Deriving the thermodynamic beta from Lagrange Multipliers

In summary, the conversation discusses the derivation of a formula for the number of microstates in a given macrostate in a system of N identical but distinguishable particles. The formula is maximized using Stirling's approximation and Lagrange multipliers. The derivation introduces the partition function and determines the values of the undetermined multipliers. Ultimately, the discussion leads to the relationship between the multipliers and the thermodynamic quantities.
  • #1
McLaren Rulez
292
3
I'm nearly at the end of this derivation but totally stuck so I'd appreciate a nudge in the right direction

Consider a set of N identical but distinguishable particles in a system of energy E. These particles are to be placed in energy levels ##E_i## for ##i = 1, 2 .. r##. Assume that we have ##n_i## particles in each energy level. The two constraints we impose are that ##\sum_{i}^{r}n_i = N## and ##\sum_{i}^{r}E_i n_i = E##.

The number of microstates in a given macrostate is given by
\begin{equation}
\Omega = \frac{N!}{\sum_{i}^r n_{i}!}
\end{equation}

We want to maximize this and for ease of notation, we work with ##\ln\Omega## and we use Stirling's approximation (##\ln x! = x\ln x - x##) to obtain
\begin{equation}
\ln\Omega = N\ln N - N - \sum_{i}^{r}n_i\ln n_i - n_i
\end{equation}

Maximizing this function subject to the constraints ##\sum_{i}^{r}n_i = N## and ##\sum_{i}^{r}E_i n_i = E## is a classic Lagrange multiplier problem. We represent the undetermined multipliers to be ##\alpha## and ##\beta## for the two constraints and obtain
\begin{align}
\frac{\partial\ln\Omega}{\partial n_i} &= \alpha\frac{\partial n_i}{\partial n_i} + \beta\frac{\partial E_i n_i}{\partial n_i} \\ \nonumber
\ln n_i &= \alpha + \beta E_i \\ \nonumber
\therefore n_i &= e^{\alpha}e^{\beta E_i}
\end{align}

Now, we use the first constraint equation to determine ##\alpha##. We get
\begin{align}
\sum_i^r n_i &= N \\ \nonumber
\sum_i^r e^{\alpha}e^{\beta E_i} &= N \\ \nonumber
e^\alpha &= \frac{N}{\sum_i^re^{\beta E_i}} \\ \nonumber
e^\alpha &= \frac{N}{Z}
\end{align}

We have introduced the partition function, ##Z=\sum_i^re^{\beta E_i}## in the last line. Next, we have the second constraint equation that determines ##\beta##
\begin{align}
\sum_i^r E_i n_i &= E \\ \nonumber
\frac{\sum_{i}^{r} E_i e^{\beta E_i}}{\sum_i^r e^{\beta E_i}} &= E \\ \nonumber
\end{align}

I'm assuming I should somehow connect ##E## with ##T## so let's say ##E=Nk_B T##. Then we have
\begin{align}
\frac{N}{Z}\frac{\partial Z}{\partial\beta} &= E \\
\frac{\partial\ln Z}{\partial\beta} &= k_B T
\end{align}

How do I get to ##\beta = -\frac{1}{k_B T}## here? Notice that this derivation requires an extra minus sign compared to the usual definition of ##\beta## and this should come out naturally too, shouldn't it?
 
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  • #2
Of course, it's easier to flip the sign of ##\beta## from the very beginning, because then you have ##\beta>0## for the usual case where the Hamiltonian of the system is bounded from below but can become infinite (e.g., for an ideal gas you have ##H=\vec{p}^2/(2m) \geq 0##. Then you have
$$Z(\beta,\alpha)=\sum_i \exp(-\beta E_i + \alpha n_i).$$
Now to get the interpretation of ##\beta## and ##\alpha## in terms of the thermodynamical quantities note that
$$U=\langle E \rangle=-\partial_{\beta} \ln Z, \quad \mathcal{N}=\langle N \rangle=\partial_{\alpha} \ln Z.$$
Further the probability distribution is
$$P_i=\frac{1}{Z} \exp(-\beta E_i+\alpha \mathcal{N}).$$
This implies that the entropy is given by
$$S=-k_B \sum_i P_i \ln P_i \rangle=k_B (\ln Z+\beta U-\alpha \mathcal{N}).$$
With the above relations you get
$$\frac{1}{k_B} \mathrm{d} S = \beta \mathrm{d} U - \alpha \mathrm{d} \mathcal{N}.$$
Then comparing this to the 1st Law
$$\mathrm{d} U=T \mathrm{d} S +\mu \mathrm{d} \mathcal{N}$$
you'll get
$$\beta=\frac{1}{k_B T}, \quad \alpha=\frac{\mu}{k_B T}.$$
 
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1. What is the significance of deriving the thermodynamic beta from Lagrange multipliers?

Deriving the thermodynamic beta from Lagrange multipliers allows us to understand the relationship between energy and entropy in a thermodynamic system. It helps us to calculate the probability of a specific energy state and predict the behavior of the system at different temperatures.

2. How is the thermodynamic beta related to temperature?

The thermodynamic beta, denoted as β, is inversely proportional to temperature. As temperature increases, the value of β decreases, indicating a higher probability of the system being in a lower energy state.

3. Can the thermodynamic beta be negative?

No, the thermodynamic beta cannot be negative. It is a physical quantity that represents the ratio of energy to temperature and therefore has to be a positive value.

4. How does the concept of Lagrange multipliers come into play in deriving the thermodynamic beta?

Lagrange multipliers are used to optimize a function subject to a constraint. In the case of deriving the thermodynamic beta, we use Lagrange multipliers to optimize the entropy of a system while keeping its energy constant. This allows us to find the optimal value of β that satisfies the given constraints.

5. What are the applications of deriving the thermodynamic beta from Lagrange multipliers?

Deriving the thermodynamic beta from Lagrange multipliers has various applications in statistical mechanics and thermodynamics. It is used to calculate the partition function, predict phase transitions, and analyze the behavior of complex systems. It also helps in understanding the relationship between energy and entropy in different physical systems.

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