation from the Einstein relation due to activity. Finally, we generalize the model to the -dimensional lattice , with an arbitrary finite set of velocities, and show that the large deviation free energy for the position of the particle can be computed via the largest eigenvalue of a matrix of Schr\"{o}dinger operator form, for which we can derive an explicit variational formula via occupation time large…
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.
Taxonomy
TopicsMicro and Nano Robotics · Advanced Thermodynamics and Statistical Mechanics · Stochastic processes and statistical mechanics
