Doubt about Jacobi's diagonalization method

In summary: This is because the algorithm is based on the principle of finding the largest non-diagonal element in each iteration and reducing it, which means that as the number of iterations increases, the larger element will also decrease. However, the rate of decrease is not constant and can vary depending on the specific matrix being diagonalized. This is why the graphical attachment shows a logarithmic decrease in the maximum element as the number of iterations increases. In summary, the Jacobi diagonalization method for symmetric matrices has slow convergence due to the number of iterations required being proportional to the size of the matrix. The rate of decrease of the largest element outside the diagonal also increases as the number of iterations increases, but this decrease is not constant and can vary depending on the
  • #1
Cloruro de potasio
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TL;DR Summary
Number of iterations required in the Jacobi symmetric matrix diagonalization method
Good Morning,

I am using the Jacobi diagonalization method for symmetric matrices and I have realized that as the number of iterations progresses, the speed with which the larger element (in absolute value) outside the diagonal of the diagonal becomes smaller Matrices are increasing (graphical attachment showing the logarithm of the value of the maximum element (in absolute value) of the matrix together depending on the number of iteration.

I don't understand very well why this happens, can someone help me?

Thank you very much in advance and greetings

1574508818069.png
 
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  • #2
The Jacobi method of matrix diagonalization has a slow convergence. The method is an iterative one and for reducing a ##n## - dimensional symmetric matrix to a diagonal one, it requires a number of iterations proportional to ##n##. Now, in each iteration, the number of off-diagonal elements to be annihilated is proportional to ##n^2## - i.e. we have an order of ##n^3## operations. The annihilation of one pair of off-diagonal elements affects the values of others in the same column and row. So, matrix elements that have been put to zero in some operation may become non-zero later on, when another pair is being reduced.
 
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  • #3
Thank you very much,

I understand that the number of iterations is proportional to the size of the matrix to be diagonalized, but ... why does the rate of decrease of the largest element outside the diagonal increase as the number of iterations increases?
 
  • #4
Cloruro de potasio said:
but ... why does the rate of decrease of the largest element outside the diagonal increase as the number of iterations increases?

Because it goes to convergence depending on the number of iterations but at a slow rate in general.
 
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1. What is Jacobi's diagonalization method and how does it work?

Jacobi's diagonalization method is a technique used to find the eigenvalues and eigenvectors of a symmetric matrix. It works by repeatedly applying a series of rotations to the original matrix in order to eliminate off-diagonal elements, until the remaining matrix is diagonal.

2. How does Jacobi's diagonalization method compare to other methods for finding eigenvalues and eigenvectors?

Jacobi's method is an iterative process and can be computationally expensive for large matrices. However, it is guaranteed to converge to the correct eigenvalues and eigenvectors for symmetric matrices, unlike other methods such as power iteration which may only find the dominant eigenvalue and corresponding eigenvector.

3. What types of matrices can be diagonalized using Jacobi's method?

Jacobi's method is specifically designed for symmetric matrices. It will not work for non-symmetric matrices, and may not produce accurate results for matrices with complex or repeated eigenvalues.

4. Can Jacobi's diagonalization method be used for non-square matrices?

No, Jacobi's method can only be applied to square matrices. It is not possible to find eigenvalues and eigenvectors for non-square matrices.

5. Are there any limitations or drawbacks to using Jacobi's diagonalization method?

As mentioned earlier, Jacobi's method can be computationally expensive for large matrices and may not produce accurate results for certain types of matrices. Additionally, it is an iterative process and may require a large number of iterations to reach convergence, making it less efficient compared to other methods for finding eigenvalues and eigenvectors.

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