Mathematical Aspects of the Feynman Path Integral
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Fluctuation-Dissipation Theorems from the Generalised Langevin Equation
Pram~na, Vol. 12, No. 4, April 1979, pp. 301-315, © printed in India Fluctuation-dissipation theorems from the generalised Langevin equation V BALAKRISHNAN Reactor Research Centre, Kalpakkam 603 102 MS received 15 November 1978 Abstract. The generalised Langevin equation (GLE), originally developed in the context of Brownian motion, yields a convenient representation for the mobility (generalised susceptibility) in terms of a frequency-dependent friction (memory func- tion). Kubo has shown how two deep consistency conditions, or fluctuation-dissi- pation theorems, follow from the GLE. The first relates the mobility to the velocity auto-correlation in equilibrium, as is also derivable from linear response theory. The second is a generalised Nyquist theorem, relating the memory function to the auto-correlation of the random force driving the velocity fluctuations. Certain subtle points in the proofs of these theorems have not been dealt with sufficiently carefully hitherto. We discuss the input information required to make the GLE description a complete one, and present concise, systematic proofs starting from the GLE. Care is taken to settle the points of ambiguity in the original version of these proofs. The causality condition imposed is clarified, and Felderhof's recent criticism of Kubo's derivation is commented upon. Finally, we demonstrate how the ' persistence ' of equilibrium can be used to evaluate easily the equilibrium auto-correlation of the ' driven ' variable (e.g., the velocity) from the transient solution of the corresponding stochastic equation. Keywords. Generalised Langevin equation; fluctuation-dissipation theorem; Brownian motion; correlations; mobility. 1. Introduction and discussion The generalised Langevin equation (GLE), originally developed in the context of Brownian motion, is an archetypal stochastic equation for the study of fluctuations and the approach to equilibrium in a variety of physical problems, ranging flora superionic conductors to mechanical relaxation. -
Solving Langevin Equation with the Stochastic Algebraically Correlated Noise
< ” "7 Solving Langevm Equation with the Stochastic Algebraically Noise M. and 3?. SmkowskF ^ AW-fORoZ ixwrdy CE^/DSM - .BP &%% Co^n CWez, Fmmef <m<i * AW»A(('e of NWear f&gaicg, P& - KmWw, fWaW GANIL F 96 IS a* ■11 Solving Langevin Equation with the Stochastic Algebraically Correlated Noise M. Ploszajczak* and T. Srokowski* t Grand Accelerateur National d’lons Lourds (GANIL), CEA/DSM - CNRS/IN2P3, BP 5027, F-14021 Caen Cedex, France and * Institute of Nuclear Physics, PL - 31-342 Krakow, Poland (May 17, 1996) Abstract Long time tail in the velocity and force autocorrelation function has been found recently in the molecular dynamics simulations of the peripheral collisions of ions. Simulation of those slowly decaying correlations in the stochastic transport theory, requires the development of new methods of generating stochastic force of arbitrarily long correlation times. In this paper we propose the Markovian process, the multidi mensional Kangaroo process, which permits describing various algebraic correlated stochastic processes. PACS numbers: 05.40.+j,05.45.+b,05.60+w Typeset using REVTgjX I. INTRODUCTION Dynamics of a classical many body system can be investigated using either the molecular dynamics approach or the kinetic rate equations. Both approaches can be generalized to incorporate also the Pauli exclusion principle for fermions. In the latter case, one considers for example different variants of the Boltzmann or Boltzmann-Langevin equations , whereas in the former case the ’quantal’ version of the molecular dynamics, the so called antisym metrized molecular dynamics [1] has been proposed. Chaotic properties of atomic nuclei have been discussed in the framework of the classical molecular dynamics (CMD). -
From Stochastic to Deterministic Langevin Equations
