How to Train Your Gyro: Reinforcement Learning for Rotation Sensing with a Shaken Optical Lattice

As the complexity of the next generation of quantum sensors increases, it becomes more and more intriguing to consider a new paradigm in which the design and control of metrological devices is supported by machine learning approaches. In a demonstration of such a design philosophy, we apply reinforcement learning to engineer a shaken-lattice matter-wave gyroscope involving minimal human intuition. In fact, the machine is given no instructions as to how to construct the splitting, reflecting, and recombining components intrinsic to conventional interferometry.