Part II: Statistical Physics

Size: px
Start display at page:

Download "Part II: Statistical Physics"

Transcription

1 Chapter 6: Boltzmann Statistics SDSMT, Physics Fall Semester: Oct. - Dec., 2014

2 1 Introduction: Very brief 2 Boltzmann Factor Isolated System and System of Interest Boltzmann Factor The Partition Function Z 3 Average Values in a Canonical Ensemble Applications 4 The Equipartition Theorem

3 Introduction In the first part of Thermal Physics, the Thermodynamics, we have learned: (1) Bulk properties of a large system, equations of state; (2) Microscopic picture of a thermal system: multiplicity, entropy, and the 2nd Law, which includes simple statistical treatment of an isolated system. (3) Thermodynamic treatment of systems interacting with each other or in contact with the heat reservoir = the maximum entropy, the minimum free energy principles, and their applications in engine and refrigerators. (4) How enthalpy (H=U+PV), Helmholtz free energy (F=U-TS), and Gibbs free energy (G=U-TS+PV) govern the processes toward equilibrium and phase transformations.

4 Introduction We tried to connect (2) and the rest contents by showing simple examples such as Ideal Gas, Einstein solid, and van der Waals gas/fluid = impressive connections between macroscopic and microscopic properties. In doing so, we based all arguments on a fundamental assumption: a closed (isolated) system visits every one of its microstates with equal frequency. In other words, all allowed microstates of the system are equally probable. In this course, we will develop more complicated models based on the same fundamental assumption for the study of a greater variety of physical systems.

5 From an isolated system to a non-isolated system We will introduce the most powerful tool in statistical mechanics to find the probability of finding a system in any particular microstate. To start, let s revisit the Isolated System and System of Interest. Combined system U 0 = const Reservoir R U 0 - ε System S ε A combined (isolated) system: (1) a heat reservoir (2) a system of interest in thermal contact with the heat reservoir

6 Isolated System- cnt. Some fundamental assumptions for an Isolated System: An isolated system in thermal equilibrium will pass through all the accessible microstates states at the same recurrence rate as it evolves over time, i.e. all accessible microstates are equally probable. Probability of a particular microstate of a microcanonical ensemble = 1 (Total number of all accessible microstates). Probability of a particular macrostate = (Ω of a particular macrostate) (Total number of all accessible microstates) The energy inside the system is conserved. A set of hypothetical systems with this probability distribution is called a mirocanonical ensemble These provides us with the basis for the study of a system we are interested in.

7 A system in thermal contact with a heat reservoir The system of interest can be any small macroscopic or microscopic object - a box of gas, a piece of solid, an atom or molecule, etc. Assuming: Interactions between the system and the reservoir are weak: with heat exchange but no affect on the microscopic structure inside the system of interest; Total energy conservation: U 0 = U R + U S = const. Energies in the system (and therefore in the reservoir) may fluctuate by a small amount δ: U 0 = (U R δ) + (U S + δ) = const. This system of interest can also be a small system: with small number of particles, small volume,... At the equilibrium between the system and reservoir, our question would be What is the probability P(E i ) of finding the system S in a particular (microscopic) quantum state i of energy E i?

8 Boltzmann Factor Now let s figure out what this P(E i ) is. Assume two microstates s 1 and s 2 in the system, corresponding to two different energy levels E(s 1) and E(s 2). The probability to find the system at these two states are P(s 1) and P(s 2). Ω comb. (s 1, U E(s 1)) = Ω S (s 1) Ω R (U E(s 1)) (1) Ω S (s 1) = 1 (system is now on a fix known state - no degeneracy case.) Ω comb. (s 1, U E(s 1)) = Ω R (U E(s 1)) = Ω R (s 1) (2) P(s 1) = Ω comb.(s 1, U E(s 1)) Ω comb. (U, N, T ) And same for state s 2. So, P(s 2) P(s = Ω R(s 2) 1) Ω R (s 1) This is the ratio. So, what is P(s 1 )? (3) (4)

9 Boltzmann Factor- cont. Since S = klnω, Ω = e S/k. Ω R (U E(s 1)) = e S R (s 1 )/k P(s 2) P(s = esr (s2)/k 1) e S R (s 1 )/k = e[s R (s 2 ) S R (s 1 )]/k (5) (6) The difference S R (s 2) S R (s 1) is the entropy change in the reservoir. It must be tiny. So, we can use the thermodynamic identity to find the answer: TdS R = du R + PdV R µdn R (7) dv R Å3 0: Volume change due to re-distribution of particles on microstates dn R = 0, for system consisting of single atom, for example S R (s 2) S R (s 1) = 1 T [U R(s 2) U R (s 1)] = 1 [E(s2) E(s1)] (8) T P(s 2) P(s = 1) e [E(s 2) E(s 1 )]/(kt ) = e E(s2)/(kT ) (9) e E(s 1)/(kT ) Note: Let s see a case in which the PdV is not negligible.

10 Partition Function for a hydrogen atom An example with PdV R being big enough and requires a new Boltzmann Factor: When high-n states are occupied because the approximate radius of the electron wave function is a 0n 2, a 0 = m is the Bohr radius. When keep PdV in ds R = 1 T (du R + PdV R µdn R ), the new Boltzmann Factor becomes (at constant pressure): BoltzmannFactor = e (E+PV )/kt. Atomic model and Energy- level diagram for a hydrogen atom Hydrogen at ground state: PV Pa m ev. When n = 10, PV 10 (10 2 ) 3 PV 0 1 ev. comparing with kt at room temperature: kt ev /K 300 K ev. Low temperature: kt ev /K 1 K ev.

11 Boltzmann Factor- cont. The Boltzmann factor is Rewrite Eq. (9), Boltzmann factor = e E(s)/(kT ) (10) P(s 2) P(s = 1) e [E(s 2) E(s 1 )]/(kt ) = e E(s2)/(kT ) e E(s 1)/(kT ) (11) P(s 2) e = P(s 1) E(s 2)/(kT ) e = 1 = const. E(s 1)/(kT ) Z (12) P(s) = 1 Z e E(s)/(kT ) (13) We arrived at the most useful formula in all of statistical mechanics. Please memorize it. It is also called the Boltzmann distribution, or the canonical distribution.

12 Partition Function Z We arrived at P(s) = 1 Z e E(s)/(kT ) To calculate the probability, we still need to know Z. The formula for Z can be easily obtained by the fact that 1 s P(s) = s 1 Z e E(s)/(kT ) = 1 Z e E(s)/(kT ) (14) s Z = s e E(s)/(kT ) (15) Z is just the sum of all Boltzmann Factors. Several remarks: 1 Z is a constant - independent of particular state s. But it depends on temperature. 2 Assuming the energy of ground state is zero, the Boltzmann Factor of ground state is 1. Boltzmann Factors for excited states are less than 1. 3 At very low temperature, Z 1. 4 At high temperatures, Z can be very big.

