Problem Set 4 Solutions 3.20 MIT Dr. Anton Van Der Ven Fall 2002

Similar documents
Chapter 4: Partial differentiation

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

Assignment 16 Solution. Please do not copy and paste my answer. You will get similar questions but with different numbers!

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

Recitation: 10 11/06/03

Statistical Mechanics. Hagai Meirovitch BBSI 2007

11.6: Ratio and Root Tests Page 1. absolutely convergent, conditionally convergent, or divergent?

13! (52 13)! 52! =

FINAL EXAM Math 25 Temple-F06

Machine Learning Srihari. Information Theory. Sargur N. Srihari

3.320 Lecture 18 (4/12/05)

Brief introduction to groups and group theory

Review (11.1) 1. A sequence is an infinite list of numbers {a n } n=1 = a 1, a 2, a 3, The sequence is said to converge if lim

Statistical thermodynamics Lectures 7, 8

1 Solution to Homework 4

Taylor Series. richard/math230 These notes are taken from Calculus Vol I, by Tom M. Apostol,

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

PHYS 445 Lecture 3 - Random walks at large N 3-1

2. Thermodynamics. Introduction. Understanding Molecular Simulation

Statistical thermodynamics Lectures 7, 8

Solid Thermodynamics (1)

Math 126 Enhanced 10.3 Series with positive terms The University of Kansas 1 / 12

Elementary Differential Equations, Section 2 Prof. Loftin: Practice Test Problems for Test Find the radius of convergence of the power series

Part 3.3 Differentiation Taylor Polynomials

Introduction Statistical Thermodynamics. Monday, January 6, 14

Thermodynamics of phase transitions

Review for the Final Exam

AP Calculus Chapter 9: Infinite Series

Math 132 Exam 3 Fall 2016

Physics 576 Stellar Astrophysics Prof. James Buckley. Lecture 14 Relativistic Quantum Mechanics and Quantum Statistics

Chemistry. Lecture 10 Maxwell Relations. NC State University

x 2 y = 1 2. Problem 2. Compute the Taylor series (at the base point 0) for the function 1 (1 x) 3.

16.4. Power Series. Introduction. Prerequisites. Learning Outcomes

The Gaussian distribution

The integral test and estimates of sums

Compare the growth rate of functions

The Partition Function Statistical Thermodynamics. NC State University

First-Order Differential Equations

Math 132 Exam 3 Fall 2016

Statistical Mechanics and Information Theory

Statistics, Probability Distributions & Error Propagation. James R. Graham

2017 HSC Mathematics Extension 1 Marking Guidelines

The Lowest Temperature Of An Einstein Solid Is Positive

Math Refresher Course

NENG 301 Week 8 Unary Heterogeneous Systems (DeHoff, Chap. 7, Chap )

CALCULUS JIA-MING (FRANK) LIOU

Solutions to Assignment-11

8.333: Statistical Mechanics I Fall 2007 Test 2 Review Problems

ELEG 3143 Probability & Stochastic Process Ch. 6 Stochastic Process

8.1 Sequences. Example: A sequence is a function f(n) whose domain is a subset of the integers. Notation: *Note: n = 0 vs. n = 1.

Thermodynamics: A Brief Introduction. Thermodynamics: A Brief Introduction

Ch. 8 Math Preliminaries for Lossy Coding. 8.4 Info Theory Revisited

Assignment 3. Tyler Shendruk February 26, 2010

Absolute Convergence and the Ratio Test

Signal Processing - Lecture 7

Series Solution of Linear Ordinary Differential Equations

Kinetic Theory 1 / Probabilities

MASSACHUSETTS INSTITUTE OF TECHNOLOGY Physics Department Statistical Physics I Spring Term 2013 Exam #1

Review Sheet on Convergence of Series MATH 141H

2 Series Solutions near a Regular Singular Point

(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

LOWELL. MICHIGAN, THURSDAY, AUGUST 16, Specialty Co. Sells to Hudson Mfg. Company. Ada Farmer Dies When Boat Tips

p. 6-1 Continuous Random Variables p. 6-2

Today: Fundamentals of Monte Carlo

The answer (except for Z = 19) can be seen in Figure 1. All credit to McGraw- Hill for the image.

Math Bootcamp 2012 Miscellaneous

General Gibbs Minimization as an Approach to Equilibrium

MATH141: Calculus II Exam #4 review solutions 7/20/2017 Page 1

An idea how to solve some of the problems. diverges the same must hold for the original series. T 1 p T 1 p + 1 p 1 = 1. dt = lim

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

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

Columbia University Department of Physics QUALIFYING EXAMINATION

Minimum Bias Events at ATLAS

5.9 Representations of Functions as a Power Series

Homework 3 Solutions(Part 2) Due Friday Sept. 8

Entropy and Free Energy in Biology

Uses of Asymptotic Distributions: In order to get distribution theory, we need to norm the random variable; we usually look at n 1=2 ( X n ).

