1. K-State home
  2. »Physics
  3. »News & Events
  4. »Colloquia
  5. »Spring 2019
  6. »Elizabeth Behrman

Department of Physics

Dr. Elizabeth Behrman
Wichita State Univeristy
Elizabeth Behrman
 
 Quantum machine learning for universal quantum computation

102 Cardwell Hall
May 6, 2019
4:15 p.m. 
   
  

We describe a systematic method, using machine learning, to "program" a large-scale quantum computer. Current algorithmic approaches use a "building block" strategy, in which a procedure is formulated as a sequence of steps from a universal set, e.g., a sequence of CNOT, Hadamard, and phase shift gates. This assumes we even have such an algorithm; often, we do not. Using quantum learning enables us to perform computations without knowing the algorithm, and without breaking it down into its building blocks, thus eliminating a difficult step and potentially increasing efficiency by simplifying and reducing unnecessary complexity. Moreover, we demonstrate robustness of quantum learning to noise and to decoherence.