Reinforcement Learning to Disentangle Quantum States from Partial Observations

Explore a 46-minute lecture on applying reinforcement learning techniques to disentangle quantum states from partial observations. Delve into the intersection of machine learning and quantum physics as speaker Marin BUKOV from MPI PKS presents innovative approaches to tackle complex quantum systems. Gain insights into how reinforcement learning algorithms can be leveraged to extract meaningful information from limited quantum data, potentially revolutionizing our understanding and manipulation of quantum states.

Reinforcement Learning to Disentangle Quantum States from Partial Observations