Robust Quantum Control using Hybrid Pulse Engineering

TL;DR

This paper introduces a hybrid quantum control algorithm combining gradient methods with simulated annealing, demonstrating improved robustness and convergence for designing noise-resilient quantum pulses in NMR systems.

Contribution

It presents a novel hybrid optimization algorithm that enhances convergence and robustness in quantum control design, including noise-resilient pulse construction.

Findings

Hybrid algorithm shows faster convergence.

Generated pulses are more robust against dephasing errors.

Effective in measuring local noise spectra in NMR.

Abstract

The development of efficient algorithms that generate robust quantum controls is crucial for the realization of quantum technologies. The commonly used gradient-based optimization algorithms are limited by their sensitivity to the initial guess, which affects their performance. Here we propose combining the gradient method with the simulated annealing technique to formulate a hybrid algorithm. Our numerical analysis confirms its superior convergence rate. Using the hybrid algorithm, we generate spin-selective $\pi$ pulses and employ them for experimental measurement of local noise-spectra in a three-qubit NMR system. Moreover, here we describe a general method to construct noise-resilient quantum controls by incorporating noisy fields within the optimization routine of the hybrid algorithm. On experimental comparison with similar sequences obtained from standard algorithms, we find remarkable robustness of the hybrid sequences against dephasing errors.