Observing Schr\"odinger's Cat with Artificial Intelligence: Emergent Classicality from Information Bottleneck

Understand

We train a generative language model on the randomized local measurement data collected from Schr\"odinger's cat quantum state.

• We demonstrate that the classical reality emerges in the language model due to the information bottleneck: although our training data contains the full quantum information about Schr\"odinger's cat, a weak language model can only learn to capture the classical reality of the cat from the data.
• We identify the quantum-classical boundary in terms of both the size of the quantum system and the information processing power of the classical intelligent agent, which indicates that a stronger agent can realize more quantum nature in the environmental noise surrounding the quantum system.
• Our approach opens up a new avenue for using the big data generated on noisy intermediate-scale quantum (NISQ) devices to train generative models for representation learning of quantum operators, which might be a step toward our ultimate goal of creating an artificial intelligence quantum physicist.