DOCSLIB.ORG

Statistical Physics– a Second Course

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Statistical Physics– a Second Course Statistical Physics– a second course Finn Ravndal and Eirik Grude Flekkøy Department of Physics University of Oslo September 3, 2008 2 Contents 1 Summary of Thermodynamics 5 1.1 Equationsofstate .......................... 5 1.2 Lawsofthermodynamics. 7 1.3 Maxwell relations and thermodynamic derivatives . .... 9 1.4 Specificheatsandcompressibilities . 10 1.5 Thermodynamicpotentials . 12 1.6 Fluctuations and thermodynamic stability . .. 15 1.7 Phasetransitions ........................... 16 1.8 EntropyandGibbsParadox. 18 2 Non-Interacting Particles 23 1 2.1 Spin- 2 particlesinamagneticfield . 23 2.2 Maxwell-Boltzmannstatistics . 28 2.3 Idealgas................................ 32 2.4 Fermi-Diracstatistics. 35 2.5 Bose-Einsteinstatistics. 36 3 Statistical Ensembles 39 3.1 Ensemblesinphasespace . 39 3.2 Liouville’stheorem . .. .. .. .. .. .. .. .. .. .. 42 3.3 Microcanonicalensembles . 45 3.4 Free particles and multi-dimensional spheres . .... 48 3.5 Canonicalensembles . 50 3.6 Grandcanonicalensembles . 54 3.7 Isobaricensembles .......................... 58 3.8 Informationtheory . .. .. .. .. .. .. .. .. .. .. 62 4 Real Gases and Liquids 67 4.1 Correlationfunctions. 67 4.2 Thevirialtheorem .......................... 73 4.3 Mean field theory for the van der Waals equation . 76 4.4 Osmosis ................................ 80 3 4 CONTENTS 5 Quantum Gases and Liquids 83 5.1 Statisticsofidenticalparticles. .. 83 5.2 Blackbodyradiationandthephotongas . 88 5.3 Phonons and the Debye theory of specific heats . 96 5.4 Bosonsatnon-zerochemicalpotential . 101 5.5 Bose-Einstein condensation and superfluid 4He .......... 107 5.6 Fermiongasesatfinitetemperature. 117 5.7 Degenerateelectronsinmetals . 125 5.8 Whitedwarfsandneutronstars. 126 6 Magnetic Systems and Spin Models 129 6.1 Thermodynamicsofmagnets . 129 6.2 Magnetism .............................. 133 6.3 Heisenberg, XY, IsingandPottsmodels . 138 6.4 Spincorrelationfunctions . 143 6.5 ExactsolutionsofIsingmodels . 146 6.6 Weissmeanfieldtheory . 151 6.7 Landaumeanfieldtheory . 155 7 Stochastic Processes 163 7.1 RandomWalks ............................ 163 7.2 Thecentrallimittheorem . 169 7.3 Diffusion and the diffusion equation . 170 7.4 Markovchains ............................ 174 7.5 Themasterequation . 178 7.6 MonteCarlomethods . 183 8 Non-equilibrium Statistical Mechanics 189 8.1 BrownianmotionandtheLangevinequation . 189 8.2 Thefluctuationdissipationtheorem . 194 8.3 GeneralizedLangevinEquation . 200 8.4 Green-Kuborelations . 203 8.5 Onsagerrelations. 205 9 Appendix 209 9.1 Fouriertransforms . 209 9.2 Convolutiontheorem. 211 9.3 Evenextensiontransform . 211 9.4 Wiener-Khinichetheorem . 212 9.5 Solutionof2dIsingmodels . 213 Chapter 1 Summary of Thermodynamics Equation of state The dynamics of particles and their interactions were under- stood at the classical level by the establishment of Newton’s laws. Later, these had to be slightly modified with the introduction of Einstein’s theory of relativ- ity. A complete reformulation of mechanics became necessary when quantum effects were discovered. In the middle of last century steam engines were invented and physicists were trying to establish the connection between thermal heat and mechanical work. This effort led to the fundamental laws of thermodynamics. In contrast to the laws of mechanics which had to be modified, these turned out to have a much larger range of validity. In fact, today we know that they can be used to describe all systems from classical gases and liquids, through quantum systems like superconductors and nuclear matter, to black holes and the elementary particles in the early Universe in exactly the same form as they were originally established. In this way thermodynamics is one of the most fundamental parts of modern science. 1.1 Equations of state Equation of state We will now in the beginning consider classical systems like gases and liquids. When these are in equilibrium, they can be assigned state variables like temper- ature T , pressure P and total volume V . These can not take arbitrary values when the system is in equilibrium since they will be related by an equation of state. Usually it has the form P = P (V,T ) . (1.1) Only values for two state variables can be independently assigned to the system. The third state variable is then fixed. 