Tsallis Entropy and the Vlasov-Poisson Equations
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On Escort Distributions, Q-Gaussians and Fisher Information Jean-François Bercher
On escort distributions, q-gaussians and Fisher information Jean-François Bercher To cite this version: Jean-François Bercher. On escort distributions, q-gaussians and Fisher information. 30th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, Jul 2010, Chamonix, France. pp.208-215, 10.1063/1.3573618. hal-00766571 HAL Id: hal-00766571 https://hal-upec-upem.archives-ouvertes.fr/hal-00766571 Submitted on 18 Dec 2012 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. On escort distributions, q-gaussians and Fisher information J.-F. Bercher Laboratoire d’Informatique Gaspard Monge, Université Paris-Est, ESIEE, 5 bd Descartes, 77454 Marne-la-Vallée Cedex 2, France Abstract. Escort distributions are a simple one parameter deformation of an original distribution p. In Tsallis extended thermostatistics, the escort-averages, defined with respect to an escort dis- tribution, have revealed useful in order to obtain analytical results and variational equations, with in particular the equilibrium distributions obtained as maxima of Rényi-Tsallis entropy subject to constraints in the form of a q-average. A central example is the q-gaussian, which is a generalization of the standard gaussian distribution. -
Lecture 7: Moments of the Boltzmann Equation
!"#$%&'()%"*#%*+,-./-*+01.2(.*3+456789* !"#$%&"'()'*+,"-$.'+/'0+1$2,3--4513.+6'78%39+-' Dr. Peter T. Gallagher Astrophysics Research Group Trinity College Dublin :2;$-$(01*%<*=,-./-*=0;"%/;"-* !"#$%#&!'()*%()#& +,)-"(./#012"(& 4,$50,671*)& 9*"5:%#))& 3*1*)& 87)21*)& ;<7#1*)& 3*%()5$&*=&9*"5:%#))& ;<7#1*)& +,)-"(&>7,?& 37"1/"(&& 3@4& >7,?$& >%/;"#.*%<*?%,#@/-""AB,-.%C*DE'-)%"* o Under certain assumptions not necessary to obtain actual distribution function if only interested in the macroscopic values. o Instead of solving Boltzmann or Vlasov equation for distribution function and integrating, can take integrals over collisional Boltzmann-Vlasov equation and solve for the quantities of interest. "f q "f & "f ) +v #$f + [E +(v % B)]# = ( + "t m "v ' "t *coll (7.1) o Called “taking the moments of the Boltzmann-Vlasov equation” . ! o Resulting equations known as the macroscopic transport equations, and form the foundation of plasma fluid theory. o Results in derivation of the equations of magnetohydrodynamics (MHD). F;$%#0A%$&;$*>%/;"#G*H%")"'2#1*DE'-)%"* o Lowest order moment obtained by integrating Eqn. 7.1: "f q "f ' "f * # dv + # v $%fdv + # [E +(v & B)]$ dv = # ) , dv "t m "v ( "t +coll The first term gives "f " "n o # dv = # fdv = (7.2) "t "t "t ! o Since v and r are independent, v is not effected by gradient operator: ! $ v " #fdv = # " $ vfdv o From before, the first order moment of distribution function is ! 1 u = " vf (r,v,t)dv n therefore, $ v " #fdv = # "(nu) (7.3) ! ! F;$%#0A%$&;$*>%/;"#G*H%")"'2#1*DE'-)%"* o For the third term, consider E and B separately. E term vanishes as #f # $ E " dv = $ "( fE)dv = $ fE "dS = 0 (7.4a) #v #v using Gauss’ Divergence Theorem in velocity space. -
The Vlasov-Poisson System and the Boltzmann Equation
DISCRETE AND CONTINUOUS Website: http://AIMsciences.org DYNAMICAL SYSTEMS Volume 8, Number 2, April 2002 pp. 361–380 AN INTRODUCTION TO KINETIC EQUATIONS: THE VLASOV-POISSON SYSTEM AND THE BOLTZMANN EQUATION JEAN DOLBEAULT Abstract. The purpose of kinetic equations is the description of dilute par- ticle gases at an intermediate scale between the microscopic scale and the hydrodynamical scale. By dilute gases, one has to understand a system with a large number of particles, for which a description of the position and of the velocity of each particle is irrelevant, but for which the decription cannot be reduced to the computation of an average velocity at any time t ∈ R and any d position x ∈ R : one wants to take into account more than one possible veloc- ity at each point, and the description has therefore to be done at the level of the phase space – at a statistical level – by a distribution function f(t, x, v) This course is intended to make an introductory review of the literature on kinetic equations. Only the most important ideas of the proofs will be given. The two main examples we shall use are the Vlasov-Poisson system and the Boltzmann equation in the whole space. 