Speaker
Barry Sanders
(University of Calgary)
Description
Control systems are vital in engineering, and machine learning is transforming data science; however, their basic constructs are expressed in terms of classical physics, which impedes generalizing to quantum control and quantum machine learning in a consistent way. We incorporate classical and quantum control and learning and their dependencies into a single conceptual framework. Then we discuss inconsistencies between current definitions of quantum control and quantum learning vs their descriptions achieved by generalizing classical versions using our framework. We illustrate our framework in the context of quantum-enhanced interferometric-phase estimation, which incorporates both control and machine learning.
Author
Barry Sanders
(University of Calgary)
