Diagonalization of an almost diagonal matrix

In summary: Expert summarizerIn summary, to show that a n x n matrix with 1 on the diagonal entries apart from the ith column which has a -1 and any real number in each entry in the ith row is diagonalisable, we can use the fact that the eigenvalues are -1 and 1 with multiplicity n-1. To find the eigenvectors corresponding to the eigenvalue 1, we can use the fact that the matrix is symmetric and find the null space of the matrix (A-I). This will give us n-1 linearly independent eigenvectors, which is enough to show that the matrix is diagonalisable.
  • #1
TheHup
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Homework Statement


If we have a n x n matrix with 1 on the diagonal entries apart from the ith column which has a -1. As well as this ith row can have any real number in each entry. Other than this the matrix is 0 everywhere.

Show this matrix is diagonalisable.


Homework Equations





The Attempt at a Solution


I know the eigenvalues of the matrix are -1 and 1 (with multiplicity n-1). I can find the eigenvector corresponding to the eigenvalue -1.

However I can't find eigenvectors corresponding to the eigenvalues 1. I assume that if I could do this then they would be n-1 linearly independent eigenvectors which I think would be enough to show that the matrix is diagonalisable.
 
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  • #2


Dear forum post author,

Thank you for your question. It is correct that the eigenvalues of this matrix are -1 and 1 with multiplicity n-1. To find the eigenvectors corresponding to the eigenvalue 1, you can use the fact that the matrix is symmetric. This means that the eigenvectors corresponding to different eigenvalues are orthogonal to each other. So, you can find the eigenvectors corresponding to the eigenvalue 1 by finding the null space of the matrix (A-I), where I is the n x n identity matrix. This will give you n-1 linearly independent eigenvectors, which is enough to show that the matrix is diagonalisable.

I hope this helps. Good luck with your research!
 

1. What is diagonalization of an almost diagonal matrix?

Diagonalization is a mathematical process used to simplify a matrix by transforming it into a diagonal matrix, where all the elements are zero except for those on the main diagonal. An almost diagonal matrix is a matrix that is close to being diagonal, but may have some non-zero elements off the main diagonal.

2. Why is diagonalization of an almost diagonal matrix important?

Diagonalization allows for easier computation and manipulation of the matrix, as well as making its properties and relationships to other matrices more apparent. It is an important tool in linear algebra, and is used in many fields of science, including physics, engineering, and economics.

3. How is diagonalization of an almost diagonal matrix done?

The process of diagonalization involves finding a diagonal matrix that is similar to the given matrix. This is done by finding a set of eigenvectors and eigenvalues of the matrix, and using them to construct a transformation matrix. Multiplying the original matrix by this transformation matrix results in a diagonal matrix.

4. Can any matrix be diagonalized?

Not all matrices can be diagonalized. Only square matrices that have a complete set of linearly independent eigenvectors can be diagonalized. Additionally, a matrix may have repeated eigenvalues, making it only partially diagonalizable. In this case, the diagonal matrix will have some non-zero elements off the main diagonal.

5. What are the applications of diagonalization of an almost diagonal matrix?

Diagonalization has many applications in mathematics, science, and engineering. It is used in solving differential equations, computing matrix powers, and finding solutions to systems of linear equations. It is also used in data analysis, signal processing, and image compression.

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