13 Boltzmann Factor- Remarks. Several remarks about the Boltzmann factor: 1 For the ratio P(s 2) P(s 1 ) = e [E(s 2) E(s 1 )]/(kt ), only the energy difference E(s 2) E(s 1) makes contributions. 2 We do not have to know anything about the reservoir except that it maintains a constant temperature T. 3 We made the transition from the fundamental assumption for an isolated system to The system of interest which is in thermal equilibrium with the thermal reservoir : The system visits each microstate with a frequency proportional to the Boltzmann factor. 4 An ensemble of identical systems all of which are in contact with the same heat reservoir and distributed over states in accordance with the Boltzmann distribution is called a canonical ensemble.

14 Degenerate energy levels If SEVERAL quantum states of the system (different sets of quantum numbers) correspond to the SAME energy level, this level is called degenerate. The probability to find the system in one of these degenerate states is the same for all the degenerate states. Thus, the total probability to find THE SYSTEM in a state with energy E i is:

15 Degenerate energy levels - cnt. P(E i ) d i e E i /kt where d i is the degree of degeneracy for energy level E i. (16) The partition function should take the form of Z = i d i e E i /kt (17)

16 Two ensembles The Microcanonical ensemble and the canonical ensemble. microcanonical ensemble canonical ensemble For an isolated system, the multiplicity Ω provides the number of accessible microstates. The constraint in calculating the states: U, V, N const P = 1 n Ω For a fixed U, the mean temperature T is specified, but T can fluctuate. - the probability of finding a system in one of the accessible states For a system in thermal contact with reservoir, the partition function Z provides the # of accessible microstates. The constraint: T, V, N const For a fixed T, the mean energy U is specified, but U can fluctuate. Pn = 1 e Z S ( U V, N) = k lnω F( T, V, N) = kb T lnz, B - in equilibrium, S reaches a maximum - in equilibrium, F reaches a minimum En kb T - the probability of finding a system in one of these states For the canonical ensemble, the role of Z is similar to that of the multiplicity Ω for the microcanonical ensemble. F(T,V,N)=f(Z) gives the fundamental relation between statistical mechanics and thermodynamics for given values of T, V, and N, just as S (U,V,N) = S(Ω) gives the fundamental relation between statistical mechanics and thermodynamics for given values of U, V, and N. F: is the Helmholtz Free Energy! We will learn more about the partition function and free energy in later sections.

17 In-Class Exercise Exercise 06-01: Prove that the probability of finding an atom in any particular energy level is P(E) = (1/Z)e F /(kt ), where F = E TS and the entropy of a level is k times the logarithm of the number of degenerate states for that level.

18 In-Class Exercise Three more examples. 1. Exercise 06-02: At very high temperature (as in the very early universe), the proton and the neutron can be thought of as two different states of the same particle, called the nucleon. Since the neutrons mass is higher than the protons by δm = kg, its energy is therefore higher by δmc 2. What was the ratio of the number of protons to the number of neutrons at T = 1011 K? 2. Exercise 06-03: Use Boltzmann factors to derive the exponential formula for the density of an isothermal atmosphere. Assume the temperature T does not vary with z: 3. Thermal excitation of atoms Self-reading, p.226 in textbook.

19 Average Values What is the average value? If the systems in an ensemble are distributed over their accessible states in accordance with the distribution P(s i ), the average value of some quantity x(s i ) can be found as: x = x(s i ) = i x(s i )P(s i ) (18) x = 1 Z i x(s i )e βe(s i ), β = 1 kt. (19) 1 The average value depends on the entire distribution, not just the peak, or the width of the distribution. 2 The average value is an additive quantity: x(s i ) + y(s i ) = i [x(s i) + y(s i )]P(s i ) = i x(s i)p(s i ) + i y(s i)p(s i ) = x(s i ) + y(s i )

20 Useful equations Another useful representation for the average energy: E = i ɛ ip(ɛ i ) = 1 Z i ɛ ie βɛ i, which is E = 1 Z E = 1 Z β i e βɛ i E = 1 Z = lnz Z β β E β=1/kt = lnz = lnz. kt 1 k 2 T It can be written as: E = kt 2 T lnz (kt ) i So, if we know Z = Z(T, V, N,...), we know the average energy! β e βɛ i, which is

21 Useful equations - degenerate energy levels We have learned: P(E i ) d i e E i /kt Z = i d i e E i /kt d i : degree of degeneracy for energy level E i The alternative representation for the average energy in this case (pay attention to d i ): E = i ɛ ip(ɛ i ) = 1 Z i ɛ id i e βɛ i, which is E = 1 Z i d i β e βɛ i, which is E = 1 Z β i d ie βɛ i E = 1 Z = lnz Z β β E β=1/kt = lnz = lnz. kt 1 k (kt ) 2 T This can be written as: E = kt 2 T lnz

22 In-Class Exercise Exercise 06-04a: On fluctuations The most common measure of the fluctuations of a set of numbers away from the average is the standard deviation. E 7eV 4eV 0 A system with 5 particles on 3 energy levels (a) For the system shown above, computer the deviation of the energy from the average energy, δe i = E i Ē, for i = 1, 2,..., 5. (b) Computer the average of the square of the found deviations, (δe i ) 2. Then, computer the square root of this quantity. This quantity is called the root-mean-square (rms) deviation, or standard deviation, noted as σ E.

23 In-Class Exercise (con. from Exercise 06-04a) (c) Prove in general that σe 2 = E 2 (Ē) 2. (d) Check the preceding formula for the five-atom toy model. Exercise 06-04b: (1) For any system in equilibrium with a reservoir at temperature T, prove the average value of E 2 is E 2 = 1 Z 2 Z β 2. (2) Define the root-mean-square (rms) deviation as σ E = (Ei Ē)2, find a formula for σ E in terms of the heat capacity, C = Ē/ T.

24 Paramagnetism Energy +μb B 0 - μb Down Up State Two- state paramagnet: Magne:c dipoles in an external magne:c field (leb) and energy levels of a single dipole (right)

25 Paramagnetsm- cnt. The system has two microstates with energy µb and +µb, where µ is the magnetic moment of the dipoles. Now we can see how easy it is to get the probabilities and mean values: The Partition Function: Z = i e βe(i) = e βµb + e βµb = 2cosh(βµB) (20) The probability of the dipoles being in the up and down state: P = 1 Z e βe = P = 1 Z e βe = e βµb 2cosh(βµB) e βµb 2cosh(βµB) (21) (22)

26 Paramagnetsm- cnt. The average energy: Ē = i E i P Ei = ( µb)p + (µb)p = ( µb)(p P ) Ē = ( µb) eβµb e βµb 2cosh(βµB) The total energy of a collection of N dipoles: = µbtanh(βµb) (23) U = NµBtanh(βµB) (24) The mean value of a dipole s magnetic moment along the direction of the magnetic field B µ B = i µ B (i)p Ei = (+µ)p + ( µ)p µ B = µtanh(βµb) (25) The total magnetization of the sample: M = Nµtanh(βµB) (26)

27 Rotation of Diatomic Molecules E 12e J=3 6e J=2 N states =2J+1 2e 0 J=0 J=1 Energy levels for the rotational states of a diatomic molecule