Abstract In the first part of this thesis we review the concept of stochastic Langevin equations. We state a simple example and explain its physical meaning in terms of Brownian motion. We then calculate the mean square displacement and the velocity autocorrelation function by solving this equation. These quantities are related to the diffusion coefficient in terms of the Green-Kuba formula, and will be defined properly. In the second part of the thesis we introduce a deterministic Langevin equation which models Brownian motion in terms of deterministic chaos, as suggested in recent research literature. We solve this equation by deriving a recurrence relation. We review Takagi function techniques of dynamical systems theory and apply them to this model. We also apply the correlation function technique. Finally, we derive, for the first time, an exact formula for the diffusion coefficient as a function of a control parameter for this model. Acknowledgement I would like to thank my supervisor Dr Rainer Klages for his excellent guid- ance and support throughout my thesis work. Special thanks to Dr Wolfram Just for some useful hints. i Contents 1 Introduction 1 2 Stochastic Langevin Equation 3 2.1 What is Brownian motion? . 3 2.2 The Langevin equation . 4 2.3 Calculation of the mean square displacement . 5 2.4 Derivation of the velocity autocorrelation function . 8 3 Deterministic Langevin Equation 10 3.1 Langevin equation revisited . 10 3.2 Solving the deterministic Langevin equation . 11 3.3 Calculation of the Diffusion Coefficient . 14 3.3.1 Correlation function technique . 15 3.3.2 Takagi function technique . -
Langevin Analysis for Time-Nonlocal Brownian Motion with Algebraic Memories and Delay Interactions
Eur. Phys. J. B (2016) 89: 87 DOI: 10.1140/epjb/e2016-70079-5 Langevin analysis for time-nonlocal Brownian motion with algebraic memories and delay interactions Matthew Chase, Tom J. McKetterick, Luca Giuggioli and V.M. Kenkre Eur. Phys. J. B (2016) 89: 87 DOI: 10.1140/epjb/e2016-70079-5 THE EUROPEAN PHYSICAL JOURNAL B Regular Article Langevin analysis for time-nonlocal Brownian motion with algebraic memories and delay interactions Matthew Chase1,a, Tom J. McKetterick2,3, Luca Giuggioli2,3,4, and V.M. Kenkre1 1 Consortium of the Americas for Interdisciplinary Science and the Department of Physics and Astronomy, University of New Mexico, Albuquerque − New Mexico 87131, USA 2 Bristol Centre for Complexity Sciences, University of Bristol, BS2 8BB, Bristol, UK 3 Department of Engineering Mathematics, University of Bristol, BS8 1UB, Bristol, UK 4 School of Biological Sciences, University of Bristol, BS8 1TQ, Bristol, UK Received 2 February 2016 / Received in final form 13 February 2016 Published online 6 April 2016 – c EDP Sciences, Societ`a Italiana di Fisica, Springer-Verlag 2016 Abstract. Starting from a Langevin equation with memory describing the attraction of a particle to a center, we investigate its transport and response properties corresponding to two special forms of the memory: one is algebraic, i.e., power-law, and the other involves a delay. We examine the properties of the Green function of the Langevin equation and encounter Mittag-Leffler and Lambert W-functions well-known in the literature. In the presence of white noise, we study two experimental situations, one involving the motional narrowing of spectral lines and the other the steady-state size of the particle under consideration. -
Field Theoretical Approaches to the Superconducting Phase Transition 3
October 23, 2018 7:17 WSPC/Trim Size: 9in x 6in for Review Volume rv-nogueira CHAPTER 1 Field Theoretical Approaches to the Superconducting Phase Transition Flavio S. Nogueira and Hagen Kleinert Institut f¨ur Theoretische Physik, Freie Universit¨at Berlin, Arnimallee 14, D-14195 Berlin, Germany E-mail: [email protected] Several field theoretical approaches to the superconducting phase tran- sition are discussed. Emphasis is given to theories of scaling and renor- malization group in the context of the Ginzburg-Landau theory and its variants. Also discussed is the duality approach, which allows to access the strong-coupling limit of the Ginzburg-Landau theory. 1. Introduction The Ginzburg-Landau (GL) phenomenological theory of superconductivity1 was proposed long before the famous Bardeen-Cooper-Schrieffer (BCS) microscopic theory of superconductivity.2 A few years after the BCS theory, Gorkov3 derived the GL theory from the BCS theory. This has been done by deriving an effective theory for the Cooper pairs valid in the neighborhood of the crit- ical temperature Tc. The modern derivation proceeds most elegantly via functional integrals, introducing a collective quantum field ∆(x,t) for the Cooper pairs via a Hubbard-Stratonovich transformation and integrating out the fermions in the partition function.4 Amazingly, the GL theory has kept great actuality up to now. It is arXiv:cond-mat/0303485v1 [cond-mat.supr-con] 22 Mar 2003 highly relevant for the description of high-Tc superconductors, even though the original BCS theory is inadequate to treat these materials. The success of the GL theory in the study of modern problems of superconductivity lies on its universal effective character, the details of the microscopic model being unimportant. -
