How to Handle Zero Eigenvalues in the Generalized Eigenvalue Problem?

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SUMMARY

The discussion focuses on handling zero eigenvalues in the Generalized Eigenvalue Problem defined by the matrices A and B. The user employs Mathematica to compute the eigenvalues, revealing two zero eigenvalues, indicating redundancy in the system. The rank of matrix A is confirmed to be 6, while matrix B has a rank of 4. The conversation highlights that the presence of zero eigenvalues can have a physical interpretation, particularly in mechanical systems, and explores methods to reduce the system before calculating eigenvalues to avoid trivial solutions.

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  • Understanding of Generalized Eigenvalue Problems
  • Familiarity with matrix rank concepts
  • Proficiency in using Mathematica for numerical computations
  • Knowledge of physical interpretations of eigenvalues in mechanical systems
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  • Learn about the implications of zero eigenvalues in mechanical systems
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Mathematicians, engineers, and researchers dealing with eigenvalue problems, particularly in the context of mechanical systems and numerical analysis.

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Hi all,

I need to find the λ and the ai that solves the Generalized eigenvalue problem

[A]{a}=-λ2 {a}

with

[A]=
Code:
-1289.57,1204.12,92.5424,-7.09489,-25037.4,32022.5,-10004.3,3019.17
1157.46,-1077.94,-0.580522,-78.9482,32022.5,-57353.5,36280.6,-10949.6
166.577,-103.776,1494.41,-1557.21,-10004.3,36280.6,-63053.2,36776.9
-34.4753,-22.407,-1586.37,1643.25,3019.17,-10949.6,36776.9,-28846.5
-22840.1,29254.3,-9328.5,2914.31,-1289.57,1157.46,166.577,-34.4753
29254.3,-51067,31724.8,-9912.15,1204.12,-1077.94,-103.776,-22.407
-9328.5,31724.8,-54591.9,32195.6,92.5424,-0.580522,1494.41,-1586.37
2914.31,-9912.15,32195.6,-25197.7,-7.09489,-78.9482,-1557.21,1643.25

and

=

Code:
0,0,0,0,1875.81,0,0,0
0,5019.07,0,0,0,22535.3,0,0
0,0,-5019.07,0,0,0,22535.3,0
0,0,0,0,0,0,0,937.905
835.2,0,0,0,0,0,0,0
0,5003.02,0,0,0,5019.07,0,0
0,0,5003.02,0,0,0,-5019.07,0
0,0,0,417.6,0,0,0,0

Using mathematica I get for lambdas {75.1098, 35.2687, 34.3082, 15.2013, 4.3281, 1.35478,
5.38827*10^-154, -2.06904*10^-154}

The last two eigenvalues are zero. That made me think that two equations are redundant. I confirmed that with mathematica. Rank of A is 6.

How can I reduce the system? I tried deleting two rows and columns, but for all the combinations the matrix B is singular.
Notice that the first and last column/row of the matrix B have only one value different from zero. Is anything I can do to exploit that?

Best
 
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Why do you think having two zero eigenvalues is an issue? If A has rank 6 and B has rank 4, that is what you would expect to get.

For example if A was the mass matrix and B the stiffness matrix of a structure, the two zero eigenvalues just mean the system can move freely in two (generalized) directions. There is nothing "unphysical" or unreasonable about that.

You don't say what your matrices represent, but if they come from a physics problem the zero eigenvalues probably have a physical interpretation.
 
AlephZero said:
Why do you think having two zero eigenvalues is an issue? If A has rank 6 and B has rank 4, that is what you would expect to get.

For example if A was the mass matrix and B the stiffness matrix of a structure, the two zero eigenvalues just mean the system can move freely in two (generalized) directions. There is nothing "unphysical" or unreasonable about that.

You don't say what your matrices represent, but if they come from a physics problem the zero eigenvalues probably have a physical interpretation.

Thanks AlephZero. The zero eigenvalues do have a physical interpretation and it is related to what you said.

Those special cases are treated separately and I do not need the associated eigenvectors.

What I do up to now is solve the 8x8 system and then remove the zero eigenvalues. I want to know if there is a way reduce the system before calculating the eigenvalues so as to have the nontrivial eigenvalues.

Best
 

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