Condition number (or estimate) of a very large matrix

In summary, the speaker is working on an integral-equation problem in electromagnetics and is using the fast multipole method to solve a large linear system. They are trying to find the condition number of the matrix but are unable to store it entirely in memory. They are seeking a method to estimate the condition number without explicit calculation of all elements. Some helpful links are provided for this.
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Demian^^
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Hello,

I am working on an integral-equation problem in the field of electromagnetics, which gives me a very large linear system that needs to be solved. I use a fairly recent method for this, namely the fast multipole method, which allows me to calculate a matrix-vector product in a fast way, so that an iterative solution of the linear system becomes possible.
Anyway, the integral equation I use is known to be relatively ill-conditioned and I want to find out the extent of the problem by taking the condition number of my matrix. However, the elements are not all explicitely calculated, FMM allows for the calculation of the matrix-vector product without having to calculate all the elements. I do ofcourse have written a number of routines to explicetely calculate the elements. The dimension of the matrix easily exceeds 80000, so that it is impossible to store it entirely in the memory.

My question is therefore if anyone knows a method to calculate or estimate the condition number of a very large matrix, of which all the elements are not a priori calculated but can be calculated, altho not all simultaneously stored. A fairly rough estimation would already be satisfactory.

In any case, thanks.
Joris
 
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1. What is the condition number of a matrix?

The condition number of a matrix is a measure of how sensitive the output of a linear system is to changes in the input. It is represented by a number and can help determine the accuracy and stability of a numerical algorithm.

2. How is the condition number calculated?

The condition number is calculated by taking the ratio of the largest and smallest singular values of a matrix. It can also be calculated using other methods such as the ratio of the largest and smallest eigenvalues.

3. What does a large condition number indicate?

A large condition number indicates that the matrix is ill-conditioned, meaning small changes in the input can result in large changes in the output. This can lead to numerical instability and inaccurate results.

4. How does the size of a matrix affect its condition number?

The size of a matrix can greatly affect its condition number. As the size of the matrix increases, the condition number tends to increase as well. This is because larger matrices have more degrees of freedom and are more likely to be ill-conditioned.

5. Can the condition number be used to compare different matrices?

Yes, the condition number can be used to compare different matrices. A lower condition number indicates a more well-conditioned matrix, meaning it is less sensitive to changes in the input. However, it is important to note that the condition number alone does not provide a complete picture and should be used in conjunction with other measures.

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