00:01
Depending the temperature through a derivative of a log of number of ways may be hard to embrace, but it's built into the boltzmann distribution and all others.
00:13
We can at least verify it in the oscillator case.
00:19
The average energy mh omega -0 by n of a collection of oscillators through the average predicted by the bolzman precision demands a fairly much.
00:33
Our system assuming the number of particles equals to 10 ,000 and the total energy is 49h omega not it's easiest to choose the energy units in which h omega is equal to 1 so that e and m e and m are both 49 ,000 first calculate the number of particles n at each level by multi -plan capital n by the exact probabilities using instead n e is the total number at a given level not a specific particle.
01:46
Here we know that h -omeagnot is equal to 1.
01:48
Small n is the level's energy round each capital n n to the nearest integer then determine the total energy by simply multiplying capital n n by small n the number times the energy at each level and summing over all the levels it might seem that the total should be 49 ,000.
02:19
Due to running it won't be but it should differ by less than 1 % entropy is fairly easy to calculate here the number of ways of rearranging particle labels when n particles are distributed in different boxes so it will be n factorial by and now calculate the entropy for b part repeat the a part changing of only capital m, marking it to 51 ,000 instead of 49 ,000.
03:07
For c, calculate the quotient, that is change in entropy over changing energy, bearing in mind that we are considering the system of n equals to 10 ,000, and m equals to 50 ,000.
03:34
How does it compare with the given equation? in order to determine the probabilities, energies, occupants, levels and entropy the equation for the probability to find a particle in the particular state, the number of particles expected per level, the energy per level, the number of ways of counting numbers, the probability, p, n is given by m minus n plus n minus 1 minus 1 m minus 1 m minus n divided by m plus n minus 1 m the number of particles expected number of particles expected capital n n per state n is given by n n is equal to n into p n is the probability of finding the particle in that state the energy level, energy per level, en for some state n is given by small nn to capital m.
05:18
Your capital n is the expected number of particles per level.
05:22
The number of ways of counting n number of particles by the binomial coefficient w is given by n factorial by pi n n factorial.
05:44
The entropy s is defined by s is equal to kb into ln of the binomial coefficient.
05:56
Your kb is the bolzman constant and w is the number of ways that system can be arranged.
06:04
Sterling approximation involving the n factorial with capital n being very large number will also be useful.
06:17
That is given by ln of n factorial is approximately capital n ln n minus n as well as the approximation using a factorial given by k factorial by k minus a small k factorial is equal to k to the power.
06:42
This is well as well.
06:44
When small k is very very less than capital k.
06:49
The equation relating the temperature, number of particles and sum of numbers of the particle capital m will be used as a comparison given by kv t is equal to h omega not by l n 1 plus n by m.
07:10
With k b being the bolzman constant, h is the plume, reduced plank constant, and omega -0 is fundamental angular frequency of the particle.
07:19
The relationship between entropy and the temperature is t is equals to differential of s by differential of e raised to to the power minus 1.
07:37
This shows that it's the inverse of change in entropy over the change in energy.
07:45
For first in order to find the probability of finding a particle in any particular another state we will start over by the probability formula.
07:56
This can be rewritten as m factorial by m minus n factorial multiplied by n minus 1 factorial by n minus 1 minus 1 multiplied by divided by m plus n minus 1 factorial factorial and it is divided by m plus n minus 1 minus of n plus 1 factorial each of those terms can be rewritten and the probability formula will be respectively m raised to the power n n minus 1 divided by m plus n minus 1 whole raise to the power n plus 1 since m and n will be very large subtracting 1 will not affect it to ignoring it we have the expression n raised to the power n capital n divided by m plus n raised to the power n plus 1.
09:46
This can again be rearranged n by m plus n into m by m plus n raised to the power small n.
10:09
The parenthesis can be written with a negative exponent so as to simplify this expression a little so the probability formula will be equals to n by m plus n, 1 plus n by m raised in power minus n.
10:38
So that is the simpler form that will be used in the calculations.
10:42
Instead, substituting the value n equals to 10 ,000 and m equals to 49 ,000 will have the equation in the reduced form in terms of small n will be 10 by 59 into 59 by 49 raised to the power minus n...