5 6 CHAPTER 1. SUMMARY OF THERMODYNAMICS The equations of state for physical systems cannot be obtained from ther- modynamics but must be established experimentally. But using the methods of statistical mechanics and knowing the fundamental interactions between and the properties of the atoms and molecules in the system, it can in principle be obtained. An ideal gas of N particles obeys the equation of state NkT P = (1.2) V where k is Boltzmann’s fundamental constant k = 1.381 10−23 JK−1. For × one mole of the gas the number of particles equals Avogadro’s number NA = 23 −1 −1 −1 −1 −1 6.023 10 mol and R = NAk =8.314 JK mol =1.987 calK mol . Since ×ρ = N/V is the density of particles, the ideal gas law (1.2) can also be P V Figure 1.1: Equation of state for an ideal gas at constant temperature. written as P = kTρ. The pressure in the gas increases with temperature for constant density. In an ideal gas there are no interactions between the particles. Including these in a simple and approximative way gives the more realistic van der Waals equation of state NkT aN 2 P = . (1.3) V Nb − V 2 − It is useful for understanding in an elementary way the transition of the gas to a liquid phase. Later in these lectures we will derive the general equation of state for gases 1.2. LAWS OF THERMODYNAMICS 7 with two-body interactions. It will have the general form ∞ n P = kT ρ Bn(T ) . (1.4) n=1 X The functions Bn(T ) are called virial coefficients with B1 = 1. They can all be calculated in principle, but only the first few are usually obtained. We see that the van der Waal’s equation (1.3) can be expanded to give this form of the virial expansion. A real gas-liquid system has a phase diagram which can be obtained from the equation of state. When it is projected onto the PT and P V planes, it has the general form shown in Fig.1.2. For low pressures there is a gas phase g. It condenses into a liquid phase ℓ at higher pressures and eventually goes into P P s l c T > T c t g T = T c T < T c T V Figure 1.2: Phase diagram of a real liquid-gas system. The dotted line in the left figure indicates the two phase transitions it undergoes while being heated up at constant pressure. the sold phase s at the highest pressures. At low temperatures, the gas can go directly into the solid phase. At the triple point t all three phases are in equilibrium. The gas-liquid co-existence curve terminates at the critical point c. In other thermodynamic systems like magnets and superconductors, there will be other state variables needed to specify the equilibrium states. But they will again all be related by an equation of state. These systems are in many ways more important and interesting today than the physics of gases and liquids. But the general thermodynamics will be very similar. We will come back to these systems later in the lectures. 1.2 Laws of thermodynamics Laws of thermodynamics When we add an small amount of heat ∆Q to a system, its internal energy U will change at the same time as the system can perform some work ∆W . These changes are related by energy conservation, ∆Q = ∆U + ∆W . (1.5) 8 CHAPTER 1. SUMMARY OF THERMODYNAMICS For a system with fixed number of particles, the work done is given by the change of volume ∆V and the pressure in the gas as ∆W = P ∆V . (1.6) It is positive when the volume of the system increases. The internal energy U depends only on the state of the system in contrast to the heat added and work done. These quantities depend on the way they have changed. U is therefore called a state function. Experiments also revealed that the system can be assigned another, very important state function which is the entropy S. It is related to the heat added by the fundamental inequality ∆Q ∆S (1.7) ≥ T where T is the temperature of the system. Reversible processes are defined to be those for which this is an equality. In the limit where the heat is added infinitely slowly, the process becomes reversible and (1.5) and (1.7) combined give T ∆S = ∆U + P ∆V (1.8) for such a gas-liquid system. This equation is a mathematical statement of the First Law of thermodynamics. When we later consider magnets, it will involve other variables, but still basically express energy conservation. The Second Law of thermodynamics is already given in (1.7). For an isolated system, ∆Q = 0, it then follows that the entropy has to remain constant or increase, ∆S 0. Combining (1.7) with energy conservation from (1.5), we obtain ≥ T ∆S ∆U + P ∆V . (1.9) ≥ This important inequality contains information about the allowed changes in the system. As an illustration of the Second Law, consider the melting of ice. At normal pressure it takes place at 0 ◦C degrees with the latent or melting heat Λ = 1440 cal mol−1 taken from the surroundings. Water is more disordered than ice and its entropy is higher by the amount ∆S =Λ/273K = 5.27 cal K−1 mol−1 since the process is reversible at this temperature. But why doesn’t ice melt at 10 ◦C since it would then increase its entropy? The answer is given − by (1.7) which in this case is violated, 5.27 < 1440/263. However, it will melt spontaneously at +10 ◦C as we all know since 5.27 > 1440/283. We have here made the reasonable approx- imation that the latent heat doesn’t vary significantly in this temperature range.
