Ludwig Boltzmann, Transport Equation and the Second
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James Clerk Maxwell
James Clerk Maxwell JAMES CLERK MAXWELL Perspectives on his Life and Work Edited by raymond flood mark mccartney and andrew whitaker 3 3 Great Clarendon Street, Oxford, OX2 6DP, United Kingdom Oxford University Press is a department of the University of Oxford. It furthers the University’s objective of excellence in research, scholarship, and education by publishing worldwide. Oxford is a registered trade mark of Oxford University Press in the UK and in certain other countries c Oxford University Press 2014 The moral rights of the authors have been asserted First Edition published in 2014 Impression: 1 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, without the prior permission in writing of Oxford University Press, or as expressly permitted by law, by licence or under terms agreed with the appropriate reprographics rights organization. Enquiries concerning reproduction outside the scope of the above should be sent to the Rights Department, Oxford University Press, at the address above You must not circulate this work in any other form and you must impose this same condition on any acquirer Published in the United States of America by Oxford University Press 198 Madison Avenue, New York, NY 10016, United States of America British Library Cataloguing in Publication Data Data available Library of Congress Control Number: 2013942195 ISBN 978–0–19–966437–5 Printed and bound by CPI Group (UK) Ltd, Croydon, CR0 4YY Links to third party websites are provided by Oxford in good faith and for information only. -
Fluctuation Theorem for Nonequilibrium Reactions
Journal of Chemical Physics 120 (2004) 8898-8905 Fluctuation theorem for nonequilibrium reactions Pierre Gaspard Center for Nonlinear Phenomena and Complex Systems, Universit´eLibre de Bruxelles, Code Postal 231, Campus Plaine, B-1050 Brussels, Belgium A fluctuation theorem is derived for stochastic nonequilibrium reactions ruled by the chemical master equation. The theorem is expressed in terms of the generating and large-deviation functions characterizing the fluctuations of a quantity which measures the loss of detailed balance out of thermodynamic equilibrium. The relationship to entropy production is established and discussed. The fluctuation theorem is verified in the Schl¨oglmodel of far-from-equilibrium bistability. PACS numbers: 82.20.Uv; 05.70.Ln; 02.50.Ey I. INTRODUCTION Reacting systems can be driven out of equilibrium when in contact with several particle reservoirs or chemiostats generating fluxes of matter across the system. The fluxes are caused by the differences of chemical potentials between the chemiostats. Such an open system may be thought of as a reactor with inlets for reactants and an outlet for the products. In this case, the open system is driven out of equilibrium at the boundaries with the chemiostats. Even if detailed balance is satisfied for all the reactions in the bulk of the reactor, the nonequilibrium boundary conditions will break detailed balance for the reactions establishing the contact with the chemiostats. According to the second law of thermodynamics, the resulting nonequilibrium states are characterized by the production of entropy inside the open system. Above the nanoscale, the reactions taking place in the system can be described in terms of the numbers of molecules of the different species. -
A Simple Method to Estimate Entropy and Free Energy of Atmospheric Gases from Their Action
