What is the Spectral Radius of Partitioned Matrices M1 and M2?

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In summary, two partitioned matrices M1 and M2 are given, and the problem is to show that their spectral radius is equal. The real problem is similar but simpler (or more complex). However, more constraints are needed to find counterexamples where the equality does not hold. The matrices are defined in terms of constants and positive definite, symmetric matrices C and G.
  • #1
ali987
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Hi everyone,

consider two following partitioned matrices:

[tex]\begin{array}{l}
{M_1} = \left[ {\begin{array}{*{20}{c}}
{ - \frac{1}{2}{X_1}} & {{X_2}} \\
{{X_3}} & { - \frac{1}{2}{X_4}} \\
\end{array}} \right] \\
{M_2} = \left[ {\begin{array}{*{20}{c}}
{\begin{array}{*{20}{c}}
{{X_1}} & { - I} \\
I & 0 \\
\end{array}} & {\begin{array}{*{20}{c}}
0 & 0 \\
0 & 0 \\
\end{array}} \\
{\begin{array}{*{20}{c}}
0 & 0 \\
0 & 0 \\
\end{array}} & {\begin{array}{*{20}{c}}
{{X_4}} & { - I} \\
I & 0 \\
\end{array}} \\
\end{array}} \right] \\
\end{array}[/tex]

I want to show that spectral radius (maximum absolute value of eigenvalues) of M1 and M2 are equal, but I don't know how!

this is general form of my problem the real one is somewhat easier (or maybe more complex)!
 
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  • #2
you need more constraints on the problem, one can find counterexamples such that this is not true.
 
  • #3
[tex]\begin{array}{l}
{X_1} = A_2^{ - 1}{B_2} \\
{X_2} = \Delta A_2^{ - 1}L \\
{X_3} = \Delta A_1^{ - 1}{L^T} \\
{X_4} = A_1^{ - 1}{B_1} \\
\end{array}[/tex]

In which

[tex]\begin{array}{l}
{A_1} = G + \frac{{{\Delta ^2}}}{4}{L^T}{C^{ - 1}}L \\
{A_2} = C + \frac{{{\Delta ^2}}}{4}L{G^{ - 1}}{L^T} \\
{B_1} = 2\left( {\frac{{{\Delta ^2}}}{4}{L^T}{C^{ - 1}}L - G} \right) \\
{B_2} = 2\left( {\frac{{{\Delta ^2}}}{4}L{G^{ - 1}}{L^T} - C} \right) \\
\end{array}[/tex]

where

[tex]\Delta = [/tex] positive constant coefficient

C and G are symmetric and positive definite.
 

1. What is spectral radius?

Spectral radius is a mathematical term that refers to the largest absolute value of the eigenvalues of a matrix or operator. It is used to measure the stability of a system or the convergence rate of an iterative method.

2. How is spectral radius calculated?

The spectral radius can be calculated by finding the eigenvalues of the matrix or operator and taking the absolute value of each eigenvalue. The spectral radius is then equal to the largest value among these absolute values.

3. What is the significance of spectral radius in scientific research?

Spectral radius is an important concept in various fields of science, including engineering, physics, and computer science. It is used to analyze the behavior of complex systems and to determine the stability of numerical methods used in scientific simulations.

4. Can the spectral radius be greater than 1?

Yes, the spectral radius can be greater than 1. In fact, if the spectral radius is greater than 1, it indicates that the system or method is unstable and may not converge to a solution.

5. How does spectral radius relate to other matrix properties?

The spectral radius is closely related to other matrix properties, such as the condition number and the norm. In general, a larger spectral radius indicates a more ill-conditioned matrix, which can lead to numerical instability in computations.

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