Sample-Efficient Learning of Quantum Many-Body Systems

Learn about sample-efficient learning of quantum many-body systems in this 22-minute IEEE conference talk. Explore classical probability distributions, quantum state operators, and the motivation behind this research. Delve into the proof, dual optimization, strong convexity, and strong complexity bound. Gain insights from the summary and consider open questions in this field. Based on research by Anurag Anshu, Srinivasan Arunachalam, Tomotaka Kuwahara, and Mehdi Soleimanifar from prestigious institutions including the Institute for Quantum Computing, IBM Research, RIKEN Center, and MIT.