1. Introduction. 1.1. The distribution function. The main object of kinetic theory is the distri- bution function f(t, x, v) which is a nonnegative function depending on the time: t ∈ R, the position: x ∈ Rd, the velocity: v ∈ Rd or the impulsion ξ). A basic 1 d d requirement is that f(t, ., .) belongs to Lloc (R × R ) and from a physical point of view f(t, x, v) dxdv represents “the probability of finding particles in an element of volume dxdv, at time t, at the point (x, v) in the (one-particle) phase space”. -
Tsallis Statistics of the Magnetic Field in the Heliosheath Lf Burlaga,1 Af Vin
The Astrophysical Journal, 644:L83–L86, 2006 June 10 ᭧ 2006. The American Astronomical Society. All rights reserved. Printed in U.S.A. TSALLIS STATISTICS OF THE MAGNETIC FIELD IN THE HELIOSHEATH L. F. Burlaga,1 A. F. Vin˜ as,1 N. F. Ness,2 and M. H. Acun˜a3 Received 2006 March 27; accepted 2006 May 3; published 2006 May 25 ABSTRACT The spacecraft Voyager 1 crossed the termination shock on 2004 December 16 at a distance of 94 AU from the Sun, and it has been moving through the heliosheath toward the interstellar medium since then. The distributions of magnetic field strength B observed in the heliosheath are Gaussian over a wide range of scales, yet the measured profile appears to be filamentary with occasional large jumps in the magnetic field strengthB(t) . All of the probability distributions of changes in B,dBn { B(t ϩ t) Ϫ B(t) on scales t from 1 to 128 days, can be fit with the symmetric Tsallis distribution of nonextensive statistical mechanics. At scales ≥32 days, the distributions are Gaussian, but on scales from 1 through 16 days the probability distribution functions have non-Gaussian tails, suggesting that the inner heliosheath is not in statistical equilibrium on scales from 1 to 16 days. Subject headings: magnetic fields — solar wind — turbulence — waves 1. INTRODUCTION is expressed by the form of u in the distribution function. In The solar wind moves supersonically beyond a few solar Tsallis statistical mechanics, the probability that a system is in a state with energy u is proportional toexp (Ϫ u) . -
Statistical Mechanics of Nonequilibrium Processes Volume 1: Basic Concepts, Kinetic Theory
Dmitrii Zubarev Vladimir Morozov Gerd Röpke Statistical Mechanics of Nonequilibrium Processes Volume 1: Basic Concepts, Kinetic Theory Akademie Verlag Contents 1 Basic concepts of Statistical mechanics 11 1.1 Classical distribution functions 11 1.1.1 Distribution functions in phase space 11 1.1.2 Liouville's theorem 15 1.1.3 Classical Liouville equation 17 1.1.4 Time reversal in classical Statistical mechanics 20 1.2 Statistical Operators for quantum Systems 23 1.2.1 Pure quantum ensembles 24 1.2.2 Mixed quantum ensembles 27 1.2.3 Passage to the classical limit of the density matrix 29 1.2.4 Second quantization 34 1.2.5 Quantum Liouville equation 40 1.2.6 Time reversal in quantum Statistical mechanics 43 1.3 Entropy 48 1.3.1 Gibbs entropy 48 1.3.2 The Information entropy 54 1.3.3 Equilibrium Statistical ensembles 57 1.3.4 Extremal property of the microcanonical ensemble 59 1.3.5 Extremal property of the canonical ensemble 63 1.3.6 Extremal property of the grand canonical ensemble 66 1.3.7 Entropy and thermodynamic relations 68 1.3.8 Nernst's theorem 72 1.3.9 Equilibrium fluctuations of thermodynamic quantities 76 1.3.10 Equilibrium fluctuations of dynamical variables 79 Appendices to Chapter 1 84 1A Time-ordered evolution Operators 84 1B The maximum entropy for quantum ensembles 86 Problems to Chapter 1 87 8 Contents 2 Nonequilibrium Statistical ensembles 89 2.1 Relevant Statistical ensembles 90 2.1.1 Reduced description of nonequilibrium Systems 90 2.1.2 Relevant Statistical distributions 96 2.1.3 Entropy and thermodynamic relations in relevant ensembles . -
Arxiv:1605.02220V1 [Cond-Mat.Quant-Gas] 7 May 2016
