Large deviations of current for the symmetric simple exclusion process on a semi-infinite line, and on an infinite line with a slow bond
Kapil Sharma, Soumyabrata Saha, Sandeep Jangid, Tridib Sadhu
TL;DR
The paper derives the full counting statistics for current in the semi-infinite symmetric simple exclusion process using macroscopic fluctuation theory, revealing an exact semi-infinite SCGF μ_si(λ,ρ_a,ρ_b) obtained via a mapping to the infinite-line problem and symmetry of the MFT equations. The result unifies finite and infinite geometry insights and is verified by cloning simulations, while enabling exact results for related problems: infinite-line with a defect bond, fast single-site injection, and tracer survival with absorbing boundaries. The approach highlights the power of MFT in solving inhomogeneous transport problems and yields practical benchmarks for non-equilibrium fluctuations. The work also links to kinetically constrained models and spin dynamics, predicting stretched-exponential relaxation and offering a framework for extensions to quenched initial states and higher dimensions.
Abstract
Two influential exact results in classical one-dimensional diffusive transport are about current statistics for the symmetric simple exclusion process: one in the stationary state on a finite line coupled with two unequal reservoirs at the boundaries, and the other in the non-stationary state on an infinite line. We present the corresponding result for the intermediate geometry of a semi-infinite line coupled with a single reservoir. This result is obtained using the fluctuating hydrodynamics approach of macroscopic fluctuation theory and confirmed by rare event simulations using a cloning algorithm. We apply our exact result for solving several related challenging problems, namely, the full counting statistics in presence of a defect bond, exclusion process with localized injection, survival of a tagged particle in presence of an absorbing boundary, and the stretched exponential decay in a kinetically constrained model.
