Quantum Optimal Control Using MAGICARP: Combining Pontryagin's Maximum Principle and Gradient Ascent

TL;DR

MAGICARP is a novel quantum control algorithm that integrates Pontryagin's Maximum Principle with gradient ascent methods, improving the design of quantum gates under optimal constraints.

Contribution

The paper presents MAGICARP, a new shooting-based optimization method that combines PMP and gradient ascent for quantum control, offering improved performance and constraint handling.

Findings

MAGICARP effectively determines initial conditions for quantum gate synthesis.

It outperforms traditional GRAPE in certain constrained scenarios.

Numerical examples demonstrate its robustness and efficiency.

Abstract

We introduce the MAGICARP algorithm, a numerical optimization method for quantum optimal control problems that combines the structure provided by Pontryagin's Maximum Principle (PMP) and the robustness of gradient ascent techniques, such as GRAPE. MAGICARP is formulated as a "shooting technique", aiming to determine the appropriate initial adjoint momentum to realize a target quantum gate. This method naturally incorporates time and energy optimal constraints through a PMP-informed pulse structure. We demonstrate MAGICARP's effectiveness through illustrative numerical examples, comparing its performance to GRAPE and highlighting its advantages in specific scenarios.