Quantum Field Theory: A quantum computation approach

February 15, 2021
book cover Yannik Meurice uiowa
Yannick Meurice
ISBN: 
Online ISBN: 978-0-7503-2187-7 • Print ISBN: 978-0-7503-2185-3

From the IOPscience website:

This book introduces quantum field theory models from a classical point of view. Practical applications are discussed, along with recent progress for quantum computations and quantum simulations experiments. New developments concerning discrete aspects of continuous symmetries and topological solutions in tensorial formulations of gauge theories are also reported.

Quantum Field Theory: A quantum computation approach requires no prior knowledge beyond undergraduate quantum mechanics and classical electrodynamics. With exercises involving Mathematica and Python with solutions provided, the book is an ideal guide for graduate students and researchers in high-energy, condensed matter and atomic physics.

Key Features

  • Introduces models from a symmetry point of view at the classical level
  • Includes the path-integral formulation used as the main quantization method
  • The quantum models are defined on space–time lattices with emphasis on the time continuum limit
  • Discrete tensor formulations are introduced from scratch
  • Provides quantum computations that require practical setups and approximations

Yannick Meurice is a professor in the Department of Physics and Astronomy at the University of Iowa. He obtained his PhD at U. C. Louvain-la-Neuve in 1985 under the supervision of Jacques Weyers and Gabriele Veneziano. He was a postdoc at CERN and Argonne National Laboratory and a visiting professor at CINVESTAV in Mexico City. He joined the faculty of the University of Iowa in 1990. His current work includes lattice gauge theory, tensor renormalization group methods, near conformal gauge theories, critical machine learning, quantum simulations with cold atoms and quantum computing. He is the PI of a multi-institutional DOE HEP QuantISED consortium that includes Boston University, Brookhaven National Laboratory, Massachusetts Institute of Technology, Michigan State University, Syracuse University, University of Maryland-College Park, and the University of California-Santa Barbara.