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Training microwave pulses using quantum machine learning
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  • jaden nola ,
  • Uriah Sanchez ,
  • Elizabeth Behrman ,
  • James Steck
jaden nola
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Uriah Sanchez
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Elizabeth Behrman
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James Steck
wichita state university

Corresponding Author:[email protected]

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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.