Statistical Mechanics – Matrix Element and Dirac Notation

density-operatorpartition functionspin-modelsstatistical mechanics

If
$$
T=
\left[
\begin{array}{cccc}
e^{\beta J} & e^{-\beta J} \\
e^{-\beta J} & e^{\beta J} \\
\end{array} \right]
$$

and
$$Z = \sum_{S_i=\pm 1} … \sum_{S_N=\pm 1} \exp{\beta J(\vec{S_1}\vec{S_2}+\vec{S_2}\vec{S_3}+…+\vec{S_{N-1}}\vec{S_N}+\vec{S_N}\vec{S_1})}
$$

Then why can we say that
$$Z = \sum_{S_i=\pm 1} … \sum_{S_N=\pm 1} \langle S_1|T|S_2\rangle\langle S_2|T|S_3\rangle…\langle S_N|T|S_1\rangle ?
$$

Best Answer

$\newcommand{\e}{\boldsymbol=}$ $\newcommand{\p}{\boldsymbol+}$ $\newcommand{\m}{\boldsymbol-}$ $\newcommand{\gr}{\boldsymbol>}$ $\newcommand{\les}{\boldsymbol<}$ $\newcommand{\greq}{\boldsymbol\ge}$ $\newcommand{\leseq}{\boldsymbol\le}$ $\newcommand{\plr}[1]{\left(#1\right)}$ $\newcommand{\blr}[1]{\left[#1\right]}$ $\newcommand{\lara}[1]{\langle#1\rangle}$ $\newcommand{\lav}[1]{\langle#1|}$ $\newcommand{\vra}[1]{|#1\rangle}$ $\newcommand{\lavra}[2]{\langle#1|#2\rangle}$ $\newcommand{\lavvra}[3]{\langle#1|\,#2\,|#3\rangle}$ $\newcommand{\x}{\boldsymbol\times}$ $\newcommand{\qqlraqq}{\qquad\boldsymbol{-\!\!\!-\!\!\!-\!\!\!\longrightarrow}\qquad}$