28 Rotation of Diatomic Molecules - cnt. 1 The allowed rotational energies: E(j) = j(j + 1)ɛ (ɛ is a constant, 1 moment of inertia ) 2 Number of degeneracy: N = 2j + 1 Assume particles occupy all possible j, corresponding to high temperature: Z rot = (2j + 1)e E(j)/kT = (2j + 1)e j(j+1)ɛ/kt (27) Z rot Z rot j=0 0 0 Z rot + kt ɛ j=0 (2j + 1)e j(j+1)ɛ/kt dj = e uɛ/kt du = kt ɛ 0 0 e j(j+1)ɛ/kt d[j(j + 1)] e uɛ/kt d(uɛ/kt ) = kt e uɛ/kt ɛ 0 ( when kt ɛ). (28)

29 Mean rotational energy at high temperatures ɛ is called rotational constant. It is inversely proportional to the molecule s moment of inertia. For molecules consisting of same atoms, such as N 2, O 2, etc.? Z rot + kt (for identical atoms when kt ɛ). (29) 2ɛ Now we can calculate the average rotational energy of a molecule at high temperatures: < E rot >= 1 Z Z β 1 = ɛβ ɛβ = 1 = kt (30) 2 β For molecules consisting of same atoms, such as N 2, O 2, degree of degeneracy reduces by a factor of 2. The partition function is: Z rot + kt = 1 (for identical atoms when kt ɛ). 2ɛ 2ɛβ Four things to address: < E rot >= 1 Z Z β 1 = 2ɛβ 2ɛβ = 1 = kt (31) 2 β

30 Mean rotational energy at high temperatures - cnt. At high T, the average rotational energy (thus the heat capacity) is the same for identical particle system. At lower T, things are more complicated when multiple particle may fight to occupy single particle states. Strict treatment of Eq. (27) will be needed. Quantum effects will appear. We will learn how to handle this in Chapter 7. We can also use E = kt 2 lnz to calculate the mean rotational T energy: < E rot > kt 2 T ln kt ɛ < E rot > kt 2 1 k kt ɛ ɛ < E rot > kt, ( when kt ɛ). (32)

31 System with more degrees of freedom A non-spherical nuclear: Two types of motions Mean field single particle states (n, l, s; Z singl. ). Rotation of the nucleus : collective rotational states (J, Z rot). What is the partition function? P(E singl. ) d i e E i /kt Z singl. = i d i e E i /kt P(E col. ) d j e E j /kt Z col. = j d j e E j /kt P(E singl., E col. ) = P(E singl. ) P(E col. ) = 1 Z singl. d i e E i /kt 1 Z col. d j e E j /kt P(E singl., E col. ) = 1 Z singl. Z col. d i d j e (E i +E j )/kt Therefore, the partition function of the system is: Example: Problem 6.48, p.255 in the textbook. Z = Z singl. Z col.

32 The Equipartition Theorem The Equipartition theorem (Chapter 1): At temperature T, the average energy of any quadratic degree of freedom is 1 kt. - This can be proved based on 2 principles in Statistical Physics which we will learn later in this semester. For a system with N particles, each with f DoF, and there is NO other non-quadratic temperature-dependent forms of energy, the total thermal energy in the system is I also made the following remarks: U thermal = Nf 1 kt (33) 2 It only applies to systems in which the energy is in the form of quadratic degree of freedom: E(q) = cq 2. It is about thermal energy of the system - those changes with temperature, not the total energy. Degree of freedom: different systems require specific analysis: vibration, rotation,... The NDoF of a system may also vary as temperature changes.

33 The Equipartition Theorem Here we give a proof using Boltzmann factors. Consider a system with single degree of freedom. Z = q exp( βe(q)) = q exp( βcq 2 ) (34) Z = 1 δq Z = 1 δq Z = exp( βcq 2 )δq (35) q + 1 δq βc 1 Z = δq βc Z = 1 δq + exp( βcq 2 )dq (36) + exp[ ( βcq) 2 ]d( βcq) exp( u 2 )du (37) π βc = Cβ 1/2, C = π/c δq (38)

34 The Equipartition Theorem Now, we can use E = 1 Z β Z Ē = 1 Cβ 1/2 β Cβ 1/2 (39) This is the Equipartition Theorem for 1-DoF system. Ē = 1 β 1/2 1 2 β 3/2 (40) Ē = 1 2 β 1 = 1 kt (41) 2 (42) Next time, we will continue our discussion about the partition function, its relation with free energy, and what it looks like for composite systems.

Part II: Statistical Physics

Part II: Statistical Physics Chapter 6: Boltzmann Statistics SDSMT, Physics Fall Semester: Oct. - Dec., 2013 1 Introduction: Very brief 2 Boltzmann Factor Isolated System and System of Interest Boltzmann Factor The Partition Function

More information

Part II: Statistical Physics

Part II: Statistical Physics Chapter 7: Quantum Statistics SDSMT, Physics 2013 Fall 1 Introduction 2 The Gibbs Factor Gibbs Factor Several examples 3 Quantum Statistics From high T to low T From Particle States to Occupation Numbers

More information

(# = %(& )(* +,(- Closed system, well-defined energy (or e.g. E± E/2): Microcanonical ensemble

(# = %(& )(* +,(- Closed system, well-defined energy (or e.g. E± E/2): Microcanonical ensemble Recall from before: Internal energy (or Entropy): &, *, - (# = %(& )(* +,(- Closed system, well-defined energy (or e.g. E± E/2): Microcanonical ensemble & = /01Ω maximized Ω: fundamental statistical quantity

More information

Physics 333, Thermal and Statistical Physics: Homework #2 Solutions Manual

Physics 333, Thermal and Statistical Physics: Homework #2 Solutions Manual Physics 333, Thermal and Statistical Physics: Homework #2 Solutions Manual 1. n 5 = 0 n 5 = 1 n 5 = 2 n 5 = 3 n 5 = 4 n 5 = 5 d n 5,0,0,0,0 4 0 0 0 0 1 5 4,1,0,0,0 12 4 0 0 4 0 20 3,2,0,0,0 12 0 4 4 0

More information

Outline Review Example Problem 1 Example Problem 2. Thermodynamics. Review and Example Problems. X Bai. SDSMT, Physics. Fall 2013

Outline Review Example Problem 1 Example Problem 2. Thermodynamics. Review and Example Problems. X Bai. SDSMT, Physics. Fall 2013 Review and Example Problems SDSMT, Physics Fall 013 1 Review Example Problem 1 Exponents of phase transformation 3 Example Problem Application of Thermodynamic Identity : contents 1 Basic Concepts: Temperature,

More information

Outline Review Example Problem 1. Thermodynamics. Review and Example Problems: Part-2. X Bai. SDSMT, Physics. Fall 2014

Outline Review Example Problem 1. Thermodynamics. Review and Example Problems: Part-2. X Bai. SDSMT, Physics. Fall 2014 Review and Example Problems: Part- SDSMT, Physics Fall 014 1 Review Example Problem 1 Exponents of phase transformation : contents 1 Basic Concepts: Temperature, Work, Energy, Thermal systems, Ideal Gas,

More information

Introduction Statistical Thermodynamics. Monday, January 6, 14

Introduction Statistical Thermodynamics. Monday, January 6, 14 Introduction Statistical Thermodynamics 1 Molecular Simulations Molecular dynamics: solve equations of motion Monte Carlo: importance sampling r 1 r 2 r n MD MC r 1 r 2 2 r n 2 3 3 4 4 Questions How can

More information

Phys Midterm. March 17

Phys Midterm. March 17 Phys 7230 Midterm March 17 Consider a spin 1/2 particle fixed in space in the presence of magnetic field H he energy E of such a system can take one of the two values given by E s = µhs, where µ is the

More information

Chapter 4: Going from microcanonical to canonical ensemble, from energy to temperature.

