In the same line of thoughts as this post, I am trying to understand better in which cases quantum computers could be useful to simulate materials under some constraints on what the quantum computer can do.
I consider a class of Hamiltonians among which we can find the Ising models without external magnetic field:
$$H=\sum_{i=1}^{\textrm{Poly}(n)} c_i P^{(i)}_Z \tag{1}.$$
$P^{(i)}_Z$ is an n-Pauli operator which is a tensor product of $\mathbb{I}$ and $Z$. $\textrm{Poly}(n)$ means that my sum contains a polynomial number of terms as a function of the number of qubits $n$. The Ising model in the absence of an external magnetic field, being written $H=\sum_{\langle i,j\rangle} J_{ij} Z_i Z_j$ is then one particular choice for $H$.
My question:
Let's assume that I am able to evaluate $\langle \psi | H | \psi \rangle$ efficiently, for any entangled state $|\psi\rangle$. Is there anything useful I could access in terms of physics with that?
More context
I know that one "hot question" about the Ising model is to be able to find its ground state. However this ground state in the absence of magnetic field is necessarily a tensor product (so it is not very useful to consider an entangled state in this case). Also, to find it, a brute-force approach would be to try exponentially many ansatz (hence even if $\langle \psi | H | \psi \rangle$ is "easy" to evaluate it is not enough to do something interesting).
That being said, it could be that in some cases it is interesting to study the properties of this Ising model with initial entangled state. I don't have any specific idea in mind but I don't find a reason why such cases would necessarily be un-interesting.
I hope it provides a little bit more context behind my question.