Large-deviation analysis for counting statistics in mesoscopic transports

TL;DR

This paper introduces an efficient large-deviation approach based on a master equation to analyze both typical and rare trajectories in mesoscopic transport, revealing dynamical phase transitions and scale invariance.

Contribution

It develops a novel large-deviation analysis method for mesoscopic transport that captures complete trajectory information beyond traditional statistics.

Findings

Revealed inhomogeneous trajectory distributions in quantum dot transport.

Identified a scale invariance point in trajectory statistics.

Discovered a dynamical phase transition in double quantum dots.

Abstract

We present an efficient approach, based on a number-conditioned master equation, for large-deviation analysis in mesoscopic transports. Beyond the conventional full-counting-statistics study, the large-deviation approach encodes complete information of both the typical trajectories and the rare ones, in terms of revealing a continuous change of the dynamical phase in trajectory space. The approach is illustrated with two examples: (i) transport through a single quantum dot, where we reveal the inhomogeneous distribution of trajectories in general case and find a particular scale invariance point in trajectory statistics; and (ii) transport through a double dots, where we find a dynamical phase transition between two distinct phases induced by the Coulomb correlation and quantum interference.