Article A Simple Method to Estimate Entropy and Free Energy of Atmospheric Gases from Their Action Ivan Kennedy 1,2,*, Harold Geering 2, Michael Rose 3 and Angus Crossan 2 1 Sydney Institute of Agriculture, University of Sydney, NSW 2006, Australia 2 QuickTest Technologies, PO Box 6285 North Ryde, NSW 2113, Australia; [email protected] (H.G.); [email protected] (A.C.) 3 NSW Department of Primary Industries, Wollongbar NSW 2447, Australia; [email protected] * Correspondence: [email protected]; Tel.: + 61-4-0794-9622 Received: 23 March 2019; Accepted: 26 April 2019; Published: 1 May 2019 Abstract: A convenient practical model for accurately estimating the total entropy (ΣSi) of atmospheric gases based on physical action is proposed. This realistic approach is fully consistent with statistical mechanics, but reinterprets its partition functions as measures of translational, rotational, and vibrational action or quantum states, to estimate the entropy. With all kinds of molecular action expressed as logarithmic functions, the total heat required for warming a chemical system from 0 K (ΣSiT) to a given temperature and pressure can be computed, yielding results identical with published experimental third law values of entropy. All thermodynamic properties of gases including entropy, enthalpy, Gibbs energy, and Helmholtz energy are directly estimated using simple algorithms based on simple molecular and physical properties, without resource to tables of standard values; both free energies are measures of quantum field states and of minimal statistical degeneracy, decreasing with temperature and declining density. We propose that this more realistic approach has heuristic value for thermodynamic computation of atmospheric profiles, based on steady state heat flows equilibrating with gravity. -
LECTURES on MATHEMATICAL STATISTICAL MECHANICS S. Adams
ISSN 0070-7414 Sgr´ıbhinn´ıInstiti´uid Ard-L´einnBhaile´ Atha´ Cliath Sraith. A. Uimh 30 Communications of the Dublin Institute for Advanced Studies Series A (Theoretical Physics), No. 30 LECTURES ON MATHEMATICAL STATISTICAL MECHANICS By S. Adams DUBLIN Institi´uid Ard-L´einnBhaile´ Atha´ Cliath Dublin Institute for Advanced Studies 2006 Contents 1 Introduction 1 2 Ergodic theory 2 2.1 Microscopic dynamics and time averages . .2 2.2 Boltzmann's heuristics and ergodic hypothesis . .8 2.3 Formal Response: Birkhoff and von Neumann ergodic theories9 2.4 Microcanonical measure . 13 3 Entropy 16 3.1 Probabilistic view on Boltzmann's entropy . 16 3.2 Shannon's entropy . 17 4 The Gibbs ensembles 20 4.1 The canonical Gibbs ensemble . 20 4.2 The Gibbs paradox . 26 4.3 The grandcanonical ensemble . 27 4.4 The "orthodicity problem" . 31 5 The Thermodynamic limit 33 5.1 Definition . 33 5.2 Thermodynamic function: Free energy . 37 5.3 Equivalence of ensembles . 42 6 Gibbs measures 44 6.1 Definition . 44 6.2 The one-dimensional Ising model . 47 6.3 Symmetry and symmetry breaking . 51 6.4 The Ising ferromagnet in two dimensions . 52 6.5 Extreme Gibbs measures . 57 6.6 Uniqueness . 58 6.7 Ergodicity . 60 7 A variational characterisation of Gibbs measures 62 8 Large deviations theory 68 8.1 Motivation . 68 8.2 Definition . 70 8.3 Some results for Gibbs measures . 72 i 9 Models 73 9.1 Lattice Gases . 74 9.2 Magnetic Models . 75 9.3 Curie-Weiss model . 77 9.4 Continuous Ising model . -
Entropy and H Theorem the Mathematical Legacy of Ludwig Boltzmann
ENTROPY AND H THEOREM THE MATHEMATICAL LEGACY OF LUDWIG BOLTZMANN Cambridge/Newton Institute, 15 November 2010 C´edric Villani University of Lyon & Institut Henri Poincar´e(Paris) Cutting-edge physics at the end of nineteenth century Long-time behavior of a (dilute) classical gas Take many (say 1020) small hard balls, bouncing against each other, in a box Let the gas evolve according to Newton’s equations Prediction by Maxwell and Boltzmann The distribution function is asymptotically Gaussian v 2 f(t, x, v) a exp | | as t ≃ − 2T → ∞ Based on four major conceptual advances 1865-1875 Major modelling advance: Boltzmann equation • Major mathematical advance: the statistical entropy • Major physical advance: macroscopic irreversibility • Major PDE advance: qualitative functional study • Let us review these advances = journey around centennial scientific problems ⇒ The Boltzmann equation Models rarefied gases (Maxwell 1865, Boltzmann 1872) f(t, x, v) : density of particles in (x, v) space at time t f(t, x, v) dxdv = fraction of mass in dxdv The Boltzmann equation (without boundaries) Unknown = time-dependent distribution f(t, x, v): ∂f 3 ∂f + v = Q(f,f) = ∂t i ∂x Xi=1 i ′ ′ B(v v∗,σ) f(t, x, v )f(t, x, v∗) f(t, x, v)f(t, x, v∗) dv∗ dσ R3 2 − − Z v∗ ZS h i The Boltzmann equation (without boundaries) Unknown = time-dependent distribution f(t, x, v): ∂f 3 ∂f + v = Q(f,f) = ∂t i ∂x Xi=1 i ′ ′ B(v v∗,σ) f(t, x, v )f(t, x, v∗) f(t, x, v)f(t, x, v∗) dv∗ dσ R3 2 − − Z v∗ ZS h i The Boltzmann equation (without boundaries) Unknown = time-dependent distribution -
