Programming multi-level quantum gates in disordered computing reservoirs via machine learning and TensorFlow

Understand

Novel machine learning computational tools open new perspectives for quantum information systems.

• Here we adopt the open-source programming library TensorFlow to design multi-level quantum gates including a computing reservoir represented by a random unitary matrix.
• In optics, the reservoir is a disordered medium or a multi-modal fiber.
• We show that trainable operators at the input and the readout enable one to realize multi-level gates.