Nonequilibrium Kinetics of One-Dimensional Bose Gases F. Baldovin1,2,3, A. Cappellaro1, E. Orlandini1,2,3, and L. Salasnich1,2,4 1Dipartimento di Fisica e Astronomia “Galileo Galilei”, Universit`adi Padova, Via Marzolo 8, 35122 Padova, Italy, 2CNISM, Unit`adi Ricerca di Padova, Via Marzolo 8, 35122 Padova, Italy, 3INFN, Sezione di Padova, Via Marzolo 8, 35122 Padova, Italy, 4INO-CNR, Sezione di Sesto Fiorentino, Via Nello Carrara, 1 - 50019 Sesto Fiorentino, Italy Abstract. We study cold dilute gases made of bosonic atoms, showing that in the mean-field one-dimensional regime they support stable out-of-equilibrium states. Starting from the 3D Boltzmann-Vlasov equation with contact interaction, we derive an effective 1D Landau-Vlasov equation under the condition of a strong transverse harmonic confinement. We investigate the existence of out-of- equilibrium states, obtaining stability criteria similar to those of classical plasmas. 1. Introduction Bose [1] and Fermi degeneracy [2] were achieved some years ago in experiments with ultracold alkali-metal atoms, based on laser-cooling and magneto-optical trapping. These experiments have opened the way to the investigation and manipulation of novel states of atomic matter, like the Bose-Einstein condensate [3] and the superfluid Fermi gas in the BCS-BEC crossover [4]. Simple but reliable theoretical tools for the study of these systems in the collisional regime are the hydrodynamic equations [3, 5]. Nevertheless, to correctly reproduce dynamical properties of atomic gases in the mean- field collisionless regime [6, 7], or in the crossover from collisionless to collisional regime [8], one needs the Boltzmann-Vlasov equation [9, 10, 11, 12]. -
Splitting Methods for Vlasov–Poisson and Vlasov–Maxwell Equations
University of Innsbruck Department of Mathematics Numerical Analysis Group PhD Thesis Splitting methods for Vlasov{Poisson and Vlasov{Maxwell equations Lukas Einkemmer Advisor: Dr. Alexander Ostermann Submitted to the Faculty of Mathematics, Computer Science and Physics of the University of Innsbruck in partial fulfillment of the requirements for the degree of Doctor of Philosophy (PhD). January 17, 2014 1 Contents 1 Introduction 3 2 The Vlasov equation 4 2.1 The Vlasov equation in relation to simplified models . 6 2.2 Dimensionless form . 7 3 State of the art 8 3.1 Particle approach . 9 3.2 Grid based discretization in phase space . 9 3.3 Splitting methods . 11 3.4 Full discretization . 13 4 Results & Publications 14 5 Future research 16 References 17 A Convergence analysis of Strang splitting for Vlasov-type equations 21 B Convergence analysis of a discontinuous Galerkin/Strang splitting approximation for the Vlasov{Poisson equations 39 C Exponential integrators on graphic processing units 62 D HPC research overview (book chapter) 70 2 1 Introduction A plasma is a highly ionized gas. That is, it describes a state of matter where the electrons dissociate from the much heavier ions. Usually the ionization is the result of a gas that has been heated to a sufficiently high temperature. This is the case for fusion plasmas, including those that exist in the center of the sun, as well as for artificially created fusion plasmas which are, for example, used in magnetic confinement fusion devices (Tokamaks, for ex- ample) or in inertial confinement fusion. However, astrophysical plasmas, for example, can exist at low temperatures, since in such configurations the plasma density is low. -
Arxiv:1707.03526V1 [Cond-Mat.Stat-Mech] 12 Jul 2017 Eq
