Year 1 Sem 2/LC Mathematics for Physicists 1B/Lecture 07
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Recap of the last (two) lecture(s):
- To classify the stationary points of a function with $n$ variables, we form the Hessian matrix $H_{ij} = f_{x_ix_j}$.
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From the top-left corner of this matrix, we form 1x1, 2x2 etc determinants. These are called the leading minors.
- If these are all positive, the point is a maximum.
- If they alternate in sign, we have a minimum.
- If anything else, we have a saddle point.
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To extremise $f(x_1, x_2, \ldots, x_n)$ subject to $p$ constraints $g_i(x_1, x_2, \ldots, x_n) = 0$, we introduce a new function of $n+p$ variables: $$F(x_1, x_2, \ldots, x_n, \lambda_1, \lambda_2, \ldots, \lambda_p) = f(x_1, x_2, \ldots, x_n) + \sum_{i=1}^{p} \lambda_i g_i(x_1, x_2, \ldots, x_p)$$
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We then extremise $F$ wrt all $n+p$ variables. Extremising with respect to $\lambda_i$ enforces the constraint: $$F_{\lambda_i} = g_i(x_1, x_2, \ldots, x_n) = 0$$
- So the the lambda term ends up dropping out and $F$ and $f$ have the same numerical value at extrema.
Statistical Mechanics
Consider a system containing $N$ atoms. Each atom has $p$ energy levels, $\epsilon_1, \epsilon_2, \ldots, \epsilon_p$.
Suppose there are $n_1$ atoms in state $\epsilon_1$, $n_2$ in state $\epsilon_2$, $\ldots$, $n_p$ in state $\epsilon_p$.
This gives us two constraints:
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The total number of atoms in the system is constant: $$\sum_{i=1}^{p} n_i = N$$
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The total energy $E$ of the system is conserved: $$\sum_{i=1}^{p} n_i \epsilon_i = E$$
The entropy of the system is defined as:
Where $W(\dots)$ represents the number of ways to put $n_1$ atoms in state $\epsilon_1$ etc. We want to maximise this function subject to the two constraints. We assume that the atoms are indistinguishable.
The $W$ function is given by the multinomial:
As, if all the atoms were in different energy levels, there would be $N!$ ways of doing so. However, the $n_1$ atoms occupying state $\epsilon_1$ can be rearranged freely, with no actual change to the system. We have therefore overcounted by a factor of $n_1!$, so divide this out. Et cetera for each energy level.
From this:
And:
Disregarding the lower bound as we assume that $n \gg 1$. This is called Stirling’s approximation. We therefore have:
We are therefore looking to maximise:
And extremising wrt $n_i$ gives:
Or:
where $z = \exp(-\lambda_i / k_B)$. The $\lambda_2$ has a physical meaning where $\lambda_2 = 1/T$.
We could also divide $n_1 / N$ to get the probability of finding a given atom in a given state:
The normalisation constant $Z$ is known as the partition function. The formulae for ${p_i}$ gives the Boltzmann distribution.
Statistical Entropy
We have:
And multiplying through by $N/N$, we get:
Hence the entropy per atom in units of $k_B$ is:
his is known as the statistical entropy of the probability distribution $\{p_i\}$.
For a continuous distribution:
Getting an Actual Value
We have (again considering per atom entropy):
The second sum is just average energy, which is the internal energy $U$.
Where “F” is called the Helmholtz Free Energy and the equation linking F and the partition function Z is called the bridge equation.