Approximate Dynamics Lead to More Optimal Control: Efficient Exact Derivatives
Jesper Hasseriis Mohr Jensen, Frederik Skovbo M{\o}ller, Jens Jakob, S{\o}rensen, Jacob Friis Sherson

TL;DR
This paper demonstrates that using approximate propagators in quantum control optimization significantly reduces computational complexity while maintaining high fidelity, enabling efficient high-dimensional system control.
Contribution
It introduces a method to trade off dynamics approximation accuracy for computational efficiency in deriving exact control derivatives for quantum systems.
Findings
Approximate propagators lead to substantial reductions in derivative calculation complexity.
Optimized schemes achieve near machine precision fidelity.
Efficiency gains increase with system size, enabling high-dimensional quantum control.
Abstract
Accurate derivatives are important for efficiently locally traversing and converging in quantum optimization landscapes. By deriving analytically exact control derivatives (gradient and Hessian) for unitary control tasks, we show here that the computational feasibility of meeting this accuracy requirement depends on the choice of propagation scheme and problem representation. Even when exact propagation is sufficiently cheap it is, perhaps surprisingly, much more efficient to optimize the (appropriately) approximate propagators: approximations in the dynamics are traded off for significant complexity reductions in the exact derivative calculations. Importantly, past the initial analytical considerations, only standard numerical techniques are explicitly required with straightforward application to realistic systems. These results are numerically verified for two concrete problems of…
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