Quantum Circuit Learning*

In recent years, machine learning has given some remarkable results, and the area called quantum machine learning (QML) is emerging fast. Google, IBM, and Intel are now demonstrating their quantum processors. However, a high depth quantum circuit used in most of suggested QML algorithms is still challenging in the near future. Classical-quantum hybrid algorithms with a low depth circuit, such as quantum variational eigensolver for quantum chemistry, are thought as candidates of applications of near term devices. Here we present a framework for classical-quantum hybrid machine learning with a low depth circuit, which we call quantum circuit learning (QCL).