Improving the dynamics of quantum sensors with reinforcement learning

Understand

Recently proposed quantum-chaotic sensors achieve quantum enhancements in measurement precision by applying nonlinear control pulses to the dynamics of the quantum sensor while using classical initial states that are easy to prepare.

• Here, we use the cross-entropy method of reinforcement learning to optimize the strength and position of control pulses.
• Compared to the quantum-chaotic sensors with periodic control pulses in the presence of superradiant damping, we find that decoherence can be fought even better and measurement precision can be enhanced further by optimizing the control.
• In some examples, we find enhancements in sensitivity by more than an order of magnitude.