Chapter 4: Going from microcanonical to canonical ensemble, from energy to temperature. Chapter 4: Going from microcanonical to canonical ensemble, from energy to temperature. All calculations in statistical mechanics can be done in the microcanonical ensemble, where all copies of the system

More information

PHYS 352 Homework 2 Solutions

PHYS 352 Homework 2 Solutions PHYS 352 Homework 2 Solutions Aaron Mowitz (, 2, and 3) and Nachi Stern (4 and 5) Problem The purpose of doing a Legendre transform is to change a function of one or more variables into a function of variables

More information

Physics 213 Spring 2009 Midterm exam. Review Lecture

Physics 213 Spring 2009 Midterm exam. Review Lecture Physics 213 Spring 2009 Midterm exam Review Lecture The next two questions pertain to the following situation. A container of air (primarily nitrogen and oxygen molecules) is initially at 300 K and atmospheric

More information

Physics 408 Final Exam

Physics 408 Final Exam Physics 408 Final Exam Name You are graded on your work (with partial credit where it is deserved) so please do not just write down answers with no explanation (or skip important steps)! Please give clear,

More information

Statistical thermodynamics for MD and MC simulations

Statistical thermodynamics for MD and MC simulations Statistical thermodynamics for MD and MC simulations knowing 2 atoms and wishing to know 10 23 of them Marcus Elstner and Tomáš Kubař 22 June 2016 Introduction Thermodynamic properties of molecular systems

More information

to satisfy the large number approximations, W W sys can be small.

to satisfy the large number approximations, W W sys can be small. Chapter 12. The canonical ensemble To discuss systems at constant T, we need to embed them with a diathermal wall in a heat bath. Note that only the system and bath need to be large for W tot and W bath

More information

Thermal and Statistical Physics Department Exam Last updated November 4, L π

Thermal and Statistical Physics Department Exam Last updated November 4, L π Thermal and Statistical Physics Department Exam Last updated November 4, 013 1. a. Define the chemical potential µ. Show that two systems are in diffusive equilibrium if µ 1 =µ. You may start with F =

More information

Lecture 9 Overview (Ch. 1-3)

Lecture 9 Overview (Ch. 1-3) Lecture 9 Overview (Ch. -) Format of the first midterm: four problems with multiple questions. he Ideal Gas Law, calculation of δw, δq and ds for various ideal gas processes. Einstein solid and two-state

More information

Statistical thermodynamics L1-L3. Lectures 11, 12, 13 of CY101

Statistical thermodynamics L1-L3. Lectures 11, 12, 13 of CY101 Statistical thermodynamics L1-L3 Lectures 11, 12, 13 of CY101 Need for statistical thermodynamics Microscopic and macroscopic world Distribution of energy - population Principle of equal a priori probabilities

More information

Thermodynamics & Statistical Mechanics

Thermodynamics & Statistical Mechanics hysics GRE: hermodynamics & Statistical Mechanics G. J. Loges University of Rochester Dept. of hysics & Astronomy xkcd.com/66/ c Gregory Loges, 206 Contents Ensembles 2 Laws of hermodynamics 3 hermodynamic

More information

Lecture 8. The Second Law of Thermodynamics; Energy Exchange

Lecture 8. The Second Law of Thermodynamics; Energy Exchange Lecture 8 The Second Law of Thermodynamics; Energy Exchange The second law of thermodynamics Statistics of energy exchange General definition of temperature Why heat flows from hot to cold Reading for

More information

9.1 System in contact with a heat reservoir

9.1 System in contact with a heat reservoir Chapter 9 Canonical ensemble 9. System in contact with a heat reservoir We consider a small system A characterized by E, V and N in thermal interaction with a heat reservoir A 2 characterized by E 2, V

More information

1. Thermodynamics 1.1. A macroscopic view of matter

1. Thermodynamics 1.1. A macroscopic view of matter 1. Thermodynamics 1.1. A macroscopic view of matter Intensive: independent of the amount of substance, e.g. temperature,pressure. Extensive: depends on the amount of substance, e.g. internal energy, enthalpy.

More information

(i) T, p, N Gibbs free energy G (ii) T, p, µ no thermodynamic potential, since T, p, µ are not independent of each other (iii) S, p, N Enthalpy H

(i) T, p, N Gibbs free energy G (ii) T, p, µ no thermodynamic potential, since T, p, µ are not independent of each other (iii) S, p, N Enthalpy H Solutions exam 2 roblem 1 a Which of those quantities defines a thermodynamic potential Why? 2 points i T, p, N Gibbs free energy G ii T, p, µ no thermodynamic potential, since T, p, µ are not independent

More information

Advanced Thermodynamics. Jussi Eloranta (Updated: January 22, 2018)

Advanced Thermodynamics. Jussi Eloranta (Updated: January 22, 2018) Advanced Thermodynamics Jussi Eloranta (jmeloranta@gmail.com) (Updated: January 22, 2018) Chapter 1: The machinery of statistical thermodynamics A statistical model that can be derived exactly from the

More information

Recitation: 10 11/06/03

Recitation: 10 11/06/03 Recitation: 10 11/06/03 Ensembles and Relation to T.D. It is possible to expand both sides of the equation with F = kt lnq Q = e βe i If we expand both sides of this equation, we apparently obtain: i F

More information

Statistical Physics. The Second Law. Most macroscopic processes are irreversible in everyday life.