Physics/9803005
UWThPh-1997-52 27. Oktober 1997 History and outlook of statistical physics 1 Dieter Flamm Institut f¨ur Theoretische Physik der Universit¨at Wien, Boltzmanngasse 5, 1090 Vienna, Austria Email: [email protected] Abstract This paper gives a short review of the history of statistical physics starting from D. Bernoulli’s kinetic theory of gases in the 18th century until the recent new developments in nonequilibrium kinetic theory in the last decades of this century. The most important contributions of the great physicists Clausius, Maxwell and Boltzmann are sketched. It is shown how the reversibility and the recurrence paradox are resolved within Boltzmann’s statistical interpretation of the second law of thermodynamics. An approach to classical and quantum statistical mechanics is outlined. Finally the progress in nonequilibrium kinetic theory in the second half of this century is sketched starting from the work of N.N. Bogolyubov in 1946 up to the progress made recently in understanding the diffusion processes in dense fluids using computer simulations and analytical methods. arXiv:physics/9803005v1 [physics.hist-ph] 4 Mar 1998 1Paper presented at the Conference on Creativity in Physics Education, on August 23, 1997, in Sopron, Hungary. 1 In the 17th century the physical nature of the air surrounding the earth was es- tablished. This was a necessary prerequisite for the formulation of the gas laws. The invention of the mercuri barometer by Evangelista Torricelli (1608–47) and the fact that Robert Boyle (1627–91) introduced the pressure P as a new physical variable where im- portant steps. Then Boyle–Mariotte’s law PV = const. -
A Molecular Modeler's Guide to Statistical Mechanics
A Molecular Modeler’s Guide to Statistical Mechanics Course notes for BIOE575 Daniel A. Beard Department of Bioengineering University of Washington Box 3552255 [email protected] (206) 685 9891 April 11, 2001 Contents 1 Basic Principles and the Microcanonical Ensemble 2 1.1 Classical Laws of Motion . 2 1.2 Ensembles and Thermodynamics . 3 1.2.1 An Ensembles of Particles . 3 1.2.2 Microscopic Thermodynamics . 4 1.2.3 Formalism for Classical Systems . 7 1.3 Example Problem: Classical Ideal Gas . 8 1.4 Example Problem: Quantum Ideal Gas . 10 2 Canonical Ensemble and Equipartition 15 2.1 The Canonical Distribution . 15 2.1.1 A Derivation . 15 2.1.2 Another Derivation . 16 2.1.3 One More Derivation . 17 2.2 More Thermodynamics . 19 2.3 Formalism for Classical Systems . 20 2.4 Equipartition . 20 2.5 Example Problem: Harmonic Oscillators and Blackbody Radiation . 21 2.5.1 Classical Oscillator . 22 2.5.2 Quantum Oscillator . 22 2.5.3 Blackbody Radiation . 23 2.6 Example Application: Poisson-Boltzmann Theory . 24 2.7 Brief Introduction to the Grand Canonical Ensemble . 25 3 Brownian Motion, Fokker-Planck Equations, and the Fluctuation-Dissipation Theo- rem 27 3.1 One-Dimensional Langevin Equation and Fluctuation- Dissipation Theorem . 27 3.2 Fokker-Planck Equation . 29 3.3 Brownian Motion of Several Particles . 30 3.4 Fluctuation-Dissipation and Brownian Dynamics . 32 1 Chapter 1 Basic Principles and the Microcanonical Ensemble The first part of this course will consist of an introduction to the basic principles of statistical mechanics (or statistical physics) which is the set of theoretical techniques used to understand microscopic systems and how microscopic behavior is reflected on the macroscopic scale. -
Entropy: from the Boltzmann Equation to the Maxwell Boltzmann Distribution
