Quantum field theory, statistical physics and other modern applications
著者
書誌事項
Quantum field theory, statistical physics and other modern applications
（Path integrals in physics, v. 2）
Institute of Physics Publishing, c2001
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注記
"Institute of Physics series in mathematical and computational physics"--On cover
Includes bibliographical references (p. 332-336) and index
内容説明・目次
内容説明
The path integral approach has proved extremely useful for the understanding of the most complex problems in quantum field theory, cosmology, and condensed matter physics. Path Integrals in Physics: Volume II, Quantum Field Theory, Statistical Physics and other Modern Applications covers the fundamentals of path integrals, both the Wiener and Feynman types, and their many applications in physics. The book deals with systems that have an infinite number of degrees of freedom. It discusses the general physical background and concepts of the path integral approach used, followed by a detailed presentation of the most typical and important applications as well as problems with either their solutions or hints how to solve them. Each chapter is self-contained and can be considered as an independent textbook. It provides a comprehensive, detailed, and systematic account of the subject suitable for both students and experienced researchers.
目次
Volume II: 3. Quantum Field Theory: the Path Integral Approach. Path integral formulation of the simplest quantum field theories. Path integral quantization of gauge field theories. Non-perturbative methods for the analysis of quantum field models in the path integral approach. Path integrals in the theory of gravitation, cosmology and string theory: advanced applications of path integrals. 4. Path Integrals in Statistical Physics. Basic concept of statistical physics. Field theory at non-zero temperature. Superfluidity, superconductivity, non-equilibrium statistical physics in the path integral formalism and stochastic quantization. Path integrals formalism and lattice systems. Supplements. Bibliography. Index
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