Statistical Physics. The Second Law. Most macroscopic processes are irreversible in everyday life. Statistical Physics he Second Law ime s Arrow Most macroscopic processes are irreversible in everyday life. Glass breaks but does not reform. Coffee cools to room temperature but does not spontaneously

More information

ChE 210B: Advanced Topics in Equilibrium Statistical Mechanics

ChE 210B: Advanced Topics in Equilibrium Statistical Mechanics ChE 210B: Advanced Topics in Equilibrium Statistical Mechanics Glenn Fredrickson Lecture 1 Reading: 3.1-3.5 Chandler, Chapters 1 and 2 McQuarrie This course builds on the elementary concepts of statistical

More information

[S R (U 0 ɛ 1 ) S R (U 0 ɛ 2 ]. (0.1) k B

[S R (U 0 ɛ 1 ) S R (U 0 ɛ 2 ]. (0.1) k B Canonical ensemble (Two derivations) Determine the probability that a system S in contact with a reservoir 1 R to be in one particular microstate s with energy ɛ s. (If there is degeneracy we are picking

More information

Atkins / Paula Physical Chemistry, 8th Edition. Chapter 16. Statistical thermodynamics 1: the concepts

Atkins / Paula Physical Chemistry, 8th Edition. Chapter 16. Statistical thermodynamics 1: the concepts Atkins / Paula Physical Chemistry, 8th Edition Chapter 16. Statistical thermodynamics 1: the concepts The distribution of molecular states 16.1 Configurations and weights 16.2 The molecular partition function

More information

Chapter 3. Entropy, temperature, and the microcanonical partition function: how to calculate results with statistical mechanics.

Chapter 3. Entropy, temperature, and the microcanonical partition function: how to calculate results with statistical mechanics. Chapter 3. Entropy, temperature, and the microcanonical partition function: how to calculate results with statistical mechanics. The goal of equilibrium statistical mechanics is to calculate the density

More information

The canonical ensemble

The canonical ensemble The canonical ensemble Anders Malthe-Sørenssen 23. september 203 Boltzmann statistics We have so far studied systems with constant N, V, and E systems in the microcanonical ensemble. Such systems are often

More information

MASSACHUSETTS INSTITUTE OF TECHNOLOGY Physics Department Statistical Physics I Spring Term Solutions to Problem Set #10

MASSACHUSETTS INSTITUTE OF TECHNOLOGY Physics Department Statistical Physics I Spring Term Solutions to Problem Set #10 MASSACHUSES INSIUE OF ECHNOLOGY Physics Department 8.044 Statistical Physics I Spring erm 203 Problem : wo Identical Particles Solutions to Problem Set #0 a) Fermions:,, 0 > ɛ 2 0 state, 0, > ɛ 3 0,, >

More information

Grand Canonical Formalism

Grand Canonical Formalism Grand Canonical Formalism Grand Canonical Ensebmle For the gases of ideal Bosons and Fermions each single-particle mode behaves almost like an independent subsystem, with the only reservation that the

More information

MASSACHUSETTS INSTITUTE OF TECHNOLOGY Physics Department Statistical Physics I Spring Term 2013 Notes on the Microcanonical Ensemble

MASSACHUSETTS INSTITUTE OF TECHNOLOGY Physics Department Statistical Physics I Spring Term 2013 Notes on the Microcanonical Ensemble MASSACHUSETTS INSTITUTE OF TECHNOLOGY Physics Department 8.044 Statistical Physics I Spring Term 2013 Notes on the Microcanonical Ensemble The object of this endeavor is to impose a simple probability

More information

Physics 172H Modern Mechanics

Physics 172H Modern Mechanics Physics 172H Modern Mechanics Instructor: Dr. Mark Haugan Office: PHYS 282 haugan@purdue.edu TAs: Alex Kryzwda John Lorenz akryzwda@purdue.edu jdlorenz@purdue.edu Lecture 22: Matter & Interactions, Ch.

More information

2. Thermodynamics. Introduction. Understanding Molecular Simulation

2. Thermodynamics. Introduction. Understanding Molecular Simulation 2. Thermodynamics Introduction Molecular Simulations Molecular dynamics: solve equations of motion r 1 r 2 r n Monte Carlo: importance sampling r 1 r 2 r n How do we know our simulation is correct? Molecular

More information

The Ideal Gas. One particle in a box:

The Ideal Gas. One particle in a box: IDEAL GAS The Ideal Gas It is an important physical example that can be solved exactly. All real gases behave like ideal if the density is small enough. In order to derive the law, we have to do following:

More information

Lecture 8. The Second Law of Thermodynamics; Energy Exchange

Lecture 8. The Second Law of Thermodynamics; Energy Exchange Lecture 8 The Second Law of Thermodynamics; Energy Exchange The second law of thermodynamics Statistics of energy exchange General definition of temperature Why heat flows from hot to cold Reading for

More information

Chapter 20 The Second Law of Thermodynamics

Chapter 20 The Second Law of Thermodynamics Chapter 20 The Second Law of Thermodynamics When we previously studied the first law of thermodynamics, we observed how conservation of energy provided us with a relationship between U, Q, and W, namely

More information

We already came across a form of indistinguishably in the canonical partition function: V N Q =

We already came across a form of indistinguishably in the canonical partition function: V N Q = Bosons en fermions Indistinguishability We already came across a form of indistinguishably in the canonical partition function: for distinguishable particles Q = Λ 3N βe p r, r 2,..., r N ))dτ dτ 2...

More information

Physics 132- Fundamentals of Physics for Biologists II

Physics 132- Fundamentals of Physics for Biologists II Physics 132- Fundamentals of Physics for Biologists II Statistical Physics and Thermodynamics It s all about energy Classifying Energy Kinetic Energy Potential Energy Macroscopic Energy Moving baseball

More information

summary of statistical physics

summary of statistical physics summary of statistical physics Matthias Pospiech University of Hannover, Germany Contents 1 Probability moments definitions 3 2 bases of thermodynamics 4 2.1 I. law of thermodynamics..........................

More information

Entropy and Free Energy in Biology

Entropy and Free Energy in Biology Entropy and Free Energy in Biology Energy vs. length from Phillips, Quake. Physics Today. 59:38-43, 2006. kt = 0.6 kcal/mol = 2.5 kj/mol = 25 mev typical protein typical cell Thermal effects = deterministic

More information

140a Final Exam, Fall 2007., κ T 1 V P. (? = P or V ), γ C P C V H = U + PV, F = U TS G = U + PV TS. T v. v 2 v 1. exp( 2πkT.

140a Final Exam, Fall 2007., κ T 1 V P. (? = P or V ), γ C P C V H = U + PV, F = U TS G = U + PV TS. T v. v 2 v 1. exp( 2πkT. 4a Final Exam, Fall 27 Data: P 5 Pa, R = 8.34 3 J/kmol K = N A k, N A = 6.2 26 particles/kilomole, T C = T K 273.5. du = TdS PdV + i µ i dn i, U = TS PV + i µ i N i Defs: 2 β ( ) V V T ( ) /dq C? dt P?

More information

213 Midterm coming up

213 Midterm coming up 213 Midterm coming up Monday April 8 @ 7 pm (conflict exam @ 5:15pm) Covers: Lectures 1-12 (not including thermal radiation) HW 1-4 Discussion 1-4 Labs 1-2 Review Session Sunday April 7, 3-5 PM, 141 Loomis

More information

Statistical Mechanics

Statistical Mechanics Statistical Mechanics Newton's laws in principle tell us how anything works But in a system with many particles, the actual computations can become complicated. We will therefore be happy to get some 'average'

More information

Entropy and Free Energy in Biology

Entropy and Free Energy in Biology Entropy and Free Energy in Biology Energy vs. length from Phillips, Quake. Physics Today. 59:38-43, 2006. kt = 0.6 kcal/mol = 2.5 kj/mol = 25 mev typical protein typical cell Thermal effects = deterministic

More information

Data Provided: A formula sheet and table of physical constants are attached to this paper.