Entropy: From the Boltzmann equation to the Maxwell Boltzmann distribution A formula to relate entropy to probability Often it is a lot more useful to think about entropy in terms of the probability with which different states are occupied. Lets see if we can describe entropy as a function of the probability distribution between different states. N! WN particles = n1!n2!....nt! stirling (N e)N N N W = = N particles n1 n2 nt n1 n2 nt (n1 e) (n2 e) ....(nt e) n1 n2 ...nt with N pi = ni 1 W = N particles n1 n2 nt p1 p2 ...pt takeln t lnWN particles = "#ni ln pi i=1 divide N particles t lnW1particle = "# pi ln pi i=1 times k t k lnW1particle = "k# pi ln pi = S1particle i=1 and t t S = "N k p ln p = "R p ln p NA A # i # i i i=1 i=1 ! Think about how this equation behaves for a moment. If any one of the states has a probability of occurring equal to 1, then the ln pi of that state is 0 and the probability of all the other states has to be 0 (the sum over all probabilities has to be 1). So the entropy of such a system is 0. This is exactly what we would have expected. In our coin flipping case there was only one way to be all heads and the W of that configuration was 1. Also, and this is not so obvious, the maximal entropy will result if all states are equally populated (if you want to see a mathematical proof of this check out Ken Dill’s book on page 85). -
Fluctuation Theorems for Quantum Master Equations
PHYSICAL REVIEW E 73, 046129 ͑2006͒ Fluctuation theorems for quantum master equations Massimiliano Esposito* and Shaul Mukamel Department of Chemistry, University of California, Irvine, California 92697, USA ͑Received 17 November 2005; published 24 April 2006͒ A quantum fluctuation theorem for a driven quantum subsystem interacting with its environment is derived based solely on the assumption that its reduced density matrix obeys a closed evolution equation—i.e., a quantum master equation ͑QME͒. Quantum trajectories and their associated entropy, heat, and work appear naturally by transforming the QME to a time-dependent Liouville space basis that diagonalizes the instanta- neous reduced density matrix of the subsystem. A quantum integral fluctuation theorem, a steady-state fluc- tuation theorem, and the Jarzynski relation are derived in a similar way as for classical stochastic dynamics. DOI: 10.1103/PhysRevE.73.046129 PACS number͑s͒: 05.30.Ch, 05.70.Ln, 03.65.Yz I. INTRODUCTION restricted situations ͓24–27͔. A quantum exchange fluctua- tion theorem has also been considered in ͓28͔. Some inter- The fluctuation theorems and the Jarzynski relation are esting considerations of the quantum definition of work in some of a handful of powerful results of nonequilibrium sta- the previous studies have been made in ͓29͔. tistical mechanics that hold far from thermodynamic equilib- It should be noted that the dynamics of an isolated rium. Originally derived in the context of classical mechan- ͑whether driven or not͒ quantum system is unitary and its ics ͓1͔, the Jarzynski relation has been subsequently von Neumann entropy is time independent. Therefore, fluc- extended to stochastic dynamics ͓2͔. -
Boltzmann Equation II: Binary Collisions
Physics 127b: Statistical Mechanics Boltzmann Equation II: Binary Collisions Binary collisions in a classical gas Scattering out Scattering in v'1 v'2 v 1 v 2 R v 2 v 1 v'2 v'1 Center of V' Mass Frame V θ θ b sc sc R V V' Figure 1: Binary collisions in a gas: top—lab frame; bottom—centre of mass frame Binary collisions in a gas are very similar, except that the scattering is off another molecule. An individual scattering process is, of course, simplest to describe in the center of mass frame in terms of the relative E velocity V =Ev1 −Ev2. However the center of mass frame is different for different collisions, so we must keep track of the results in the lab frame, and this makes the calculation rather intricate. I will indicate the main ideas here, and refer you to Reif or Landau and Lifshitz for precise discussions. Lets first set things up in the lab frame. Again we consider the pair of scattering in and scattering out processes that are space-time inverses, and so have identical cross sections. We can write abstractly for the scattering out from velocity vE1 due to collisions with molecules with all velocities vE2, which will clearly be proportional to the number f (vE1) of molecules at vE1 (which we write as f1—sorry, not the same notation as in the previous sections where f1 denoted the deviation of f from the equilibrium distribution!) and the 3 3 number f2d v2 ≡ f(vE2)d v2 in each velocity volume element, and then we must integrate over all possible vE0 vE0 outgoing velocities 1 and 2 ZZZ df (vE ) 1 =− w(vE0 , vE0 ;Ev , vE )f f d3v d3v0 d3v0 . -
