Training microwave pulses using quantum machine learning
Quantum Physics
2025-07-18 v1
Abstract
A gate sequence of single-qubit transformations may be condensed into a single microwave pulse that maps a qubit from an initialized state directly into the desired state of the composite transformation. Here, machine learning is used to learn the parameterized values for a single driving pulse associated with a transformation of three sequential gate operations on a qubit. This implies that future quantum circuits may contain roughly a third of the number of single-qubit operations performed, greatly reducing the problems of noise and decoherence. There is a potential for even greater condensation and efficiency using the methods of quantum machine learning.
Cite
@article{arxiv.2409.03861,
title = {Training microwave pulses using quantum machine learning},
author = {Jaden Nola and Uriah Sanchez and Anusha Krishna Murthy and Elizabeth Behrman and James Steck},
journal= {arXiv preprint arXiv:2409.03861},
year = {2025}
}