Quantum Entanglement in Neural Network States

Machine learning has recently gained attention as a possible way to understand phase transitions in many-body quantum systems. A new entanglement analysis reveals crucial properties of the data structures that encode quantum states in a neural network, opening new inroads in applying machine learning to quantum many-body physics.

# Quantum many-body systems # Physics and Astronomy # Quantum Computing Algorithms and Architecture # Computer Science # Quantum Information and Cryptography

Dong-Ling Deng, Xiaopeng Li, S. Das Sarma (2017). "Quantum Entanglement in Neural Network States". Physical Review X. https://doi.org/10.1103/physrevx.7.021021