Data Provided: A formula sheet and table of physical constants are attached to this paper. Data Provided: A formula sheet and table of physical constants are attached to this paper. DEPARTMENT OF PHYSICS AND ASTRONOMY Spring Semester (2016-2017) From Thermodynamics to Atomic and Nuclear Physics

More information

Statistical. mechanics

Statistical. mechanics CHAPTER 15 Statistical Thermodynamics 1: The Concepts I. Introduction. A. Statistical mechanics is the bridge between microscopic and macroscopic world descriptions of nature. Statistical mechanics macroscopic

More information

5. Systems in contact with a thermal bath

5. Systems in contact with a thermal bath 5. Systems in contact with a thermal bath So far, isolated systems (micro-canonical methods) 5.1 Constant number of particles:kittel&kroemer Chap. 3 Boltzmann factor Partition function (canonical methods)

More information

Removing the mystery of entropy and thermodynamics. Part 3

Removing the mystery of entropy and thermodynamics. Part 3 Removing the mystery of entropy and thermodynamics. Part 3 arvey S. Leff a,b Physics Department Reed College, Portland, Oregon USA August 3, 20 Introduction In Part 3 of this five-part article, [, 2] simple

More information

UNIVERSITY OF SOUTHAMPTON

UNIVERSITY OF SOUTHAMPTON UNIVERSITY OF SOUTHAMPTON PHYS1013W1 SEMESTER 2 EXAMINATION 2014-2015 ENERGY AND MATTER Duration: 120 MINS (2 hours) This paper contains 8 questions. Answers to Section A and Section B must be in separate

More information

763620SS STATISTICAL PHYSICS Solutions 5 Autumn 2012

763620SS STATISTICAL PHYSICS Solutions 5 Autumn 2012 7660SS STATISTICAL PHYSICS Solutions 5 Autumn 01 1 Classical Flow in Phase Space Determine the trajectories of classical Hamiltonian flow in -dim corresponding to a particle in a constant gravitational

More information

PHYS3113, 3d year Statistical Mechanics Tutorial problems. Tutorial 1, Microcanonical, Canonical and Grand Canonical Distributions

PHYS3113, 3d year Statistical Mechanics Tutorial problems. Tutorial 1, Microcanonical, Canonical and Grand Canonical Distributions 1 PHYS3113, 3d year Statistical Mechanics Tutorial problems Tutorial 1, Microcanonical, Canonical and Grand Canonical Distributions Problem 1 The macrostate probability in an ensemble of N spins 1/2 is

More information

PHY 5524: Statistical Mechanics, Spring February 11 th, 2013 Midterm Exam # 1

PHY 5524: Statistical Mechanics, Spring February 11 th, 2013 Midterm Exam # 1 PHY 554: Statistical Mechanics, Spring 013 February 11 th, 013 Midterm Exam # 1 Always remember to write full work for what you do. This will help your grade in case of incomplete or wrong answers. Also,

More information

Physics 132- Fundamentals of Physics for Biologists II. Statistical Physics and Thermodynamics

Physics 132- Fundamentals of Physics for Biologists II. Statistical Physics and Thermodynamics Physics 132- Fundamentals of Physics for Biologists II Statistical Physics and Thermodynamics QUIZ 2 25 Quiz 2 20 Number of Students 15 10 5 AVG: STDEV: 5.15 2.17 0 0 2 4 6 8 10 Score 1. (4 pts) A 200

More information

1 Foundations of statistical physics

1 Foundations of statistical physics 1 Foundations of statistical physics 1.1 Density operators In quantum mechanics we assume that the state of a system is described by some vector Ψ belonging to a Hilbert space H. If we know the initial

More information

Chapter 18 Thermal Properties of Matter

Chapter 18 Thermal Properties of Matter Chapter 18 Thermal Properties of Matter In this section we define the thermodynamic state variables and their relationship to each other, called the equation of state. The system of interest (most of the

More information

MP203 Statistical and Thermal Physics. Jon-Ivar Skullerud and James Smith

MP203 Statistical and Thermal Physics. Jon-Ivar Skullerud and James Smith MP203 Statistical and Thermal Physics Jon-Ivar Skullerud and James Smith October 3, 2017 1 Contents 1 Introduction 3 1.1 Temperature and thermal equilibrium.................... 4 1.1.1 The zeroth law of

More information

Physics 607 Final Exam

Physics 607 Final Exam Physics 67 Final Exam Please be well-organized, and show all significant steps clearly in all problems. You are graded on your work, so please do not just write down answers with no explanation! Do all

More information

Physics 4230 Final Examination 10 May 2007

Physics 4230 Final Examination 10 May 2007 Physics 43 Final Examination May 7 In each problem, be sure to give the reasoning for your answer and define any variables you create. If you use a general formula, state that formula clearly before manipulating

More information

Statistical Mechanics Notes. Ryan D. Reece

Statistical Mechanics Notes. Ryan D. Reece Statistical Mechanics Notes Ryan D. Reece August 11, 2006 Contents 1 Thermodynamics 3 1.1 State Variables.......................... 3 1.2 Inexact Differentials....................... 5 1.3 Work and Heat..........................

More information

arxiv:cond-mat/ v1 10 Aug 2002

arxiv:cond-mat/ v1 10 Aug 2002 Model-free derivations of the Tsallis factor: constant heat capacity derivation arxiv:cond-mat/0208205 v1 10 Aug 2002 Abstract Wada Tatsuaki Department of Electrical and Electronic Engineering, Ibaraki

More information

Some properties of the Helmholtz free energy

Some properties of the Helmholtz free energy Some properties of the Helmholtz free energy Energy slope is T U(S, ) From the properties of U vs S, it is clear that the Helmholtz free energy is always algebraically less than the internal energy U.