Summing Over Trajectories of Stochastic Dynamics with Multiplicative Noise Ying Tang, Ruoshi Yuan, and Ping Ao
Summing over trajectories of stochastic dynamics with multiplicative noise Ying Tang, Ruoshi Yuan, and Ping Ao Citation: The Journal of Chemical Physics 141, 044125 (2014); doi: 10.1063/1.4890968 View online: http://dx.doi.org/10.1063/1.4890968 View Table of Contents: http://scitation.aip.org/content/aip/journal/jcp/141/4?ver=pdfcov Published by the AIP Publishing Articles you may be interested in Study of non-Markovian dynamics of a charged particle in presence of a magnetic field in a simple way J. Appl. Phys. 113, 124905 (2013); 10.1063/1.4798356 From Entropic Dynamics to Quantum Theory AIP Conf. Proc. 1193, 48 (2009); 10.1063/1.3275646 Stochastic dynamics of the scattering amplitude generating K -distributed noise J. Math. Phys. 44, 5212 (2003); 10.1063/1.1611264 Stochastic Resonance, Brownian Ratchets and the FokkerPlanck Equation AIP Conf. Proc. 665, 74 (2003); 10.1063/1.1584877 Stochastic modelling of nonlinear dynamical systems AIP Conf. Proc. 502, 313 (2000); 10.1063/1.1302402 This article is copyrighted as indicated in the article. Reuse of AIP content is subject to the terms at: http://scitation.aip.org/termsconditions. Downloaded to IP: 128.103.149.52 On: Wed, 17 Sep 2014 00:23:27 THE JOURNAL OF CHEMICAL PHYSICS 141, 044125 (2014) Summing over trajectories of stochastic dynamics with multiplicative noise Ying Tang,1,2,a) Ruoshi Yuan,3 and Ping Ao1,2,b) 1Department of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai 200240, China 2Key Laboratory of Systems Biomedicine Ministry of Education, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai 200240, China 3School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China (Received 21 April 2014; accepted 11 July 2014; published online 30 July 2014) We demonstrate that previous path integral formulations for the general stochastic interpre- tation generate incomplete results exemplified by the geometric Brownian motion. -
Supersymmetry in Stochastic Processes with Higher-Order Time
Supersymmetry in Stochastic Processes with Higher-Order Time Derivatives Hagen KLEINERT and Sergei V. SHABANOV ∗ † Institut f¨ur Theoretische Physik, Freie Universit¨at Berlin, Arnimallee 14, 14195 Berlin, Germany The supersymmetry implies QS = 0. A supersymmetric path integral representation is devel- The determinant (3) should not be confused with the oped for stochastic processes whose Langevin equation con- partition function for fermions governed by the Hamil- tains any number N of time derivatives, thus generalizing the tonian associated with the action (4). Instead of a Langevin equation with inertia studied by Kramers, where trace over external states it contains only the vacuum- N = 2. The supersymmetric action contains N fermion fields to-vacuum transition amplitude for the imaginary-time with first-order time derivatives whose path integral is evalu- ated for fermionless asymptotic states. interval under consideration. In the coherent state rep- resentation,c ¯t and ct are set to zero at the initial and 1. For a stochastic time-dependent variable xt obeying a first-order Langevin equation final times, respectively [2]. The path integral (2) can also be rewritten in a canon- ical Hamiltonian form by introducing an auxiliary Gaus- Lt[x] ≡ x˙ t + F (xt)= ηt, (1) sian integral over momentum variables pt, and replac- H 2 driven by a white noise ηt with hηti = 0, hηtηt′ i = δtt′ , ing Sb by Sb = dt (pt /2 − iptLt). The generator the correlation functions hx ··· x i can be derived from of supersymmetry for the canonical action is QH = t1 tn R a generating functional dt (ictδxt + ptδc¯t ). -
Solving the Generalized Langevin Equation with the Algebraically Correlated Noise
