Suppose I have a Hamiltonian that depends on the continuous vector parameter $\boldsymbol{\theta}$, and the ground state corresponds to line/plane or some other $1$ to $p-1$ dimensional subspace of the $p\,$ dimensional space of my parameter vector.
And suppose I wish to find the ground state energy using a statistical mechanics/analysis method:
- I write my partition function $Z = \displaystyle\int d\boldsymbol{\theta}\,e^{-\beta H(\boldsymbol{\theta})}$
- I use the formula for the internal energy $U = -\dfrac{\partial}{\partial \beta} \ln(Z)$
- And I take the limit of $\beta \rightarrow \infty$ corresponding to $T\rightarrow 0$
This should give me the ground state energy. But, I am suspicious of whether the underlying mathematics suggests this is a fishy thing to do in the case of a degenerate ground state.
From my limited understanding of analysis:
I take:
$$U = \lim_{\beta \rightarrow \infty} \frac{\displaystyle \int d\boldsymbol{\theta}\,H(\theta)e^{-\beta H(\boldsymbol{\theta})}}{Z}$$
and this is handled with the saddle point method: Watson's lemma etc.
But while I understand how the saddle point method works (in terms of using a Taylor expansion of the Hamiltonian) for a single saddle point (this stack exchange post has a good overview) I don't think it works when there is a dimension $\dim \mathfrak g>0$ subspace for the ground state.
Would it be appropriate to do a Landau-type expansion of the Hamiltonian (though I have only come across Landau expansions of the free energy; and with macroscopic order parameters rather parameters on which the Hamiltonian depends!). But still, if I have a continuous region of the parameter space are ground states, then how to consider this analytical approach?