Quantum transport through a finite network is one of the fundamental processes in both natural and engineering systems. Understanding factors contributing to high-efficiency transport is crucial for transport theory and experimental design. In this study, how configurations of the central system and environmental coupling affect transport efficiency were explored in the context of the Fenna–Matthews–Olson (FMO) complex. The high-efficiency transport in this light harvesting complex has once been explained by quantum coherence, but the exact mechanisms have not been well understood. Motivated by this problem, the relation between network configurations and two bath interactions, Holstein and Peierls couplings, were explored in the limit of fast transport. Two optimization algorithms, Bayesian optimization (BO) and covariance matrix adaptation evolution strategy (CMA-ES) were adapted to propose the optimal design principles. Results showed that Holstein and Peierls coupling affected transport dynamics differently. While Holstein couplings may enhance the efficiency of transport for suboptimal configurations, bare optimal configurations are always more efficient than optimal configurations with Holstein couplings. For Peierls coupling, optimal configurations with Peierls couplings have similar efficiency with the bare optimal configurations when the system size is larger than 7 sites.
This repo contains source codes for quantum transport simulation and the optimization algorithms.