Comparative Analysis of Control Strategies

TL;DR

This paper compares various quantum control strategies, including geometric, optimal, and iterative methods, focusing on their performance in controlling qubits and generating entanglement.

Contribution

It provides a systematic comparison of control modeling, problem formulation, and solution techniques in quantum systems, highlighting their relative effectiveness.

Findings

Optimal control methods outperform geometric control in certain tasks.

Iterative techniques show faster convergence for entanglement generation.

Gradient-based local optimization is effective for specific quantum control problems.

Abstract

Different ways of modelling quantum control systems, formulating control problems and solving the resulting problems are considered and compared. In particular, we compare the performance of geometric and optimal control, as well as iterative techniques for optimal control design versus local gradient optimization using a Lyapunov-type potential function for two problems of general interest: global control of qubits and entanglement generation in the form of Bell state preparation.