Garnet Chan: Simulating the Quantum World on a Classical Computer

source: GoogleTechTalks     2016年11月10日
A Google TechTalk, 10/6/16, presented by Garnet Chan
ABSTRACT: Quantum mechanics is the fundamental theory underlying all of chemistry, materials science, and the biological world, yet solving the equations appears to be an exponentially hard problem. Is there hope to simulate the quantum world using classical computers? I will discuss why simulating quantum mechanics is not usually as hard as it first appears, and give some examples of how modern day quantum mechanical calculations are changing our understanding of practical chemistry and materials science.

Speaker Bio:
Garnet Chan recently joined the Cal Tech faculty as the Bren Professor in Chemistry. Before that he was the A. Barton Hepburn Professor of Chemistry at Princeton University, where he was also a member of the physics faculty. Professor Chan received his PhD from the University of Cambridge in 2000. He was born in London and grew up in Hong Kong. Professor Chan's research lies at the interface of theoretical chemistry, condensed matter physics, and quantum information theory, and is concerned with quantum many-particle phenomena and the numerical methods to simulate them. Over the last decade, his group has contributed to and invented a variety of methods addressing different aspects of quantum simulations, ranging from the challenges of strong electron correlation, to treating many-particle problems in the condensed phase, to dynamical simulations of spectra and coupling between electron and nuclear degrees of freedom. Some of these methods include density matrix renormalization and tensor network algorithms for real materials, canonical transformation-based down-foldings, local quantum chemistry methods, quantum embeddings including dynamical mean-field theory and density matrix embedding theory, and new quantum Monte Carlo algorithms. The primary focus is on methodologies for problems which appear naively exponentially hard, but where an understanding of inherent physics, for example in terms of the entanglement structure, allows for calculations of polynomial cost.