Load more

Recommended publications
  • Canonical Ensemble
    ME346A Introduction to Statistical Mechanics { Wei Cai { Stanford University { Win 2011 Handout 8. Canonical Ensemble January 26, 2011 Contents Outline • In this chapter, we will establish the equilibrium statistical distribution for systems maintained at a constant temperature T , through thermal contact with a heat bath. • The resulting distribution is also called Boltzmann's distribution. • The canonical distribution also leads to definition of the partition function and an expression for Helmholtz free energy, analogous to Boltzmann's Entropy formula. • We will study energy fluctuation at constant temperature, and witness another fluctuation- dissipation theorem (FDT) and finally establish the equivalence of micro canonical ensemble and canonical ensemble in the thermodynamic limit. (We first met a mani- festation of FDT in diffusion as Einstein's relation.) Reading Assignment: Reif x6.1-6.7, x6.10 1 1 Temperature For an isolated system, with fixed N { number of particles, V { volume, E { total energy, it is most conveniently described by the microcanonical (NVE) ensemble, which is a uniform distribution between two constant energy surfaces. const E ≤ H(fq g; fp g) ≤ E + ∆E ρ (fq g; fp g) = i i (1) mc i i 0 otherwise Statistical mechanics also provides the expression for entropy S(N; V; E) = kB ln Ω. In thermodynamics, S(N; V; E) can be transformed to a more convenient form (by Legendre transform) of Helmholtz free energy A(N; V; T ), which correspond to a system with constant N; V and temperature T . Q: Does the transformation from N; V; E to N; V; T have a meaning in statistical mechanics? A: The ensemble of systems all at constant N; V; T is called the canonical NVT ensemble.
    [Show full text]
  • Bose-Einstein Condensation of Photons and Grand-Canonical Condensate fluctuations
    Bose-Einstein condensation of photons and grand-canonical condensate fluctuations Jan Klaers Institute for Applied Physics, University of Bonn, Germany Present address: Institute for Quantum Electronics, ETH Zürich, Switzerland Martin Weitz Institute for Applied Physics, University of Bonn, Germany Abstract We review recent experiments on the Bose-Einstein condensation of photons in a dye-filled optical microresonator. The most well-known example of a photon gas, pho- tons in blackbody radiation, does not show Bose-Einstein condensation. Instead of massively populating the cavity ground mode, photons vanish in the cavity walls when they are cooled down. The situation is different in an ultrashort optical cavity im- printing a low-frequency cutoff on the photon energy spectrum that is well above the thermal energy. The latter allows for a thermalization process in which both tempera- ture and photon number can be tuned independently of each other or, correspondingly, for a non-vanishing photon chemical potential. We here describe experiments demon- strating the fluorescence-induced thermalization and Bose-Einstein condensation of a two-dimensional photon gas in the dye microcavity. Moreover, recent measurements on the photon statistics of the condensate, showing Bose-Einstein condensation in the grandcanonical ensemble limit, will be reviewed. 1 Introduction Quantum statistical effects become relevant when a gas of particles is cooled, or its den- sity is increased, to the point where the associated de Broglie wavepackets spatially over- arXiv:1611.10286v1 [cond-mat.quant-gas] 30 Nov 2016 lap. For particles with integer spin (bosons), the phenomenon of Bose-Einstein condensation (BEC) then leads to macroscopic occupation of a single quantum state at finite tempera- tures [1].
