Subsystem-based Approach to Scalable Quantum Optimal Control

TL;DR

This paper introduces a scalable subsystem-based quantum optimal control method that reduces computational complexity for large quantum systems, enabling efficient control of local quantum operations on intermediate-scale devices.

Contribution

A novel subsystem-based approach that reformulates quantum control problems as robust control tasks on subsystems, significantly reducing problem size and computational resources.

Findings

Successfully applied to a 12-spin system, reducing memory and time costs.

Enables efficient local quantum gate control on large systems.

Has implications for quantum engineering on near-term devices.

Abstract

The development of quantum control methods is an essential task for emerging quantum technologies. In general, the process of optimizing quantum controls scales very unfavorably in system size due to the exponential growth of the Hilbert space dimension. Here, I present a scalable subsystem-based method for quantum optimal control on a large quantum system. The basic idea is to cast the original problem as a robust control problem on subsystems with requirement of robustness in respect of inter-subsystem couplings, thus enabling a drastic reduction of problem size. The method is in particular suitable for target quantum operations that are local, e.g., elementary quantum gates. As an illustrative example, I employ it to tackle the demanding task of pulse searching on a 12-spin coupled system, achieving substantial reduction of memory and time costs. This work has significant implications for coherent quantum engineering on near-term intermediate-scale quantum devices.