Learning Shallow Quantum Circuits and Quantum States in Polynomial Time

Explore polynomial time algorithms for learning constant depth quantum circuits and quantum states in this lecture by Yunchao Liu from UC Berkeley. Discover efficient techniques to reconstruct quantum systems with low circuit complexity using local observables. Gain insights into approximating unknown constant depth quantum circuits on finite-dimensional lattices and learning to prepare quantum states generated by such circuits. Delve into the extension of these algorithms to polylog(n) depth circuits with quasi-polynomial run-time. Grasp key concepts through simple and accessible explanations, based on recent research in arxiv 2401.10095 and upcoming work with Zeph Landau.

Learning Shallow Quantum Circuits and Quantum States Prepared by Shallow Circuits in Polynomial Time