FR9800223 Solving the Generalized Langevin Equation with the Algebraically Correlated Noise T. Srokowskif and M. Ploszajczak* t Institute of Nuclear Physics, PL - 31-342 Krakow, Poland and * Grand Accelerateur National d'lons Lourds (GANIL), CEA/DSM - CNRS/IN2P3, BP 5027, F-14021 Caen Cedex, France GANIL P 97 33 Solving the Generalized Langevin Equation with the Algebraically Correlated Noise T. Srokowskif and M. Pioszajczak* t Institute of Nuclear Physics, PL - 31-342 Krakow, Poland and * Grand Accelerateur National d'lons Lourds (GANIL), CEA/DSM - CNRS/IN2P3, BP 5027, F-14021 Caen Cedex, France (October 1, 1997) Abstract a Langevin equation with the memory kernel/ The stochastic force possesses algebraic correlations, proportional to 1/t. The velocity autocorrelation function and related quantities characterizing transport properties^ are calculated at the assumption that the system is in the thermal equilibrium. Stochastic trajec- tories are simulated numerically, using the kangaroo process as a noise generator. Results of this simulation resemble Levy walks with divergent moments of the ve- locity distribution. WG1 tuusidtr motion of a Brownian particleYT)oth without any external potential and in the harmonic oscillator field, in particular the escape from a potential well. The results are compared with memory-free calculations for the Brownian particle. PACS numbers: 05.40.+j,05.60+w,02.50.Ey Typeset using REVTJEX I. INTRODUCTION Stochastic equations are often regarded as an effective description of a complicated high- dimensional system. Fast varying variables are substituted by a fluctuating force and the stochastic equation possesses only few degrees of freedom. However, such a procedure de- stroys in general the Markovian property of the original system [1]. -
PARTICLES and QUANTUM FIELDS Particles and Quantum Fields
PARTICLES AND QUANTUM FIELDS Particles and Quantum Fields Hagen Kleinert Professor of Physics Freie Universit¨at Berlin To my wife Annemarie and our son Hagen Michael II Preface This book arose from lectures I gave at the Freie Universit¨at Berlin over the past five decades. They were intended to prepare graduate students for their research in elementary-particle physics or in many-body theory of condensed matter. They should serve as a general introduction and a basis for understanding more advanced work on the subject. The theory of quantum fields presented in this book is mainly based on the perturbative approach. Elementary particles are introduced initially without any interactions. These are added later, and their strength is parametrized by some coupling constant g. The consequences are studied order by order in g, with the particles propagating forward from interaction to interaction. Such a treatment is clearly a gross simplification of what happens in nature, where even the existence of a free particle involves the full interaction from the very beginning. Nevertheless, this kind of procedure has been the basis of many successful theories. In all of them, there exist dominant freely propagating excitations or elementary particles at least in some experimentally accessible limit. The most prominent example is the theory of strongly interacting particles. There they are described as being composed of quarks held together by gluons which interact via a nonabelian gauge theory called quantum chromodynamics (QCD). In the limit of large energies, the particles behave like free point-like particles. This behavior was named parton-like by Richard Feynman. -
Arxiv:1612.08381V1 [Physics.Data-An]
100 years after Smoluchowski: stochastic processes in cell biology 1 2 D. Holcman∗ , and Z. Schuss Abstract 100 years after Smoluchowski introduces his approach to stochas- tic processes, they are now at the basis of mathematical and physical modeling in cellular biology: they are used for example to analyse and to extract features from large number (tens of thousands) of sin- gle molecular trajectories or to study the diffusive motion of molecules, proteins or receptors. Stochastic modeling is a new step in large data analysis that serves extracting cell biology concepts. We review here the Smoluchowski’s approach to stochastic processes and provide sev- eral applications for coarse-graining diffusion, studying polymer mod- els for understanding nuclear organization and finally, we discuss the stochastic jump dynamics of telomeres across cell division and stochas- tic gene regulation. Contents 1 Introduction 2 2 Construction of the Brownian trajectories 5 3 The velocity process and Langevin’s approach 7 3.1 Thevelocityproblem ....................... 