Fluctuation Theorem
Fluctuation Theorem Giovanni Gallavotti Fluctuation Theorem: a simple consequence of a time reversal symmetry; it deals with motions which are chaotic in the strong mathematical sense of being hyperbolic and transitive (ie are generated by smooth hyperbolic evolutions on a smooth compact surface (the “phase space”) and with a dense trajectory, also called Anosov systems) and “furthermore are time reversible”. In such systems any initial data, with the exception of a set of zero volume in phase space, have the same statistical properties in the sense that all smooth observables admit a time average independent of the initial data and expressed as an integral with respect to a probability distribution on phase space, called the ”natural stationary state”, or simply the “stationary state”. The theorem provides, asymptotically in the observation time, a quantitative and param- eter free relation between the stationary state probability of observing a value of the average entropy production rate and its opposite. Although there are quite a few examples of mechanical systems which are hyperbolic and transitive in the above mathematical sense, the fluctuation theorem ac- quires physical interest only in connection with the chaotic hypothesis. Under the latter general assumption, combined with time reversal, it pre- dicts a ”universal relation” between an entropy creation rate value and its opposite, accessible to simulations and possibly to laboratory experiments. The basis for the physical interpretation of the theorem as a property of stationary states in nonequilibrium statistical mechanics is developed here. Statistical Mechanics of Nonequilibrium Stationary States. Thermostats In nonequilibrium statistical mechanics the molecules of a system are sub- ject to nonconservative forces whose work is dissipated in the form of heat supplied to other systems kept at constant temperature: the ”thermostats” with which the system is in contact. -
Equalities and Inequalities : Irreversibility and the Second Law of Thermodynamics at the Nanoscale
S´eminairePoincar´eXV Le Temps (2010) 77 { 102 S´eminairePoincar´e Equalities and Inequalities : Irreversibility and the Second Law of Thermodynamics at the Nanoscale Christopher Jarzynski Department of Chemistry and Biochemistry and Institute for Physical Science and Technology University of Maryland College Park MD 20742, USA 1 Introduction On anyone's list of the supreme achievements of the nineteenth-century science, both Maxwell's equations and the second law of thermodynamics surely rank high. Yet while Maxwell's equations are widely viewed as done, dusted, and uncontro- versial, the second law still provokes lively arguments, long after Carnot published his Reflections on the Motive Power of Fire (1824) and Clausius articulated the increase of entropy (1865). The puzzle at the core of the second law is this : how can microscopic equations of motion that are symmetric with respect to time-reversal give rise to macroscopic behavior that clearly does not share this symmetry ? Of course, quite apart from questions related to the origin of \time's arrow", there is a nuts-and-bolts aspect to the second law. Together with the first law, it provides a set of tools that are indispensable in practical applications ranging from the design of power plants and refrigeration systems to the analysis of chemical reactions. The past few decades have seen growing interest in applying these laws and tools to individual microscopic systems, down to nanometer length scales. Much of this interest arises at the intersection of biology, chemistry and physics, where there has been tremendous progress in uncovering the mechanochemical details of biomolecular processes.