More information

Preliminary Examination - Day 2 August 15, 2014

Preliminary Examination - Day 2 August 15, 2014 UNL - Department of Physics and Astronomy Preliminary Examination - Day 2 August 15, 2014 This test covers the topics of Thermodynamics and Statistical Mechanics (Topic 1) and Mechanics (Topic 2). Each

More information

University of Illinois at Chicago Department of Physics SOLUTIONS. Thermodynamics and Statistical Mechanics Qualifying Examination

University of Illinois at Chicago Department of Physics SOLUTIONS. Thermodynamics and Statistical Mechanics Qualifying Examination University of Illinois at Chicago Department of Physics SOLUTIONS Thermodynamics and Statistical Mechanics Qualifying Eamination January 7, 2 9: AM to 2: Noon Full credit can be achieved from completely

More information

2m + U( q i), (IV.26) i=1

2m + U( q i), (IV.26) i=1 I.D The Ideal Gas As discussed in chapter II, micro-states of a gas of N particles correspond to points { p i, q i }, in the 6N-dimensional phase space. Ignoring the potential energy of interactions, the

More information

Phase Equilibria and Molecular Solutions Jan G. Korvink and Evgenii Rudnyi IMTEK Albert Ludwig University Freiburg, Germany

Phase Equilibria and Molecular Solutions Jan G. Korvink and Evgenii Rudnyi IMTEK Albert Ludwig University Freiburg, Germany Phase Equilibria and Molecular Solutions Jan G. Korvink and Evgenii Rudnyi IMTEK Albert Ludwig University Freiburg, Germany Preliminaries Learning Goals Phase Equilibria Phase diagrams and classical thermodynamics

More information

Part II Statistical Physics

Part II Statistical Physics Part II Statistical Physics Theorems Based on lectures by H. S. Reall Notes taken by Dexter Chua Lent 2017 These notes are not endorsed by the lecturers, and I have modified them (often significantly)

More information

A Brief Introduction to Statistical Mechanics

A Brief Introduction to Statistical Mechanics A Brief Introduction to Statistical Mechanics E. J. Maginn, J. K. Shah Department of Chemical and Biomolecular Engineering University of Notre Dame Notre Dame, IN 46556 USA Monte Carlo Workshop Universidade

More information

Contents. 1 Introduction and guide for this text 1. 2 Equilibrium and entropy 6. 3 Energy and how the microscopic world works 21

Contents. 1 Introduction and guide for this text 1. 2 Equilibrium and entropy 6. 3 Energy and how the microscopic world works 21 Preface Reference tables Table A Counting and combinatorics formulae Table B Useful integrals, expansions, and approximations Table C Extensive thermodynamic potentials Table D Intensive per-particle thermodynamic

More information

IV. Classical Statistical Mechanics

IV. Classical Statistical Mechanics IV. Classical Statistical Mechanics IV.A General Definitions Statistical Mechanics is a probabilistic approach to equilibrium macroscopic properties of large numbers of degrees of freedom. As discussed

More information

ChE 503 A. Z. Panagiotopoulos 1

ChE 503 A. Z. Panagiotopoulos 1 ChE 503 A. Z. Panagiotopoulos 1 STATISTICAL MECHANICAL ENSEMLES 1 MICROSCOPIC AND MACROSCOPIC ARIALES The central question in Statistical Mechanics can be phrased as follows: If particles (atoms, molecules,

More information

5. Systems in contact with a thermal bath

5. Systems in contact with a thermal bath 5. Systems in contact with a thermal bath So far, isolated systems (micro-canonical methods) 5.1 Constant number of particles:kittel&kroemer Chap. 3 Boltzmann factor Partition function (canonical methods)

More information

Introduction. Statistical physics: microscopic foundation of thermodynamics degrees of freedom 2 3 state variables!

Introduction. Statistical physics: microscopic foundation of thermodynamics degrees of freedom 2 3 state variables! Introduction Thermodynamics: phenomenological description of equilibrium bulk properties of matter in terms of only a few state variables and thermodynamical laws. Statistical physics: microscopic foundation

More information

Thermodynamics: Chapter 02 The Second Law of Thermodynamics: Microscopic Foundation of Thermodynamics. September 10, 2013

Thermodynamics: Chapter 02 The Second Law of Thermodynamics: Microscopic Foundation of Thermodynamics. September 10, 2013 Thermodynamics: Chapter 02 The Second Law of Thermodynamics: Microscopic Foundation of Thermodynamics September 10, 2013 We have talked about some basic concepts in thermodynamics, T, W, Q, C,.... Some

More information

Elements of Statistical Mechanics

Elements of Statistical Mechanics Elements of Statistical Mechanics Thermodynamics describes the properties of macroscopic bodies. Statistical mechanics allows us to obtain the laws of thermodynamics from the laws of mechanics, classical

More information

Physics 607 Exam 2. ( ) = 1, Γ( z +1) = zγ( z) x n e x2 dx = 1. e x2

Physics 607 Exam 2. ( ) = 1, Γ( z +1) = zγ( z) x n e x2 dx = 1. e x2 Physics 607 Exam Please be well-organized, and show all significant steps clearly in all problems. You are graded on your work, so please do not just write down answers with no explanation! Do all your

More information

Statistical Mechanics in a Nutshell

Statistical Mechanics in a Nutshell Chapter 2 Statistical Mechanics in a Nutshell Adapted from: Understanding Molecular Simulation Daan Frenkel and Berend Smit Academic Press (2001) pp. 9-22 11 2.1 Introduction In this course, we will treat

More information

i=1 n i, the canonical probabilities of the micro-states [ βǫ i=1 e βǫn 1 n 1 =0 +Nk B T Nǫ 1 + e ǫ/(k BT), (IV.75) E = F + TS =

i=1 n i, the canonical probabilities of the micro-states [ βǫ i=1 e βǫn 1 n 1 =0 +Nk B T Nǫ 1 + e ǫ/(k BT), (IV.75) E = F + TS = IV.G Examples The two examples of sections (IV.C and (IV.D are now reexamined in the canonical ensemble. 1. Two level systems: The impurities are described by a macro-state M (T,. Subject to the Hamiltonian

More information

Chapter 7: Quantum Statistics

Chapter 7: Quantum Statistics Part II: Applications SDSMT, Physics 2014 Fall 1 Introduction Photons, E.M. Radiation 2 Blackbody Radiation The Ultraviolet Catastrophe 3 Thermal Quantities of Photon System Total Energy Entropy 4 Radiation

More information

a. 4.2x10-4 m 3 b. 5.5x10-4 m 3 c. 1.2x10-4 m 3 d. 1.4x10-5 m 3 e. 8.8x10-5 m 3

a. 4.2x10-4 m 3 b. 5.5x10-4 m 3 c. 1.2x10-4 m 3 d. 1.4x10-5 m 3 e. 8.8x10-5 m 3 The following two problems refer to this situation: #1 A cylindrical chamber containing an ideal diatomic gas is sealed by a movable piston with cross-sectional area A = 0.0015 m 2. The volume of the chamber

More information

140a Final Exam, Fall 2006., κ T 1 V P. (? = P or V ), γ C P C V H = U + PV, F = U TS G = U + PV TS. T v. v 2 v 1. exp( 2πkT.