Statistical. mechanics

CS839: Probabilistic Graphical Models. Lecture 7: Learning Fully Observed BNs. Theo Rekatsinas

Lecture 6 Free Energy

The Euler Equation. Using the additive property of the internal energy U, we can derive a useful thermodynamic relation the Euler equation.

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

Math RE - Calculus II Antiderivatives and the Indefinite Integral Page 1 of 5

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

Final Exam Review Quesitons

ELEG 5633 Detection and Estimation Signal Detection: Deterministic Signals

Convergence in Distribution

+ kt φ P N lnφ + φ lnφ

ABCD42BEF F2 F8 5 4D6589 CC8 9

Math 2233 Homework Set 8

Chapter 4 Notes, Calculus I with Precalculus 3e Larson/Edwards

Temperature and Heat. Ken Intriligator s week 4 lectures, Oct 21, 2013

MATH 301 INTRO TO ANALYSIS FALL 2016

Math 180C, Spring Supplement on the Renewal Equation

10.1 Sequences. A sequence is an ordered list of numbers: a 1, a 2, a 3,..., a n, a n+1,... Each of the numbers is called a term of the sequence.

Chapter 8. Infinite Series

Lecture 17: The Exponential and Some Related Distributions

Statistical thermodynamics (mechanics)

Math Numerical Analysis

ε1 ε2 ε3 ε4 ε

Transcription:

Problem Set 4 Solutions 3.20 MIT Dr. Anton Van Der Ven Fall 2002 Problem -22 For this problem we need the formula given in class (Mcuarie -33) for the energy states of a particle in an three-dimensional infinite well, namely Now we can make a table nxn yn z h 2 8ma 2 n x 2 n y 2 n z 2, n x,n y,n z,2... n x n y n z n 2 x n 2 2 y n z Degeneracy 3 2 6 2 6 3 2 6 2 2 9 2 2 9 3 2 2 9 3 3 3 3 Problem -29

Start with the differential form for E de TdS pdv E T S T T p We can use a Maxwell relation on S T from FT,V S T p T V So, E T p T T V p Problem -4 Show that x x 2 x 2 x 2 x x 2 x 2 2x x x 2 x 2 2x x x 2 x 2 2 x x x 2 x 2 x 2

Problem -43 Here we have to plot the Gaussian px 2 to see what happens as 0 x x 2 exp 2 2 for several values of As 0, the function becomes sharper and sharper (remember the area under the curve is contrained to be, as we will see in problem -44a). Thus, the Gaussian approaches a delta function. Problem -44 Gaussian distribution is px 2 exp x x 2 2 2 (a) show pxdx 2 exp x x 2 2 2 dx Let

u x x 2, then du dx 2 So we now have expu2 du And using standard integral tables or the math software, it can be show that this integral is equal to.

(b) n th central moment for n 0,,2, and 3 For n 0 x x 0 see part a For n x x x x pxdx x x 2 x x 2 exp 2 2 dx Let u x x 2, then du dx 2 Then x x u expu 2 du 0 u expu 2 du I u expu 2 du 0 II For I let v u and dv du. Then I 0 u expu 2 du 0 v expv 2 dv II Thus, u expu 2 du 0 For n 2 x x 2 x x pxdx x x 2 2 x x 2 exp 2 2 dx Let

u x x 2, then du dx 2 x x 3 2 2 u 2 expu 2 du 22 u 2 expu 2 du Now lets take a crack at this integral... u 2 expu 2 du We have to do this by parts. Remembering how to do that... yx y x yx y x yx yx For our case, let y 2uexpu 2 du and x u 2 y expu 2 and x 2

So, u 2 expu 2 du u expu 2 2 2 expu 2 0 2 Which leaves us with, x x 2 2 For n 3 x x 3 x x 3 pxdx x x 3 2 x x 2 exp 2 2 dx As before, let u x x 2, then du dx 2 Then, x x 3 2 2 u 3 expu 2 Since e u2 is a symmetric function around the origin and u 3 is an antisymmetric function around the origin, the integral of the product of the two functions is zero. x x 3 0 (c) limpx lim 0 0 2 x x 2 exp 2 2 x x, the delta function The delta function is defined as

x a xdx a and xdx So lets see if this works for our case lim 0 2 exp x a2 2 2 xdx Let u xa 2 and du dx 2 lim expu 2 2 a 0 Since 0 expu 2 a a expu 2 a Problem -49 Maximize WN,N 2,...N m N! m N! under the contraints that N N and E N. Since the natural log is a monotonic function, we can maximize lnw. M lnwn,n 2,...N m ln N! m N! Using Sterling approximation, this can be written as

