How can I diagonize this n×n matrix Hamiltonian?

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To diagonalize the given n×n Hamiltonian matrix, the approach involves calculating its eigenvalues using the determinant equation det|λId - H|=0. The matrix is structured with specific non-zero entries that suggest a pattern, making it potentially easier to express in terms of Kronecker delta functions. However, the complexity of the determinant calculation in n dimensions poses a challenge. The discussion seeks alternative methods or insights to simplify this process for finding the eigenvalues and subsequently the eigenfunctions. Understanding the matrix's structure could provide a more straightforward path to diagonalization.
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Homework Statement


sorry for my english..

I was asked to find a base to diagonize a Hamiltonian, which could been written in the given base as below:

n×n matrix

0 1 0 0 0 ... 0 0
1 0 1 0 0 ... 0 0
0 1 0 1 0 ... 0 0
0 0 1 0 1 ... 0 0
... ... ... ... ...
0 0 0 0 0 ... 0 1
0 0 0 0 0 ... 1 0


Homework Equations


In order to diagonize this Hamiltonian, I think one could calculate its eigenvalues in this base to get
eigenfuntions, hence one can use matrix of eigenfunctions to tranforms this base to obtain a new base which diagonize Hamiltonian as
λ1 0 ... 0
0 λ2 ... 0
...
0 ... λn


The Attempt at a Solution


I tried to calculate the determinant to obtain eignenvalues of Hamiltonian by
det|λId - H|=0
But it is too complicated and I didn't find a way to calculate it in n dimensions. Is there some way that I didn't know to calculate the determinant?
 
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is there someone could make it?
 
You could try expressing H as ##H_{ij} = \delta_{i (j-1)}+\delta_{i (j+1)}##.
 
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