Consider two complex $n\m$vectors expressed also as kets \begin{equation} \mathbf x\e \begin{bmatrix} x_1 \vphantom{\dfrac{a}{b}}\\ x_2 \vphantom{\dfrac{a}{b}}\\ \vdots \vphantom{\dfrac{a}{b}}\\ x_n \vphantom{\dfrac{a}{b}}\\ \end{bmatrix}\e \vra{\mathbf x}\qquad \texttt{and} \qquad \mathbf y\e \begin{bmatrix} y_1 \vphantom{\dfrac{a}{b}}\\ y_2 \vphantom{\dfrac{a}{b}}\\ \vdots \vphantom{\dfrac{a}{b}}\\ y_n \vphantom{\dfrac{a}{b}}\\ \end{bmatrix}\e \vra{\mathbf y}\quad \in \mathbb C^n \tag{01}\label{01} \end{equation} Complex conjugating and transposing these one-column matrices we obtain the bras \begin{equation} \mathbf x^{\boldsymbol*}\e \begin{bmatrix} \overline x_1 & \overline x_2 & \cdots & \overline x_n \vphantom{\dfrac{a}{b}}\\ \end{bmatrix}\e \lav{\mathbf x}\quad \texttt{and} \quad \mathbf y^{\boldsymbol*}\e \begin{bmatrix} \overline y_1 & \overline y_2 & \cdots & \overline y_n \vphantom{\dfrac{a}{b}}\\ \end{bmatrix}\e \lav{\mathbf y} \tag{02}\label{02} \end{equation} Their usual inner product in $\,\mathbb C^n\,$ is \begin{equation} \overline x_1\,y_1\p\overline x_2\,y_2\p\cdots\overline x_n\,y_n\e \begin{bmatrix} \overline x_1 & \overline x_2 & \cdots & \overline x_n \vphantom{\dfrac{a}{b}}\\ \end{bmatrix} \begin{bmatrix} y_1 \vphantom{\dfrac{a}{b}}\\ y_2 \vphantom{\dfrac{a}{b}}\\ \vdots \vphantom{\dfrac{a}{b}}\\ y_n \vphantom{\dfrac{a}{b}}\\ \end{bmatrix}\e \lavra{\mathbf x}{\mathbf y} \tag{03}\label{03} \end{equation} Given a $\,n\times n\,$ complex matrix $\,\mathrm A\,$ \begin{equation} \mathrm A\e \begin{bmatrix} a_{11} & a_{11} & \cdots & a_{1n} \vphantom{\dfrac{a}{b}}\\ a_{21} & a_{22} & \cdots & a_{2n} \vphantom{\dfrac{a}{b}}\\ \vdots & \vdots & \vdots & \vdots\vphantom{\dfrac{a}{b}}\\ a_{n1} & a_{n2} & \cdots & a_{nn}\vphantom{\dfrac{a}{b}}\\ \end{bmatrix} \tag{04}\label{04} \end{equation} the notation $\,\lavvra{\mathbf x}{\mathrm A}{\mathbf y}\,$ is the inner product of the vectors $\,\mathbf x\,$ and $\,\mathrm A\mathbf y\,$ expressed by matrices as \begin{equation} \lavvra{\mathbf x}{\mathrm A}{\mathbf y}\e \begin{bmatrix} \overline x_1 & \overline x_2 & \cdots & \overline x_n \vphantom{\dfrac{a}{b}}\\ \end{bmatrix} \begin{bmatrix} a_{11} & a_{11} & \cdots & a_{1n} \vphantom{\dfrac{a}{b}}\\ a_{21} & a_{22} & \cdots & a_{2n} \vphantom{\dfrac{a}{b}}\\ \vdots & \vdots & \vdots & \vdots\vphantom{\dfrac{a}{b}}\\ a_{n1} & a_{n2} & \cdots & a_{nn}\vphantom{\dfrac{a}{b}}\\ \end{bmatrix} \begin{bmatrix} y_1 \vphantom{\dfrac{a}{b}}\\ y_2 \vphantom{\dfrac{a}{b}}\\ \vdots \vphantom{\dfrac{a}{b}}\\ y_n \vphantom{\dfrac{a}{b}}\\ \end{bmatrix} \tag{05}\label{05} \end{equation} Under this spirit you could look at the $\,S_k\,$ as $2\times 1$ matrices and more precisely \begin{equation} S_k\e \left. \begin{cases} \begin{bmatrix} 1 \vphantom{\dfrac{a}{b}}\\ 0 \vphantom{\dfrac{a}{b}}\\ \end{bmatrix} \texttt{for} \p 1\\ \\ \begin{bmatrix} 0 \vphantom{\dfrac{a}{b}}\\ 1 \vphantom{\dfrac{a}{b}}\\ \end{bmatrix} \texttt{for} \m 1 \end{cases}\right\} \tag{06}\label{06} \end{equation} (note : this reminds us the up and down states of a spin-1/2 particle or the up and down quarks of isospin-1/2 particle).

So if for example $\,S_3\e\m 1\,$ and $\,S_8\e\p 1\,$ then \begin{equation} \lavvra{S_3}{\mathrm T}{S_8}\e \begin{bmatrix} 0 & 1 \vphantom{\dfrac{a}{b}}\\ \end{bmatrix} \begin{bmatrix} t_{11} & t_{11} \vphantom{\dfrac{a}{b}}\\ t_{21} & t_{22} \vphantom{\dfrac{a}{b}} \end{bmatrix} \begin{bmatrix} 1 \vphantom{\dfrac{a}{b}}\\ 0 \vphantom{\dfrac{a}{b}} \end{bmatrix}\e \begin{bmatrix} 0 & 1 \vphantom{\dfrac{a}{b}}\\ \end{bmatrix} \begin{bmatrix} t_{11} \vphantom{\dfrac{a}{b}}\\ t_{21} \vphantom{\dfrac{a}{b}} \end{bmatrix}\e t_{21} \tag{07}\label{07} \end{equation} For the rest look in the other till now two answers.