OPTIC: A Practical Quantum Binary Classifier for Near-Term Quantum Computers

Tirthak Patel, Daniel Silver, Devesh Tiwari

Abstract: Quantum computers can theoretically speed up optimization workloads such as variational machine learning and classification workloads over classical computers. However, in practice, proposed variational algorithms have not been able to run on existing quantum computers for practical-scale problems owing to their error-prone hardware. We propose Optic, a framework to effectively execute quantum binary classification on real noisy intermediate-scale quantum (NISQ) computers.