    [Show full text]
  • Grand-Canonical Ensemble
    PHYS4006: Thermal and Statistical Physics Lecture Notes (Unit - IV) Open System: Grand-canonical Ensemble Dr. Neelabh Srivastava (Assistant Professor) Department of Physics Programme: M.Sc. Physics Mahatma Gandhi Central University Semester: 2nd Motihari-845401, Bihar E-mail: [email protected] • In microcanonical ensemble, each system contains same fixed energy as well as same number of particles. Hence, the system dealt within this ensemble is a closed isolated system. • With microcanonical ensemble, we can not deal with the systems that are kept in contact with a heat reservoir at a given temperature. 2 • In canonical ensemble, the condition of constant energy is relaxed and the system is allowed to exchange energy but not the particles with the system, i.e. those systems which are not isolated but are in contact with a heat reservoir. • This model could not be applied to those processes in which number of particle varies, i.e. chemical process, nuclear reactions (where particles are created and destroyed) and quantum process. 3 • So, for the method of ensemble to be applicable to such processes where number of particles as well as energy of the system changes, it is necessary to relax the condition of fixed number of particles. 4 • Such an ensemble where both the energy as well as number of particles can be exchanged with the heat reservoir is called Grand Canonical Ensemble. • In canonical ensemble, T, V and N are independent variables. Whereas, in grand canonical ensemble, the system is described by its temperature (T),volume (V) and chemical potential (μ). 5 • Since, the system is not isolated, its microstates are not equally probable.
    [Show full text]
  • The Grand Canonical Ensemble
    University of Central Arkansas The Grand Canonical Ensemble Stephen R. Addison Directory ² Table of Contents ² Begin Article Copyright °c 2001 [email protected] Last Revision Date: April 10, 2001 Version 0.1 Table of Contents 1. Systems with Variable Particle Numbers 2. Review of the Ensembles 2.1. Microcanonical Ensemble 2.2. Canonical Ensemble 2.3. Grand Canonical Ensemble 3. Average Values on the Grand Canonical Ensemble 3.1. Average Number of Particles in a System 4. The Grand Canonical Ensemble and Thermodynamics 5. Legendre Transforms 5.1. Legendre Transforms for two variables 5.2. Helmholtz Free Energy as a Legendre Transform 6. Legendre Transforms and the Grand Canonical Ensem- ble 7. Solving Problems on the Grand Canonical Ensemble Section 1: Systems with Variable Particle Numbers 3 1. Systems with Variable Particle Numbers We have developed an expression for the partition function of an ideal gas. Toc JJ II J I Back J Doc Doc I Section 2: Review of the Ensembles 4 2. Review of the Ensembles 2.1. Microcanonical Ensemble The system is isolated. This is the ¯rst bridge or route between mechanics and thermodynamics, it is called the adiabatic bridge. E; V; N are ¯xed S = k ln ­(E; V; N) Toc JJ II J I Back J Doc Doc I Section 2: Review of the Ensembles 5 2.2. Canonical Ensemble System in contact with a heat bath. This is the second bridge between mechanics and thermodynamics, it is called the isothermal bridge. This bridge is more elegant and more easily crossed. T; V; N ¯xed, E fluctuates.
