The precise and stable working of quantum gates in quantum computers is essential for any quantum computations. We define a machine learning-based framework for the unsupervised control of entangled quantum gates in gate-model quantum computers.
© 2018 The Author(s)
You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.
Contact your librarian or system administrator
Login to access OSA Member Subscription