Quantum Algorithms for Eigenvalue Problems - Lin Lin скачать в хорошем качестве

Quantum Algorithms for Eigenvalue Problems - Lin Lin

Lin Lin, the 2011 Alvarez Fellow in Computing Sciences at Berkeley Lab, is now an associate professor in the Department of Mathematics at UC Berkeley. He shared some of his most recent work in this talk on September 20, 2022. Berkeley Lab's Luis W. Alvarez Fellowship in Computing Sciences offers upcoming or recent Ph.D.'s the opportunity to work on some of the most important research challenges in computing sciences at a national lab synonymous with scientific excellence. The Alvarez Seminar Series features current and past Alvarez Fellows talking about their research and career paths. To learn more about the series, visit https://go.lbl.gov/alvarez-seminars. ABSTRACT: The problem of finding the smallest eigenvalue of a Hermitian matrix (also called the ground state energy) has wide applications in quantum physics, quantum chemistry, materials science etc. Lin Lin discusses two classes of quantum algorithms for solving such eigenvalue problems with near-optimal query complexities: those suitable for full-scale fault-tolerant quantum computers, and those suitable for early fault-tolerant quantum computers.