Efficient Discrete Feature Encoding for Variational Quantum Classifier

Understand

Recent days have witnessed significant interests in applying quantum-enhanced techniques for solving a variety of machine learning tasks.

• Variational methods that use quantum resources of imperfect quantum devices with the help of classical computing techniques are popular for supervised learning.
• Variational quantum classification (VQC) is one of such methods with possible quantum advantage in using quantum-enhanced features that are hard to compute by classical methods.
• Its performance depends on the mapping of classical features into a quantum-enhanced feature space.