How can I diagonize this n×n matrix Hamiltonian?

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In summary, the conversation discusses finding a base to diagonize a Hamiltonian, which is given as an n×n matrix. The suggested method is to calculate the eigenvalues and use the matrix of eigenfunctions to transform the base. The attempt at a solution involved calculating the determinant, but it was too complicated to do in n dimensions. An alternative method of expressing H as ##H_{ij} = \delta_{i (j-1)}+\delta_{i (j+1)}## is suggested.
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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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  • #2
is there someone could make it?
 
  • #3
You could try expressing H as ##H_{ij} = \delta_{i (j-1)}+\delta_{i (j+1)}##.
 

Related to How can I diagonize this n×n matrix Hamiltonian?

1. What is the purpose of diagonization of a matrix?

The purpose of diagonization of a matrix is to simplify the matrix and make it easier to perform calculations on it. It also helps to reveal the underlying structure and properties of the matrix.

2. How is a matrix diagonized?

A matrix is diagonized by finding a set of linearly independent eigenvectors that form a basis for the matrix. These eigenvectors are used to construct a diagonal matrix that is similar to the original matrix.

3. What are the benefits of diagonizing a matrix?

Diagonizing a matrix can help to solve systems of linear equations, since the diagonal matrix is easier to work with. It also helps to identify the eigenvalues and eigenvectors of the matrix, which are important in many applications such as physics, engineering, and computer science.

4. Can any matrix be diagonized?

No, not all matrices can be diagonized. A matrix can only be diagonized if it is square and has a set of linearly independent eigenvectors. If the matrix does not have enough eigenvectors, it cannot be diagonized.

5. What is the difference between diagonalization and diagonalization?

Diagonalization is the process of finding a diagonal matrix that is similar to the original matrix, while diagonalization is the process of transforming a non-diagonal matrix into a diagonal matrix. They are essentially the same process, but the terms are often used interchangeably.

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