    [Show full text]
  • Statistical Physics 06/07
    STATISTICAL PHYSICS 06/07 Quantum Statistical Mechanics Tutorial Sheet 3 The questions that follow on this and succeeding sheets are an integral part of this course. The code beside each question has the following significance: • K: key question – explores core material • R: review question – an invitation to consolidate • C: challenge question – going beyond the basic framework of the course • S: standard question – general fitness training! 3.1 Particle Number Fluctuations for Fermions [s] (a) For a single fermion state in the grand canonical ensemble, show that 2 h(∆nj) i =n ¯j(1 − n¯j) wheren ¯j is the mean occupancy. Hint: You only need to use the exclusion principle not the explict form ofn ¯j. 2 How is the fact that h(∆nj) i is not in general small compared ton ¯j to be reconciled with the sharp values of macroscopic observables? (b) For a gas of noninteracting particles in the grand canonical ensemble, show that 2 X 2 h(∆N) i = h(∆nj) i j (you will need to invoke that nj and nk are uncorrelated in the GCE for j 6= k). Hence show that for noninteracting Fermions Z h(∆N)2i = g() f(1 − f) d follows from (a) where f(, µ) is the F-D distribution and g() is the density of states. (c) Show that for low temperatures f(1 − f) is sharply peaked at = µ, and hence that 2 h∆N i ' kBT g(F ) where F = µ(T = 0) R ∞ ex dx [You may use without proof the result that −∞ (ex+1)2 = 1.] 3.2 Entropy of the Ideal Fermi Gas [C] The Grand Potential for an ideal Fermi is given by X Φ = −kT ln [1 + exp β(µ − j)] j Show that for Fermions X Φ = kT ln(1 − pj) , j where pj = f(j) is the probability of occupation of the state j.
    [Show full text]
  • Grand-Canonical Ensembles
    Grand-canonical ensembles As we know, we are at the point where we can deal with almost any classical problem (see below), but for quantum systems we still cannot deal with problems where the translational degrees of freedom are described quantum mechanically and particles can interchange their locations – in such cases we can write the expression for the canonical partition function, but because of the restriction on the occupation numbers we simply cannot calculate it! (see end of previous write-up). Even for classical systems, we do not know how to deal with problems where the number of particles is not fixed (open systems). For example, suppose we have a surface on which certain types of atoms can be adsorbed (trapped). The surface is in contact with a gas containing these atoms, and depending on conditions some will stick to the surface while other become free and go into the gas. Suppose we are interested only in the properties of the surface (for instance, the average number of trapped atoms as a function of temperature). Since the numbers of atoms on the surface varies, this is an open system and we still do not know how to solve this problem. So for these reasons we need to introduce grand-canonical ensembles. This will finally allow us to study quantum ideal gases (our main goal for this course). As we expect, the results we’ll obtain at high temperatures will agree with the classical predictions we already have, however, as we will see, the low-temperature quantum behavior is really interesting and worth the effort! Like we did for canonical ensembles, I’ll introduce the formalism for classical problems first, and then we’ll generalize to quantum systems.
    [Show full text]
  • Microcanonical, Canonical, and Grand Canonical Ensembles Masatsugu Sei Suzuki Department of Physics, SUNY at Binghamton (Date: September 30, 2016)
    The equivalence: microcanonical, canonical, and grand canonical ensembles Masatsugu Sei Suzuki Department of Physics, SUNY at Binghamton (Date: September 30, 2016) Here we show the equivalence of three ensembles; micro canonical ensemble, canonical ensemble, and grand canonical ensemble. The neglect for the condition of constant energy in canonical ensemble and the neglect of the condition for constant energy and constant particle number can be possible by introducing the density of states multiplied by the weight factors [Boltzmann factor (canonical ensemble) and the Gibbs factor (grand canonical ensemble)]. The introduction of such factors make it much easier for one to calculate the thermodynamic properties. ((Microcanonical ensemble)) In the micro canonical ensemble, the macroscopic system can be specified by using variables N, E, and V. These are convenient variables which are closely related to the classical mechanics. The density of states (N E,, V ) plays a significant role in deriving the thermodynamic properties such as entropy and internal energy. It depends on N, E, and V. Note that there are two constraints. The macroscopic quantity N (the number of particles) should be kept constant. The total energy E should be also kept constant. Because of these constraints, in general it is difficult to evaluate the density of states. ((Canonical ensemble)) In order to avoid such a difficulty, the concept of the canonical ensemble is introduced. The calculation become simpler than that for the micro canonical ensemble since the condition for the constant energy is neglected. In the canonical ensemble, the system is specified by three variables ( N, T, V), instead of N, E, V in the micro canonical ensemble.
