diff --git a/docs/physics/thermal/6-boltzmann-statistics.md b/docs/physics/thermal/6-boltzmann-statistics.md new file mode 100644 index 0000000..4a097a7 --- /dev/null +++ b/docs/physics/thermal/6-boltzmann-statistics.md @@ -0,0 +1,37 @@ +# Chapter 6 - Boltzmann Statistics + +## Section 6.1 - The Boltzmann Factor + +Consider some system coupled to a reservoir. Then, we can associate each microstate of the system with some energy level $E$. + +**Definition**. We say an energy level is *degenerate* if it corresponds to more than one microstate. + +Now, consider two microstates $s_1$ and $s_2$, with energies $E(s_1)$ and $E(s_2)$ and probabilities $\mathcal{P}(s_1)$ and $\mathcal{P}(s_2)$ respectively. While in an isolated system, the fundamental assumption of statistical mechanics tells us that each microstate is equally probable, this is not the case in a closed or open system. + +We can now consider the reservoir when the system is in state $s_1$. There are multiple microstates the reservoir can be in under these constrains, so let us define $\Omega_R(s_1)$ as the multiplicity of the macrostate of the reservoir while the system is in state $s_1$. + +This then lets us derive the relation + +$$\frac{\mathcal{P}(s_2)}{\mathcal{P}(s_1)} = \frac{\Omega_R(s_2)}{\Omega_R(s_1)}$$ + +We can then see that as $S = k ln \Omega$, we can write $\Omega_R = \exp(S_R/k)$, allowing us to write + +$$\frac{\mathcal{P}(s_2)}{\mathcal{P}(s_1)} = \frac{\exp(S_R(s_2)/k)}{\exp(S_R(s_1)/k)} = \exp((S_R(s_2) - S_R(s_1))/k)$$ + +If the system is small compared to the reservoir, such as if the system is an atom, we can write $S_R(s_2) - S_R(s_1) = dS_R$, and invoke the thermodynamic identity. We further can assume that $P dV_R$, while nonzero, is negligible compared to $dU_R$. Additionally, we assume $dN = 0$ for closed systems. Thus, + +$$S_R(s_2) - S_R(s_1) = \frac{1}{T}(U_R(s_2) - U_R(s_1)) = -\frac{1}{T}(E(s_2) - E(s_1))$$ + +We can substitute this into the ratio of probabilities to see that + +$$\frac{\mathcal{P}(s_2)}{\mathcal{P}(s_1)} = \frac{\exp(-E(s_2)/kT)}{\exp(-E(s_1)/kT)}$$ + +We can rearrange this. + +$$\frac{\mathcal{P}(s_2)}{\exp(-E(s_2)/kT)} = \frac{\mathcal{P}(s_1)}{\exp(-E(s_1)/kT)}$$ + +However, for this to be true for all states, the expression must equal a constant, which we denote as $1/Z$. Thus, + +$$\mathcal{P}(s) = \frac{1}{Z}e^{-E(s)/kT}$$ + +**Definition**. Here, $Z$ is the *partition function*. This is a constant that only depends on temperature, and equals the sum of all unweighted probabilities.