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technical:ising1d [2022/10/29 13:58] – [Eigenvalues] chunchungtechnical:ising1d [2022/10/29 15:10] (current) – [Simple case 1: $J = 1$, $h = 0$] chunchung
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 \begin{equation} \lambda^2 - \left(e^{\beta (J+h)}+e^{\beta (J-h)}\right) \lambda + e^{2\beta J} - e^{-2\beta J}. \end{equation} \begin{equation} \lambda^2 - \left(e^{\beta (J+h)}+e^{\beta (J-h)}\right) \lambda + e^{2\beta J} - e^{-2\beta J}. \end{equation}
 Since the discriminant \begin{align} Since the discriminant \begin{align}
-  \left(e^{\beta (J+h)}+e^{\beta (J-h)}\right)^2 - 4 \left(e^{2\beta J} - e^{-2\beta J}\right) \notag \\ +\mathrm{Disc}_\lambda \left(e^{\beta (J+h)}+e^{\beta (J-h)}\right)^2 - 4 \left(e^{2\beta J} - e^{-2\beta J}\right) \notag \\ 
-& =  e^{2\beta(J+h)} + e^{2\beta(J-h)} + 2 e^{2\beta J} - 4 \left(e^{2\beta J} - e^{-2\beta J}\right) \notag \\ +& = e^{2\beta(J+h)} + e^{2\beta(J-h)} + 2 e^{2\beta J} - 4 \left(e^{2\beta J} - e^{-2\beta J}\right) \notag \\ 
-& =  \left(e^{\beta (J+h)}-e^{\beta (J-h)}\right)^2 + 4 e^{-2\beta J} \notag \\ +& = \left(e^{\beta (J+h)}-e^{\beta (J-h)}\right)^2 + 4 e^{-2\beta J} \notag \\ 
-& >  0 .+& >  0,
 \end{align} \end{align}
-The characteristic polynomial has two real roots, that is, the transfer matrix $T$ has two real eigenvalues.+the characteristic polynomial has two real roots, that is, the transfer matrix $T$ has two real eigenvalues.
  
 ====Eigenvalues==== ====Eigenvalues====
 The two eigenvalues are The two eigenvalues are
 \begin{align} \begin{align}
-\lambda_\pm &= \frac{1}{2} \left[ \left( e^{\beta(J+h)}+e^{\beta(J−h)} \right) \pm \sqrt{ \left(e^{\beta (J+h)}-e^{\beta (J-h)}\right)^2 + 4 e^{-2\beta J} } \right] \\+\lambda_\pm &= \frac{1}{2} \left[ \left( e^{\beta(J+h)}+e^{\beta(J−h)} \right) \pm \sqrt{ \left(e^{\beta (J+h)}-e^{\beta (J-h)}\right)^2 + 4 e^{-2\beta J} } \right] \notag \\
  &= e^{\beta J}\left[\cosh(\beta h)\pm\sqrt{\sinh^2(\beta h)+e^{-4\beta J}}\right]  &= e^{\beta J}\left[\cosh(\beta h)\pm\sqrt{\sinh^2(\beta h)+e^{-4\beta J}}\right]
 \end{align} \end{align}
 and the partition function is given by and the partition function is given by
-$$ Z = \lambda_+^N+\lambda_-^N . $$+\begin{equation} Z = \lambda_+^N+\lambda_-^N . \end{equation}
 ====Simple case 1: $J = 1$, $h = 0$==== ====Simple case 1: $J = 1$, $h = 0$====
 The eigenvalues become The eigenvalues become
-$$ \lambda_\pm = e^{\beta}\pm e^{-\beta}. $$+\begin{equation} \lambda_\pm = e^{\beta}\pm e^{-\beta}. \end{equation}
 The partition function is The partition function is
-$$ Z = \left(e^\beta+e^{-\beta}\right)^N+\left(e^\beta-e^{-\beta}\right)^N . $$+\begin{equation} Z = \left(e^\beta+e^{-\beta}\right)^N+\left(e^\beta-e^{-\beta}\right)^N . \end{equation}
  
 Generally, the average energy $U = \langle E\rangle$ can be calculated from the $\beta$-derivative of $-\log Z$: Generally, the average energy $U = \langle E\rangle$ can be calculated from the $\beta$-derivative of $-\log Z$:
-\begin{eqnarray*+\begin{align
-U & = \langle E\rangle \\ +U &= \langle E\rangle \notag \\ 
-& = Z^{-1} \sum_{\mathbf{s}} E e^{-\beta E} \\ +&= Z^{-1} \sum_{\mathbf{s}} E e^{-\beta E} \notag \\ 
-& = - Z^{-1} \frac{\partial}{\partial\beta} Z \\ +&= - Z^{-1} \frac{\partial}{\partial\beta} Z \notag \\ 
-& = - \frac{\partial}{\partial\beta}\log Z +&= - \frac{\partial}{\partial\beta}\log Z \\ 
-\end{eqnarray*}+&= \frac{N\left[\left(e^\beta+e^{-\beta}\right)^{N-1}\left(e^\beta-e^{-\beta}\right)+\left(e^\beta+e^{-\beta}\right)\left(e^\beta-e^{-\beta}\right)^{N-1}\right]}{\left(e^\beta+e^{-\beta}\right)^N+\left(e^\beta-e^{-\beta}\right)^N} \notag \\ 
 +&= N\frac{r+r^{N-1}}{1+r^N} 
 +\end{align} 
 +where $r = \left(e^\beta-e^{-\beta}\right)/\left(e^\beta+e^{-\beta}\right)<1$ is the ratio between the two eigenvalues.
  

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