Seminar: AI for designing quantum experiments

Quantum experiments push the envelope of our understanding of fundamental concepts in quantum physics. The designing of modern quantum experiments is difficult and often clashes with human intuition. In my talk, I will address whether a reinforcement learning agent can propose novel quantum experiments. In our works, we answer this question by considering two examples. In the first example, a reinforcement learning agent learns to create high-dimensional entangled multiphoton states. In the second example, our reinforcement learning agent proposes new unintuitive experiments leading to higher Bell-CHSH inequality violations than the best currently known setups. Our findings highlight the possibility that machine learning could have a significantly more creative role in future quantum experiments.