Generalized Ensemble Theory with Non-extensive Statistics Ke-Ming Shen,∗ Ben-Wei Zhang,y and En-Ke Wang Key Laboratory of Quark & Lepton Physics (MOE) and Institute of Particle Physics, Central China Normal University, Wuhan 430079, China (Dated: October 17, 2018) The non-extensive canonical ensemble theory is reconsidered with the method of Lagrange multipliers by maximizing Tsallis entropy, with the constraint that the normalized term of P q Tsallis' q−average of physical quantities, the sum pj , is independent of the probability pi for Tsallis parameter q. The self-referential problem in the deduced probability and thermal quantities in non-extensive statistics is thus avoided, and thermodynamical relationships are obtained in a consistent and natural way. We also extend the study to the non-extensive grand canonical ensemble theory and obtain the q-deformed Bose-Einstein distribution as well as the q-deformed Fermi-Dirac distribution. The theory is further applied to the general- ized Planck law to demonstrate the distinct behaviors of the various generalized q-distribution functions discussed in literature. I. INTRODUCTION In the last thirty years the non-extensive statistical mechanics, based on Tsallis entropy [1,2] and the corresponding deformed exponential function, has been developed and attracted a lot of attentions with a large amount of applications in rather diversified fields [3]. Tsallis non- extensive statistical mechanics is a generalization of the common Boltzmann-Gibbs (BG) statistical PW mechanics by postulating a generalized entropy of the classical one, S = −k i=1 pi ln pi: W X q Sq = −k pi lnq pi ; (1) i=1 where k is a positive constant and denotes Boltzmann constant in BG statistical mechanics. -
Beyond Behavioural Economics
Beyond Behavioural Economics A Process Realist Perspective Mathematics of Behavioural Economics and Finance James Juniper November, 2015 Ultimate scientific explanation is attractive and important, but financial engineering cannot wait for full explanation. That is, it is legitimate to strive towards a second best: a “descriptive phenomenology” that is organized tightly enough to bring a degree of order and understanding. Benoit B. Mandelbrot (1997) Overview • Keynes on DM under uncertainty & role of conventions • Ontological considerations • Objective not just subjective • Applications: • Bounded sub-additivity (Tversky & Wakker) • Equivalent approach—fuzzy measure theory (approximation algebras) • Concept lattices and “framing” • Tsallis arithmetic: q-generalized binomial approximation […] civilization is a thin and precarious crust erected by the personality and will of a very few and only maintained by rules and conventions skillfully put across and guilefully preserved” (Keynes, X: 447) The “love of money as a possession” is a “somewhat disgusting morbidity, one of those semi-criminal, semi-pathological propensities which one hands over with a shudder to the specialists in mental disease (IX: 329) For we shall enquire more curiously than is safe today into the true character of this ‘purposiveness’ with which in varying degrees Nature has endowed almost all of us. For purposiveness means that we are more concerned with the remote future results of our actions than with their own quality or their immediate effects on the environment. The ‘purposive’ man is always trying to secure a spurious and delusive immortality for his acts by pushing his interest in them forward into time. He does not love his cat, but his cat’s kittens; nor, in truth, the kittens, but only the kittens’ kittens, and so on forward to the end of catdom. -
Fractal Structure and Non-Extensive Statistics
entropy Article Fractal Structure and Non-Extensive Statistics Airton Deppman 1,* ID , Tobias Frederico 2, Eugenio Megías 3,4 and Debora P. Menezes 5 1 Instituto de Física, Universidade de São Paulo, Rua do Matão Travessa R Nr.187, Cidade Universitária, CEP 05508-090 São Paulo, Brazil 2 Instituto Tecnológico da Aeronáutica, 12228-900 São José dos Campos, Brazil; [email protected] 3 Departamento de Física Teórica, Universidad del País Vasco UPV/EHU, Apartado 644, 48080 Bilbao, Spain; [email protected] 4 Departamento de Física Atómica, Molecular y Nuclear and Instituto Carlos I de Física Teórica y Computacional, Universidad de Granada, Avenida de Fuente Nueva s/n, 18071 Granada, Spain 5 Departamento de Física, CFM, Universidade Federal de Santa Catarina, CP 476, CEP 88040-900 Florianópolis, Brazil; [email protected] * Correspondence: [email protected] Received: 27 June 2018; Accepted: 19 August 2018; Published: 24 August 2018 Abstract: The role played by non-extensive thermodynamics in