    [Show full text]
  • LECTURE 9 Statistical Mechanics Basic Methods We Have Talked
    LECTURE 9 Statistical Mechanics Basic Methods We have talked about ensembles being large collections of copies or clones of a system with some features being identical among all the copies. There are three different types of ensembles in statistical mechanics. 1. If the system under consideration is isolated, i.e., not interacting with any other system, then the ensemble is called the microcanonical ensemble. In this case the energy of the system is a constant. 2. If the system under consideration is in thermal equilibrium with a heat reservoir at temperature T , then the ensemble is called a canonical ensemble. In this case the energy of the system is not a constant; the temperature is constant. 3. If the system under consideration is in contact with both a heat reservoir and a particle reservoir, then the ensemble is called a grand canonical ensemble. In this case the energy and particle number of the system are not constant; the temperature and the chemical potential are constant. The chemical potential is the energy required to add a particle to the system. The most common ensemble encountered in doing statistical mechanics is the canonical ensemble. We will explore many examples of the canonical ensemble. The grand canon- ical ensemble is used in dealing with quantum systems. The microcanonical ensemble is not used much because of the difficulty in identifying and evaluating the accessible microstates, but we will explore one simple system (the ideal gas) as an example of the microcanonical ensemble. Microcanonical Ensemble Consider an isolated system described by an energy in the range between E and E + δE, and similar appropriate ranges for external parameters xα.
    [Show full text]
  • Statistical Physics Syllabus Lectures and Recitations
    Graduate Statistical Physics Syllabus Lectures and Recitations Lectures will be held on Tuesdays and Thursdays from 9:30 am until 11:00 am via Zoom: https://nyu.zoom.us/j/99702917703. Recitations will be held on Fridays from 3:30 pm until 4:45 pm via Zoom. Recitations will begin the second week of the course. David Grier's office hours will be held on Mondays from 1:30 pm to 3:00 pm in Physics 873. Ankit Vyas' office hours will be held on Fridays from 1:00 pm to 2:00 pm in Physics 940. Instructors David G. Grier Office: 726 Broadway, room 873 Phone: (212) 998-3713 email: [email protected] Ankit Vyas Office: 726 Broadway, room 965B Email: [email protected] Text Most graduate texts in statistical physics cover the material of this course. Suitable choices include: • Mehran Kardar, Statistical Physics of Particles (Cambridge University Press, 2007) ISBN 978-0-521-87342-0 (hardcover). • Mehran Kardar, Statistical Physics of Fields (Cambridge University Press, 2007) ISBN 978- 0-521-87341-3 (hardcover). • R. K. Pathria and Paul D. Beale, Statistical Mechanics (Elsevier, 2011) ISBN 978-0-12- 382188-1 (paperback). Undergraduate texts also may provide useful background material. Typical choices include • Frederick Reif, Fundamentals of Statistical and Thermal Physics (Waveland Press, 2009) ISBN 978-1-57766-612-7. • Charles Kittel and Herbert Kroemer, Thermal Physics (W. H. Freeman, 1980) ISBN 978- 0716710882. • Daniel V. Schroeder, An Introduction to Thermal Physics (Pearson, 1999) ISBN 978- 0201380279. Outline 1. Thermodynamics 2. Probability 3. Kinetic theory of gases 4.
    [Show full text]
  • Lecture 7: Ensembles
    Matthew Schwartz Statistical Mechanics, Spring 2019 Lecture 7: Ensembles 1 Introduction In statistical mechanics, we study the possible microstates of a system. We never know exactly which microstate the system is in. Nor do we care. We are interested only in the behavior of a system based on the possible microstates it could be, that share some macroscopic proporty (like volume V ; energy E, or number of particles N). The possible microstates a system could be in are known as the ensemble of states for a system. There are dierent kinds of ensembles. So far, we have been counting microstates with a xed number of particles N and a xed total energy E. We dened as the total number microstates for a system. That is (E; V ; N) = 1 (1) microstatesk withsaXmeN ;V ;E Then S = kBln is the entropy, and all other thermodynamic quantities follow from S. For an isolated system with N xed and E xed the ensemble is known as the microcanonical 1 @S ensemble. In the microcanonical ensemble, the temperature is a derived quantity, with T = @E . So far, we have only been using the microcanonical ensemble. 1 3 N For example, a gas of identical monatomic particles has (E; V ; N) V NE 2 . From this N! we computed the entropy S = kBln which at large N reduces to the Sackur-Tetrode formula. 1 @S 3 NkB 3 The temperature is T = @E = 2 E so that E = 2 NkBT . Also in the microcanonical ensemble we observed that the number of states for which the energy of one degree of freedom is xed to "i is (E "i) "i/k T (E " ).
