Training microwave pulses using quantum machine learning
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.
Email Address of Submitting Authorjames.email@example.com
ORCID of Submitting Authorhttps://orcid.org/0000-0001-7557-0671
Submitting Author's Institutionwichita state university
Submitting Author's Country
- United States of America