A Classical Machine Learning Algorithm Goes Quantum

In recent years, computer scientists have used machine learning algorithms known as generative adversarial networks (GANs) to manipulate data to startling effect. Applied to graphics, GANs can open closed eyes in photos and create forged videos of politicians speaking. Now, Seth Lloyd of the Massachusetts Institute of Technology, Cambridge, and Christian Weedbrook of the Canadian startup Xanadu have theoretically proven that the algorithm can be applied to quantum data sets. Similar to classical GANs, quantum GANs, or QGANs, could be used to generate realistic-looking quantum data on quantum computers.