    [Show full text]
  • Arxiv:Cond-Mat/0411176V1
    PARTITION FUNCTIONS FOR STATISTICAL MECHANICS WITH MICROPARTITIONS AND PHASE TRANSITIONS AJAY PATWARDHAN Physics department, St Xavier’s college, Mahapalika Marg , Mumbai 400001,India Visitor, Institute of Mathematical Sciences, CIT campus, Tharamani, Chennai, India [email protected] ABSTRACT The fundamentals of Statistical Mechanics require a fresh definition in the context of the developments in Classical Mechanics of integrable and chaotic systems. This is done with the introduction of Micro partitions; a union of disjoint components in phase space. Partition functions including the invariants ,Kolmogorov entropy and Euler number are introduced. The ergodic hypothesis for partial ergodicity is discussed. In the context of Quantum Mechanics the presence of symmetry groups with irreducible representations gives rise to degenerate and non degenerate spectrum for the Hamiltonian. Quantum Statistical Mechanics is formulated including these two cases ; by including the multiplicity dimension of the group representation and the Casimir invariants into the Partition function. The possibility of new kinds of phase transitions is discussed. The occurence of systems with non simply connected configuration spaces and Quantum Mechanics for them , also requires a possible generalisation of Statistical Mechanics. The developments of Quantum pure, mixed and en- tangled states has made it neccessary to understand the Statistical Mechanics of the multipartite N particle system . And to obtain in terms of the den- sity matrices , written in energy basis , the Trace of the Gibbs operator as the Partition function and use it to get statistical averages of operators. There are some issues of definition, interpretation and application that are discussed. INTRODUCTION A Statistical Mechanics of systems with properties of symmetry , chaos, topology and mixtures is required for a variety of physics ; including con- densed matter and high energy physics.
    [Show full text]
  • 8.044 Lecture Notes Chapter 6: Statistical Mechanics at Fixed Temperature (Canonical Ensemble)
    8.044 Lecture Notes Chapter 6: Statistical Mechanics at Fixed Temperature (Canonical Ensemble) Lecturer: McGreevy 6.1 Derivation of the Canonical Ensemble . 6-2 6.2 Monatomic, classical, ideal gas, at fixed T ................... 6-11 6.3 Two-level systems, re-revisited . 6-16 6.4 Classical harmonic oscillators and equipartition of energy . 6-20 6.5 Quantum harmonic oscillators . 6-23 6.6 Heat capacity of a diatomic ideal gas . 6-30 6.7 Paramagnetism . 6-35 6.7.1 Cooling by adiabatic demagnetization . 6-39 6.8 The Third Law of Thermodynamics . 6-42 Reading: Greytak, Notes on the Canonical Ensemble; Baierlein, Chapters 5, 13, 14. Optional Reading for x6.6: Greytak, Notes on (Raman Spectroscopy of) Diatomic Molecules. 6-1 6.1 Derivation of the Canonical Ensemble In Chapter 4, we studied the statistical mechanics of an isolated system. This meant fixed E; V; N. From some fundamental principles (really, postulates), we developed an algorithm for cal- culating (which turns out not to be so practical, as you'll have seen e.g. if you thought about the random 2-state systems on pset 6): 1. Model the system 2. Count microstates for given E: Ω(E; V; N). 3. from Ω, derive thermodynamics by S = kB ln Ω. Ω0(X) 4. from Ω, derive microscopic information by p(X) = Ω . The fixed-energy constraint makes the counting difficult, in all but the simplest problems (the ones we've done). Fixing the temperature happens to be easier to analyze in practice. Consider a system 1 which is not isolated, but rather is in thermal contact with a heat bath 2 , and therefore held at fixed temperature T equal to that of the bath.
    [Show full text]