physical systems has been under intense debate for the last decades. With many applications in several areas, the Tsallis statistics have been discussed in detail in many works and triggered an interesting discussion on the most deep meaning of entropy and its role in complex systems. Some possible mechanisms that could give rise to non-extensive statistics have been formulated over the last several years, in particular a fractal structure in thermodynamic functions was recently proposed as a possible origin for non-extensive statistics in physical systems. In the present work, we investigate the properties of such fractal thermodynamical system and propose a diagrammatic method for calculations of relevant quantities related to such a system. -
The Relativistic Vlasov Equation with Current and Charge Density Given by by Alec Johnson, January 2011 X X J = Qpvpδxp Σ = Qpδxp I
1 The Relativistic Vlasov Equation with current and charge density given by by Alec Johnson, January 2011 X X J = qpvpδxp σ = qpδxp I. Recitation of basic electrodynamics p p X δxp X δxp = q p ; = q γ ; A. Classical electrodynamics p p γ p p γ p p p p Classical electrodynamics is governed by Newton's sec- here p (i.e. γ v ) is the proper velocity, where γ is the ond law (for particle motion), p p p p rate at which time t elapses with respect to the proper time τ of a clock moving with particle p. Dropping the particle mpdtvp = Fp; vp := dtxp; p index, (where p is particle index, t is time, mp is particle mass, γ := d t; and xp(t) is particle position, and Fp(t) is the force on the τ particle), the Lorentz force law, p := dτ x = (dτ t)dtx = γv: Fp = qp (E + v × B) A concrete expression relating γ to (proper) velocity is (where E(t; x) = electric field, B(t; x) = magnetic field, and qp is particle charge), and Maxwell's equations, γ2 = 1 + (p=c)2; i.e. (dividing by γ2), −2 2 @tB + r × E = 0; r · B = 0; 1 = γ + (v=c) ; i.e. (solving for γ), 2 −1=2 @tE − c r × B = −J/, r · E = σ/, γ = 1 − (v=c)2 : with current and charge density given by II. Vlasov equation X X J := qpvpδxp ; σ := qpδxp ; The Vlasov equation asserts that particles are conserved p p in phase space and that the only force acting on particles is the electromagnetic force. -
Thermodynamics from First Principles: Correlations and Nonextensivity
Thermodynamics from first principles: correlations and nonextensivity S. N. Saadatmand,1, ∗ Tim Gould,2 E. G. Cavalcanti,3 and J. A. Vaccaro1 1Centre for Quantum Dynamics, Griffith University, Nathan, QLD 4111, Australia. 2Qld Micro- and Nanotechnology Centre, Griffith University, Nathan, QLD 4111, Australia. 3Centre for Quantum Dynamics, Griffith University, Gold Coast, QLD 4222, Australia. (Dated: March 17, 2020) The standard formulation of thermostatistics, being based on the Boltzmann-Gibbs distribution and logarithmic Shannon entropy, describes idealized uncorrelated systems with extensive energies and short-range interactions. In this letter, we use the fundamental principles of ergodicity (via Liouville's theorem), the self-similarity of correlations, and the existence of the thermodynamic limit to derive generalized forms of the equilibrium distribution for long-range-interacting systems. Significantly, our formalism provides a justification for the well-studied nonextensive thermostatistics characterized by the Tsallis distribution, which it includes as a special case. We also give the complementary maximum entropy derivation of the same distributions by constrained maximization of the Boltzmann-Gibbs-Shannon entropy. The consistency between the ergodic and maximum entropy approaches clarifies the use of the latter in the study of correlations and nonextensive thermodynamics. Introduction. The ability to describe the statistical tion [30] or the structure of the microstates [27]. Another state of a macroscopic system is central to many ar- widely-used approach is to generalize the MaxEnt prin- eas of physics [1{4]. In thermostatistics, the statistical ciple to apply to a different entropy functional in place of BGS state of a system of N particles in equilibrium is de- S (fwzg).