Robustness of Controlled Quantum Dynamics

TL;DR

This paper develops theoretical tools and efficient methods to analyze the robustness of controlled quantum dynamics, accounting for uncertainties in control fields and system parameters, crucial for reliable quantum control applications.

Contribution

It introduces a comprehensive theoretical framework and analytical expressions for robustness analysis, highlighting the existence of more resilient control pathways in quantum systems.

Findings

Robust control pathways are less affected by uncertainties.

Analytical expressions enable efficient robustness evaluation.

Certain pathways maintain high transition probabilities despite uncertainties.

Abstract

Control of multi-level quantum systems is sensitive to implementation errors in the control field and uncertainties associated with system Hamiltonian parameters. A small variation in the control field spectrum or the system Hamiltonian can cause an otherwise optimal field to deviate from controlling desired quantum state transitions and reaching a particular objective. An accurate analysis of robustness is thus essential in understanding and achieving model-based quantum control, such as in control of chemical reactions based on ab initio or experimental estimates of the molecular Hamiltonian. In this paper, theoretical foundations for quantum control robustness analysis are presented from both a distributional perspective - in terms of moments of the transition amplitude, interferences, and transition probability - and a worst-case perspective. Based on this theory, analytical expressions and a computationally efficient method for determining the robustness of coherently controlled quantum dynamics are derived. The robustness analysis reveals that there generally exists a set of control pathways that are more resistant to destructive interferences in the presence of control field and system parameter uncertainty. These robust pathways interfere and combine to yield a relatively accurate transition amplitude and high transition probability when uncertainty is present.