Optimizing Quantum Transport in 1D Open Quantum Systems

Optimizing quantum transport over noisy networks is important to the development of advanced energy and information processing technologies such as in quantum communication or in solar cells. In this project, we focus on transport of a single excitation in a one dimensional chain with long range couplings, and we aim to optimize the chain's energy profile towards high transport flux. The system's interaction with its environment is modeled through the Lindblad master equation, with fixed dephasing rates and temperatures. We compare the optimal chain design under infinite and finite temperature conditions. Utilizing Optax's optimistic gradient descent and JAX's automatic differentiation, the optimization of steady-state transport efficiency demonstrates quicker convergence when temperature is considered. As a case study, we test the optimization approach against complete simulations for a three-site chain. We show that in the local-site local-decoherence model (representing an infinite temperature bath), transport is insensitive to the position of the central level, when couplings beyond nearest neighbors are included. In contrast, at temperatures comparable to the system's energies, V and Λ type models optimize transport. I will also present results of ongoing work, focusing on optimization of longer networks, and will discuss challenges encountered with different gradient-based optimizers. I will conclude by discussing extensions to muti excitations and higher dimension networks.