140a Final Exam, Fall 2006., κ T 1 V P. (? = P or V ), γ C P C V H = U + PV, F = U TS G = U + PV TS. T v. v 2 v 1. exp( 2πkT. 40a Final Exam, Fall 2006 Data: P 0 0 5 Pa, R = 8.34 0 3 J/kmol K = N A k, N A = 6.02 0 26 particles/kilomole, T C = T K 273.5. du = TdS PdV + i µ i dn i, U = TS PV + i µ i N i Defs: 2 β ( ) V V T ( )

More information

Thermal & Statistical Physics Study Questions for the Spring 2018 Department Exam December 6, 2017

Thermal & Statistical Physics Study Questions for the Spring 2018 Department Exam December 6, 2017 Thermal & Statistical Physics Study Questions for the Spring 018 Department Exam December 6, 017 1. a. Define the chemical potential. Show that two systems are in diffusive equilibrium if 1. You may start

More information

Physics 607 Final Exam

Physics 607 Final Exam Physics 607 Final Exam Please be well-organized, and show all significant steps clearly in all problems You are graded on your work, so please do not ust write down answers with no explanation! o state

More information

PHY214 Thermal & Kinetic Physics Duration: 2 hours 30 minutes

PHY214 Thermal & Kinetic Physics Duration: 2 hours 30 minutes BSc Examination by course unit. Friday 5th May 01 10:00 1:30 PHY14 Thermal & Kinetic Physics Duration: hours 30 minutes YOU ARE NOT PERMITTED TO READ THE CONTENTS OF THIS QUESTION PAPER UNTIL INSTRUCTED

More information

An Outline of (Classical) Statistical Mechanics and Related Concepts in Machine Learning

An Outline of (Classical) Statistical Mechanics and Related Concepts in Machine Learning An Outline of (Classical) Statistical Mechanics and Related Concepts in Machine Learning Chang Liu Tsinghua University June 1, 2016 1 / 22 What is covered What is Statistical mechanics developed for? What

More information

UNIVERSITY COLLEGE LONDON. University of London EXAMINATION FOR INTERNAL STUDENTS. For The Following Qualifications:-

UNIVERSITY COLLEGE LONDON. University of London EXAMINATION FOR INTERNAL STUDENTS. For The Following Qualifications:- UNIVERSITY COLLEGE LONDON University of London EXAMINATION FOR INTERNAL STUDENTS For The Following Qualifications:- B.Sc. M.Sci. Statistical Thermodynamics COURSE CODE : PHAS2228 UNIT VALUE : 0.50 DATE

More information

Energy Barriers and Rates - Transition State Theory for Physicists

Energy Barriers and Rates - Transition State Theory for Physicists Energy Barriers and Rates - Transition State Theory for Physicists Daniel C. Elton October 12, 2013 Useful relations 1 cal = 4.184 J 1 kcal mole 1 = 0.0434 ev per particle 1 kj mole 1 = 0.0104 ev per particle

More information

1 The fundamental equation of equilibrium statistical mechanics. 3 General overview on the method of ensembles 10

1 The fundamental equation of equilibrium statistical mechanics. 3 General overview on the method of ensembles 10 Contents EQUILIBRIUM STATISTICAL MECHANICS 1 The fundamental equation of equilibrium statistical mechanics 2 2 Conjugate representations 6 3 General overview on the method of ensembles 10 4 The relation

More information

(a) How much work is done by the gas? (b) Assuming the gas behaves as an ideal gas, what is the final temperature? V γ+1 2 V γ+1 ) pdv = K 1 γ + 1

(a) How much work is done by the gas? (b) Assuming the gas behaves as an ideal gas, what is the final temperature? V γ+1 2 V γ+1 ) pdv = K 1 γ + 1 P340: hermodynamics and Statistical Physics, Exam#, Solution. (0 point) When gasoline explodes in an automobile cylinder, the temperature is about 2000 K, the pressure is is 8.0 0 5 Pa, and the volume

More information

Statistical Mechanics and Information Theory

Statistical Mechanics and Information Theory 1 Multi-User Information Theory 2 Oct 31, 2013 Statistical Mechanics and Information Theory Lecturer: Dror Vinkler Scribe: Dror Vinkler I. INTRODUCTION TO STATISTICAL MECHANICS In order to see the need

More information

Results of. Midterm 1. Points < Grade C D,F C B points.

Results of. Midterm 1. Points < Grade C D,F C B points. esults of Midterm 0 0 0 0 40 50 60 70 80 90 points Grade C D,F oints A 80-95 + 70-79 55-69 C + 45-54 0-44

More information

although Boltzmann used W instead of Ω for the number of available states.

although Boltzmann used W instead of Ω for the number of available states. Lecture #13 1 Lecture 13 Obectives: 1. Ensembles: Be able to list the characteristics of the following: (a) icrocanonical (b) Canonical (c) Grand Canonical 2. Be able to use Lagrange s method of undetermined

More information

THE UNIVERSITY OF NEW SOUTH WALES SCHOOL OF PHYSICS FINAL EXAMINATION JUNE 2010 PHYS3020. Statistical Physics

THE UNIVERSITY OF NEW SOUTH WALES SCHOOL OF PHYSICS FINAL EXAMINATION JUNE 2010 PHYS3020. Statistical Physics THE UNIVERSITY OF NEW SOUTH WALES SCHOOL OF PHYSICS FINAL EXAMINATION JUNE 2010 PHYS3020 Statistical Physics Time Allowed - 2 hours Total number of questions - 5 Answer ALL questions All questions ARE

More information

ME 501. Exam #2 2 December 2009 Prof. Lucht. Choose two (2) of problems 1, 2, and 3: Problem #1 50 points Problem #2 50 points Problem #3 50 points

ME 501. Exam #2 2 December 2009 Prof. Lucht. Choose two (2) of problems 1, 2, and 3: Problem #1 50 points Problem #2 50 points Problem #3 50 points 1 Name ME 501 Exam # December 009 Prof. Lucht 1. POINT DISTRIBUTION Choose two () of problems 1,, and 3: Problem #1 50 points Problem # 50 points Problem #3 50 points You are required to do two of the

More information

Thermodynamics of nuclei in thermal contact

Thermodynamics of nuclei in thermal contact Thermodynamics of nuclei in thermal contact Karl-Heinz Schmidt, Beatriz Jurado CENBG, CNRS/IN2P3, Chemin du Solarium B.P. 120, 33175 Gradignan, France Abstract: The behaviour of a di-nuclear system in

More information

PHAS2228 : Statistical Thermodynamics

PHAS2228 : Statistical Thermodynamics PHAS8 : Statistical Thermodynamics Last L A TEXed on: April 1, 007 Contents I. Notes 1 1. Basic Thermodynamics : Zeroth and First Laws 1.1. Zeroth Law - Temperature and Equilibrium................ 1..

More information

Physics 607 Final Exam

Physics 607 Final Exam Physics 607 Final Exam Please be well-organized, and show all significant steps clearly in all problems. You are graded on your work, so please do not just write down answers with no explanation! Do all

More information

Physics Qual - Statistical Mechanics ( Fall 2016) I. Describe what is meant by: (a) A quasi-static process (b) The second law of thermodynamics (c) A throttling process and the function that is conserved

More information

Lecture 4: Entropy. Chapter I. Basic Principles of Stat Mechanics. A.G. Petukhov, PHYS 743. September 7, 2017

Lecture 4: Entropy. Chapter I. Basic Principles of Stat Mechanics. A.G. Petukhov, PHYS 743. September 7, 2017 Lecture 4: Entropy Chapter I. Basic Principles of Stat Mechanics A.G. Petukhov, PHYS 743 September 7, 2017 Chapter I. Basic Principles of Stat Mechanics A.G. Petukhov, Lecture PHYS4: 743 Entropy September

More information