Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Oxford University Press eBooks

Path integral methods

太郎 柏, 義郎 大貫, Masuo Suzuki

Published Jan 1, 1997• 47 citations
OpenAlex

Abstract

  1. Path integral representation 2. Perturbation theory and the WKB approximation 3. Generalization 4. Application to field theory 5. Quantum Monte Carlo Method 6. Algebraic generalization 7. Problems in solid-state physics

Related papers

Path Integrals in Quantum Physics

Rosenfelder, R.

These lectures are intended for graduate students who want to acquire a working knowledge of path integral methods in a wide variety of fields in physics. In general the presentation is elementary and path integrals are developed in the usual heuristic, non-mathematical way for application in many diverse problems in quantum physics. Three main parts deal with path integrals in non-relativistic quantum mechanics, many-body physics and field theory and contain standard examples (quadratic Lagrangians, tunneling, description of bosons and fermions, quantization of gauge theories etc.) as well as specialized topics (scattering, dissipative systems, spin \& color in the path integral, lattice methods etc.). In each part simple Fortran programs which can be run on a PC, illustrate the numerical evaluation of (Euclidean) path integrals by Monte-Carlo or variational methods. Also included are the set of problems which accompanied the lectures and their solutions.

arXiv:1209.1315•Sep 6, 2012•3 citations

Path Integral Methods and Their Applications

Dinkar C. Khandekar, S. V. Lawande, K.V. Bhagwat

Concepts of Lagrangian and Hamiltonian path integrals Wiener integrals and Brownian motion representation of the statistical mechanical density matrix as a path integral propagators for local and non-local quadratic actions path integrals in polar and curvilinear coordinates and group manifolds local and global time transformation techniques approximation and numerical methods of evaluating path integrals and their applications to polaron bi polaron spectrum of disordered systems path integrals with topological constraints and their applications

WORLD SCIENTIFIC eBooks•Apr 1, 1993•124 citations

Quantum Monte Carlo Method

Tarō Kashiwa, Yoshio Ohnuki, Masuo Suzuki

Abstract The path integral discussed in the preceding chapters can be exactly calculated only in a few restricted systems such as harmonic oscillators. The WKB method and perturbational expansions based on the above path integral method are in fact applicable to systems close to classical ones and weakly interacting systems, respectively. However, in order to study interesting phenomena such as high Tc superconductivity, we have to treat strongly correlated systems in which the quantum effect plays an important role. It is effective in these systems to extract some physically crucial contributions numerically. This will be possible if we use the quantum Monte Carlo method. Although there are many different types of quantum Monte Carlo methods, we explain here mainly the quantum statistical Monte Carlo method based on a Trotter-like formula and on the important sampling method applied to transformed classical systems.

•Jul 3, 1997•1 citation

Path integrals and their applications in quantum, statistical and solid state physics

Solid State Communications•Apr 1, 1977•68 citations

The Path Integral approach to Quantum Mechanics Lecture Notes for Quantum Mechanics IV

Riccardo Rattazzi A

•Jan 1, 2009•6 citations

Time correlation functions for quantum systems: the case of harmonic oscillators

Vladislav Efremkin, Jean‐Louis Barrat, Stefano Mossa +1 more

The quantum harmonic oscillator represents the most common fundamental building block to compute thermal properties of virtually any dielectric crystalline material at low temperatures in terms of phonons, extended further to cases with anharmonic couplings, or even disordered solids. In general, Path Integral Monte Carlo (PIMC) methods provide a powerful numerical tool to stochastically determine thermodynamic quantities without systematic bias, not relying on perturbative schemes. Addressing transport properties, for instance the calculation of thermal conductivity from PIMC, however, has turned out to be substantially more difficult. Although correlation functions of current operators can be determined by PIMC in the form of analytic continuation on the imaginary time axis, Bayesian methods are usually employed for the numerical inversion back to real-time response functions. This task not only relies strongly on the accuracy of the PIMC data, but also introduces noticeable dependence on the underlying model used for the inversion problem. Here, we address both difficulties with great care. In particular, we first devise improved estimators for current correlations which substantially reduce the variance of the PIMC data. Next, we provide a neat statistical approach to the inversion problem, blending into a fresh workflow the classical stochastic maximum entropy method together with more recent notions borrowed from statistical learning theory. We test our ideas on a single harmonic oscillator and a collection of oscillators with a continuous distribution of frequencies, establishing solid grounds for an unbiased, fully quantum mechanical calculation of transport properties in solids.

•May 20, 2021•0 citations
These lectures are intended for graduate students who want to acquire a working knowledge of path integral methods in a wide variety of fields in physics. In general the presentation is elementary and path integrals are developed in the usual heuristic, non-mathematical way for application in many diverse problems in quantum physics. Three main parts deal with path integrals in non-relativistic quantum mechanics, many-body physics and field theory and contain standard examples (quadratic Lagrangians, tunneling, description of bosons and fermions, quantization of gauge theories etc.) as well as specialized topics (scattering, dissipative systems, spin \& color in the path integral, lattice methods etc.). In each part simple Fortran programs which can be run on a PC, illustrate the numerical evaluation of (Euclidean) path integrals by Monte-Carlo or variational methods. Also included are the set of problems which accompanied the lectures and their solutions.
Concepts of Lagrangian and Hamiltonian path integrals Wiener integrals and Brownian motion representation of the statistical mechanical density matrix as a path integral propagators for local and non-local quadratic actions path integrals in polar and curvilinear coordinates and group manifolds local and global time transformation techniques approximation and numerical methods of evaluating path integrals and their applications to polaron bi polaron spectrum of disordered systems path integrals with topological constraints and their applications
Abstract The path integral discussed in the preceding chapters can be exactly calculated only in a few restricted systems such as harmonic oscillators. The WKB method and perturbational expansions based on the above path integral method are in fact applicable to systems close to classical ones and weakly interacting systems, respectively. However, in order to study interesting phenomena such as high Tc superconductivity, we have to treat strongly correlated systems in which the quantum effect plays an important role. It is effective in these systems to extract some physically crucial contributions numerically. This will be possible if we use the quantum Monte Carlo method. Although there are many different types of quantum Monte Carlo methods, we explain here mainly the quantum statistical Monte Carlo method based on a Trotter-like formula and on the important sampling method applied to transformed classical systems.
The quantum harmonic oscillator represents the most common fundamental building block to compute thermal properties of virtually any dielectric crystalline material at low temperatures in terms of phonons, extended further to cases with anharmonic couplings, or even disordered solids. In general, Path Integral Monte Carlo (PIMC) methods provide a powerful numerical tool to stochastically determine thermodynamic quantities without systematic bias, not relying on perturbative schemes. Addressing transport properties, for instance the calculation of thermal conductivity from PIMC, however, has turned out to be substantially more difficult. Although correlation functions of current operators can be determined by PIMC in the form of analytic continuation on the imaginary time axis, Bayesian methods are usually employed for the numerical inversion back to real-time response functions. This task not only relies strongly on the accuracy of the PIMC data, but also introduces noticeable dependence on the underlying model used for the inversion problem. Here, we address both difficulties with great care. In particular, we first devise improved estimators for current correlations which substantially reduce the variance of the PIMC data. Next, we provide a neat statistical approach to the inversion problem, blending into a fresh workflow the classical stochastic maximum entropy method together with more recent notions borrowed from statistical learning theory. We test our ideas on a single harmonic oscillator and a collection of oscillators with a continuous distribution of frequencies, establishing solid grounds for an unbiased, fully quantum mechanical calculation of transport properties in solids.