Suppose you flip four fair coins.

(a) Make a list of all the possible outcomes, as in Table 2.1.

(b) Make a list of all the different "macrostates" and their probabilities.

(c) Compute the multiplicity of each macrostate using the combinatorial formula 2.6, and check that these results agree with what you got by bruteforce counting.

Short Answer

Expert verified

Determine the multiplicity of each macrostate and ensure that the result is agree with got by brute force counting is

Ω(0tails)=Ω(4,0)=40=1Ω(1tails)=Ω(4,1)=41=4Ω(2tails)=Ω(4,2)=42=6Ω(3tails)=Ω(4,3)=43=4Ω(4tails)=Ω(4,4)=44=1

Step by step solution

01

Step1:Given data

Assume we have four distinguishable fair (equally likely to land heads or tails) coins. There are two if we flip all four. 24=16possible outcomes, because each coin has two possible states and the four coins are distinct from one another Each of these states is referred to as a microstate. On the other hand, we might be more interested in the total number of heads or tails rather than which coins came up in either state. In this case, we'd only be interested in the overall condition of the four coin collection.

02

Step2:Possible outcomes(part a)

(a)

03

Step3:Macrostate possibilities(part b)

(b)To make things easier to count, I converted the four coin states into binary numbers usingH=0 andT=1, then simply counted how many times each number appeared. for example:

- if the sum =0, so we have0tails.

- if the sum=1so we have1tails.

- if the sum =2, so we have 2tails.

- if the sum=3,so we have3tails.

- if the sum=4, so we have3tails.

04

Step4:possible outcomes(part b)

05

Step5:final probability(part b)

06

Step6:multiplicity macrostate(part c)

(c) In general, we can calculate the probability of getting n heads in N coin flips. The problem can be thought of as the number of ways to choose n coins from a total of N and make these n coins the heads with the remaining N-n tails. We have N coins to choose from for the first of the n coins, so there are N ways to make this first selection. With that first coin selected, there areN-1coins from which we can select the next head, and so on, until we reach the final head. for which we have N-n+1choices. Thus the number of ways of choosing n coins from N in which the order of the choice does matter is:

N(N1)(Nn+1)=N!(N1)!

However, for a given macrostate, the order in which we choose the heads is irrelevant, and because there are n! ways to order each of the macrostates, the actual number of ways to choose the macrostate with n heads isΩ(N,n)=N!(N1)!n!=Nn

That is, Ω(N,n)is the binomial coefficientNn. So the multiplicity of macrostates:

Ω(0tails)=Ω(4,0)=40=1Ω(1tails)=Ω(4,1)=41=4Ω(2tails)=Ω(4,2)=42=6Ω(3tails)=Ω(4,3)=43=4Ω(4tails)=Ω(4,4)=44=1

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Most popular questions from this chapter

Suppose you flip1000 coins.
a What is the probability of getting exactly 500heads and 500tails? (Hint: First write down a formula for the total number of possible outcomes. Then, to determine the "multiplicity" of the 500-500"macrostate," use Stirling's approximation. If you have a fancy calculator that makes Stirling's approximation unnecessary, multiply all the numbers in this problem by 10, or 100, or1000, until Stirling's approximation becomes necessary.)
bWhat is the probability of getting exactly 600heads and400 tails?

Use a computer to plot formula 2.22directly, as follows. Define z=q_{A}/q, so that (1-z)=q_{B}/q. Then, aside from an overall constant that we'll ignore, the multiplicity function is [4z(1-z)]N, where zranges from 0to1and the factor of 4ensures that the height of the peak is equal to 1for any N. Plot this function forN=1,10,100,1000, and 10,000. Observe how the width of the peak decreases asNincreases.

Using the same method as in the text, calculate the entropy of mixing for a system of two monatomic ideal gases, Aand B, whose relative proportion is arbitrary. Let Nbe the total number of molecules and letx be the fraction of these that are of speciesB . You should find

ΔSmixing=Nk[xlnx+(1x)ln(1x)]

Check that this expression reduces to the one given in the text whenx=1/2 .

Consider again the system of two large, identical Einstein solids treated in Problem 2.22.

(a) For the case N=1023, compute the entropy of this system (in terms of Boltzmann's constant), assuming that all of the microstates are allowed. (This is the system's entropy over long time scales.)

(b) Compute the entropy again, assuming that the system is in its most likely macro state. (This is the system's entropy over short time scales, except when there is a large and unlikely fluctuation away from the most likely macro state.)

(c) Is the issue of time scales really relevant to the entropy of this system?

(d) Suppose that, at a moment when the system is near its most likely macro state, you suddenly insert a partition between the solids so that they can no longer exchange energy. Now, even over long time scales, the entropy is given by your answer to part (b). Since this number is less than your answer to part (a), you have, in a sense, caused a violation of the second law of thermodynamics. Is this violation significant? Should we lose any sleep over it?

Use a computer to reproduce the table and graph in Figure2.4: two Einstein solids, each containing three harmonic oscillators, with a total of six units of energy. Then modify the table and graph to show the case where one Einstein solid contains six harmonic oscillators and the other contains four harmonic oscillators (with the total number of energy units still equal to six). Assuming that all microstates are equally likely, what is the most probable macrostate, and what is its probability? What is the least probable macrostate, and what is its probability?

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