7 3.2 Langevin’s solution of the velocity problem . 8 3.3 Thedisplacementprocess . 11 3.4 Reconciliation of Einstein’s and Langevin’s theories . 13 4 Smoluchowski’s limit of Langevin’s equation 14 arXiv:1612.08381v1 [physics.data-an] 26 Dec 2016 4.1 Numerical solution of the Smoluchowski equation . 15 4.2 The probability density of the Smoluchowski trajectories . 16 1Applied Mathematics and Computational Biology, Ecole Normale Sup´erieure, France and Churchill College, DAMTP Cambridge university, CB3 0DS, UK. ∗corresponding authors: [email protected] 2Department of Applied Mathematics, Tel-Aviv University, Tel-Aviv 69968, Israel. 1 4.3 Diffusion processes and diffusion models of large data sets . -
Building a Path-Integral Calculus: a Covariant Discretization Approach
Building a path-integral calculus: a covariant discretization approach Leticia F. Cugliandolo1, Vivien Lecomte2 and Fr´ed´eric van Wijland3 1 Laboratoire de Physique Th´eorique et Hautes Energies,´ Sorbonne Universit´e, UMR 7589 CNRS, 4 Place Jussieu Tour 13 5`eme´etage, 75252 Paris Cedex 05, France 2 Laboratoire Interdisciplinaire de Physique, Universit´eGrenoble Alpes, CNRS, LIPhy, F-38000 Grenoble, France 3 Laboratoire Mati`ereet Syst`emesComplexes, Universit´eParis Diderot, UMR 7057 CNRS, 10 rue Alice Domon et L´eonie Duquet, 75205 Paris Cedex 13, France E-mail: [email protected] [email protected] [email protected] Abstract. Path integrals are a central tool when it comes to describing quantum or thermal fluctuations of particles or fields. Their success dates back to Feynman who showed how to use them within the framework of quantum mechanics. Since then, path integrals have pervaded all areas of physics where fluctuation effects, quantum and/or thermal, are of paramount importance. Their appeal is based on the fact that one converts a problem formulated in terms of operators into one of sampling classical paths with a given weight. Path integrals are the mirror image of our conventional Riemann integrals, with functions replacing the real numbers one usually sums over. However, unlike conventional integrals, path integration suffers a serious drawback: in general, one cannot make non-linear changes of variables without committing an error of some sort. Thus, no path-integral based calculus is possible. Here we identify which are the deep mathematical reasons causing this important caveat, and we come up with cures for systems described by one degree of freedom. -
Uhlenbeck Process
Journal of Statistical Physics. Vol. 88, Nos. 3/4, 1997 Relativistic Ornstein-Uhlenbeck Process F. Debbasch,1 K. Mallick,2 and J. P. Rivet3 Received July 31, IV96; final November 13, IW6 We wish to shed some light on the problem of thermodynamic irreversibility in the relativistic framework. Therefore, we propose a relativistic stochastic process based on a generalization of the usual Ornstein-Uhlenbeck process: we intro- duce a relativistic version of the Langevin equation with a damping term which has the correct Galilean limit. We then deduce relativistic Kramers and Fokker- Planck equations and a fluctuation-dissipation theorem is derived from them. Finally, numerical simulations are used to check the equilibrium distribution in momentum space and to investigate dilTusion in physical space. KEY WORDS: Irreversibility; Einstein's relativity; Ornstein-Uhlenbeck process. 1. NOTATION In this article, the velocity of light will be denoted by c and the signature of the space time metric will be chosen to be ( + ,—,—,—). y and m are respectively the Lorentz factor and the mass of the particle undergoing stochastic motion. T will designate the absolute temperature, and k will stand for the Boltzmann constant. The second order modified Hankel func- tion'" will be denoted K2(x). As usual, Greek indices will run from 0 to 3 and Latin ones from 1 to 3, except in Appendix A, where Latin indices run from 1 to 6. 2. INTRODUCTION Modeling and understanding irreversible behavior has been one of the key jobs of Thermodynamics and Statistical Physics. The first approach 1 Laboratoire de Radioastronomie, E.N.S., F-75231 Paris Cedcx 05, France.