Characteristic equation formula for a nxn matrix ?

In summary, the characteristic equation for a 2x2 matrix can be given by t^2 - traceA + |A|. To generalize for a matrix of size 4x4 or higher, we can use the polynomial (x-\lambda_1)\times...\times (x-\lambda_n) = a_n x^n + a_{n-1}x^{n-1}... + a_1x + a_0, where a_{n-1} is the negative trace and a_0 is plus or minus the determinant of the matrix. The other coefficients are obtained by adding up multiples of the eigenvalues. This is derived from expanding the multiplication on the right hand side of the original equation
  • #1
sid9221
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So I know that the characteristic equation for a 2x2 matrix can be given by

[tex] t^2 - traceA + |A| [/tex]

So how would this be generalised for a 4x4 or higher matrix ?
 
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  • #2
You forgot some t's in your equation but it's clear what you are referring to.

The characteristic equation is a polynomial whose roots are the eigenvalues of the matrix. So if we have [tex](x-\lambda_1)\times...\times (x-\lambda_n) = a_n x^n + a_{n-1}x^{n-1}... + a_1x + a_0 [/tex]
then an-1 is the sum of the negatives of the eigenvalues, so an-1 is the negative trace. a0 is the product of the eigenvalues with minus signs, so a0 is plus or minus the determinant of the matrix (depending on whether n is even or odd). The other ones are constructed by adding up multiples of the eigenvalues, for example
[tex] a_{n-2} = \sum_{i<j} (-\lambda_i) (-\lambda_j) [/tex]
an-3 requires adding every way to multiply three of the eigenvalues, etc. This just comes from expanding the multiplication on the right hand side of the original equation... to get an xn-2 power you have to use two of the eigenvalues and the rest x's
 

What is the characteristic equation formula for a nxn matrix?

The characteristic equation formula for a nxn matrix is det(A - λI) = 0, where A is the nxn matrix, λ is the eigenvalue, and I is the identity matrix.

How do you find the eigenvalues of a nxn matrix?

To find the eigenvalues of a nxn matrix, we first need to find the characteristic equation by taking the determinant of (A - λI). Then, we solve for the values of λ that make the equation equal to 0, as those are the eigenvalues of the matrix.

What is the significance of the characteristic equation in linear algebra?

The characteristic equation is important in linear algebra because it helps us find the eigenvalues and corresponding eigenvectors of a matrix. These eigenvalues and eigenvectors are useful in solving various problems, such as finding the diagonalization of a matrix or solving systems of linear equations.

Can the characteristic equation formula be applied to any nxn matrix?

Yes, the characteristic equation formula can be applied to any square matrix, regardless of its size (n). However, the process of finding the eigenvalues and eigenvectors may become more complex as the size of the matrix increases.

Are there any alternative ways to find eigenvalues of a nxn matrix?

Yes, there are alternative methods such as using the diagonalization method, power method, or the QR algorithm. These methods may be more efficient for certain types of matrices, but the characteristic equation formula is still the most commonly used method for finding eigenvalues.

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