I would like to solve an eigenvalue problem of a Hamiltonian. I was able to find the lowest eigenvalue by converting the Hamiltonian into a matrix and applying linear algebra eigenvalue techniques. But this method is extremely cumbersome and does not generalize to arbitrary-sized Hamiltonians. I was hoping somebody could point to a more general approach. Here is the definition of the problem:
Let $\vert \psi_N \rangle$ denote the uniform superposition, $$\vert \psi_N \rangle = \frac{1}{\sqrt{N}}\sum^{N-1}_{i=0}\lvert i \rangle.$$ Then $\vert \psi_N \rangle$ is the ground state of the Hamiltonian $H_0 = I - \lvert \psi_N \rangle \langle \psi_N \lvert$ with the lowest eigenvalue $0$. Let $\vert m \rangle = \vert 1 0...0 \rangle$. Then it is the ground state of the Hamiltonian $H_m = I - \vert m \rangle \langle m \vert$.
For $ s \in [0,1]$ define the Hamiltonian $$H(s) = (1-s)H_0 + s H_m.$$
What would be the general approach to solving the following eigenvalue problem for an arbitrary $N$ \begin{align} H(s) \lvert E_k, s \rangle = E_k(s) \lvert E_k, s\rangle \end{align} where $E_k(s)$ is the $k$th eigenvalue at time $s$.
I was able to solve the problem for $N = 4$ by converting the Hamiltonian into a matrix and then using computer algebra I got $$E_0(s) = \displaystyle \frac{1}{2} - \frac{\sqrt{3 s^{2} - 3 s + 1}}{2}.$$ The problem with this approach is that it is not general and requires conversion to matrices and then solving the eigenvalue problem. I suspect that it is possible to get the answers in terms of $N$ and $s$ without fixing the size $N$ and expressing the Hamiltonian as a matrix.