NlnN N N lnn N But the maximization must be constrained therefore we intoduce Lagrange multipliers M NlnN N N lnn N N N E N N Remembering N N and taking the derivative of M with respect to N M N lnn E 0 lnn E lnn E, with N exp expe Problem -50 We want to show that the maximum of WN,N 2,...N m N! occurs for N N 2 N s N s Maximize m N! M lnw NlnN N N lnn N subect to the constraint N N. So we must use Lagrange multipliers: M NlnN N N lnn N N N

M lnn 0 N lnn N exp But now we must determine s s N exp Sexp N exp N s So N N s

Problem -5 Here we use Lagrange multipliers again with the constraint P. N M P lnp N P Maximize M P lnp 0 P exp Determine N P Nexp exp N Thus P N Problem 2- From stat mech we get E p N, p And from thermo we have

E T p N,T T p To show why cont T lets see what happens if we let T where is a constant E N, T p T p or E T p N,T T p but from a Maxwell relation we know p T S N,T and we can write E T S N,T de TdS PdV N,T p This statement violates the second law of thermodynamics because it implies that TdS ds T

Problem 2-2 Given n n! n!n n! is n n? n is the value of n that maximizes n. From problem -50, we know that n n. 2 n is given by n n n 0 n n 0 n n! n!nn! n! n!nn! 2-2- We also know that (given in the problem): n y x n x n n! n n 0!n n! If we take the derivative of y with respect to x we get n y n x n n x n n! n!n n! n 0 If we let x : n n2 n n n! n!n n! n 0 Furthermore,

n 2 n n 0 n! n!n n! So if we put this all together back in (2-2-) we get n n n 0 n n 0 n n! n!nn! n! n!nn! n2n 2 n n 2 n n n Problem 2-5 Show that S k P lnp We have the following three relations already and S ln T P exp exp E E kln Starting with S we can write S T kln E exp E 2 kln S k E exp E kln S k ln exp E exp E kln

S k ln exp E exp E kln P Since P S k P ln exp S k P ln exp E E kln P k P ln S k P ln exp E S k P lnp Problem 2-8 E E expe E expe ln E ln Problem 2-0 First derive E 2 ln T starting from the result of problem 2-8, namely E ln

From the chain rule E ln T T We know T so 2, thus E 2 ln T We can check this by taking 2 ln T. 2 ln T 2 T 2 T exp E 2 T exp E E exp E 2 The 2 cancels and we are left with 2 ln T E exp E definition of E So we have shown again that indeed E 2 ln T. Now for the relation involving p p p exp E E exp E exp E N,T p ln N,T

Problem 2- Starting with F ln (Remember F A S F T V,N S ln kln Eqn. 2-33 T V,N p F T,N p ln T,N Eqn. 2-32 F E TS E F TS E ln T ln kln T V,N E 2 ln T V,N Eqn. 2-3 Problem 2-3 E V. We can start For a particle confined to a cube of length a we are asked to show p 2 3 with the equation for the energy states of a particle in an three-dimensional infinite well, namely E h 2 8ma 2 n x 2 n y 2 n z 2, n x,n y,n z,2... Remembering that a 3 V or a V 3 we can write E in terms of V E h2 V 2 3 8m n x 2 n y 2 n z 2 p E 2 3 h2 V 5 3 8m n x 2 n 2 y n 2 z 2 3 V h 2 V 2 3 8m n x 2 n 2 y n 2 z E So we have

p 2 3 E V and taking the ensemble average gives us p 2 3 E V Problem 2-4,T N! 2m h 2 3N 2 V N For p, p ln ln N! 3N 2 ln p N V T.N ln 2m h 2 NlnV Now for E E 2 ln T 2 3N 2 E 3N 2 2mk h 2 2m h 2 Ideal gas equation of state is obtained when ft N ln lnft NlnV p ln T.N lnft T,N NlnV p N V

Problem 2-5 We are given as exp h 2 exp h 3N exp U o substituting in h k exp 2T exp T 3N exp U o To find c v we need to use the following two relations E 2 c v ln T E T Using your favorite math package (Maple), we can get E as E Uo e 2 3Nke Uo 2Nke Uo k 9Nke 2 kuo e T 2 2U o e Uo 4U o e Uo k 2U o e 2 kuo and c v as c v E T 3 T 2 kn 2 e T e T 2 Now we can take the lim T c v andwefindthat

lim T 3 T 2 k 2 e T N e T 2 3Nk