Speaker: Anurag Anshu, Assistant Professor of Computer Science at Harvard John A. Paulson School Of Engineering And Applied Sciences

Abstract : In recent years, there has been a surge of research on the learnability of quantum states that emerge from physically motivated settings. Prominent examples include Gibbs states, shallow quantum circuits, and tensor network states. This talk will provide a survey of these developments, emphasizing how efficient algorithms are intrinsically linked to the fundamental structures of these quantum states. A key theme in these results is the role of locality, which necessitates the use of experiment-friendly measurements that act jointly on only a few qubits. We will also discuss the major challenges that remain, particularly in the quest for optimal algorithms. The talk will assume a very mild background in quantum computing and aim to provide a broadly accessible view.