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What does eigenvalues mean?

Updated: 12/21/2022
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Well in linear algebra if given a vector space V,over a field F,and a linear function A:V->V (i.e for each x,y in V and a in F,A(ax+y)=aA(x)+A(y))then ''e" in F is said to be an eigenvalue of A ,if there is a nonzero vector v in V such that A(v)=ev.Now since every linear transformation can represented as a matrix so a more specific definition would be that if u have an NxN matrix "A" then "e" is an eigenvalue for "A" if there exists an N dimensional vector "v" such that Av=ev.Basically a matrix acts on an eigenvector(those vectors whose direction remains unchanged and only magnitude changes when a matrix acts on it) by multiplying its magnitude by a certain factor and

this factor is called the eigenvalue of that eigenvector.

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Q: What does eigenvalues mean?
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Related questions

Do similar matrices have the same eigenvalues?

Yes, similar matrices have the same eigenvalues.


How do you find eigenvalues of a 3 by 3 matrix?

Call your matrix A, the eigenvalues are defined as the numbers e for which a nonzero vector v exists such that Av = ev. This is equivalent to requiring (A-eI)v=0 to have a non zero solution v, where I is the identity matrix of the same dimensions as A. A matrix A-eI with this property is called singular and has a zero determinant. The determinant of A-eI is a polynomial in e, which has the eigenvalues of A as roots. Often setting this polynomial to zero and solving for e is the easiest way to compute the eigenvalues of A.


Do similar matrices have the same eigenvectors?

No, in general they do not. They have the same eigenvalues but not the same eigenvectors.


Can a Hermitian Matrix possess Complex Eigenvectors?

Yes. Simple example: a=(1 i) (-i 1) The eigenvalues of the Hermitean matrix a are 0 and 2 and the corresponding eigenvectors are (i -1) and (i 1). A Hermitean matrix always has real eigenvalues, but it can have complex eigenvectors.


What do you mean by eigen value and eigen function?

In linear algebra, there is an operation that you can do to a matrix called a linear transformation that will get you answers called eigenvalues and eigenvectors. They are to complicated to explain in this forum assuming that you haven't studied them yet, but their usefulness is everywhere in science and math, specifically quantum mechanics. By finding the eigenvalues to certain equations, one can come up with the energy levels of hydrogen, or the possible spins of an electron. You really need to be familiar with matrices, algebra, and calculus though before you start dabbling in linear algebra.


What has the author Carl Sheldon Park written?

Carl Sheldon Park has written: 'Real eigenvalues of unsymmetric matrices' -- subject(s): Aeronautics


What has the author James V Burke written?

James V. Burke has written: 'Differential properties of eigenvalues' -- subject(s): Accessible book


What is Eigen analysis?

Eigenvalues and eigenvectors are properties of a mathematical matrix.See related Wikipedia link for more details on what they are and some examples of how to use them for analysis.


What has the author R S Caswell written?

R S. Caswell has written: 'A Fortran code for calculation of Eigenvalues and Eigenfunctions in real potential wells'


What has the author Gaetano Fichera written?

Gaetano Fichera has written: 'Numerical and quantitative analysis' -- subject(s): Differential equations, Eigenvalues, Numerical solutions


What has the author Hung Chang written?

Hung Chang has written: 'Using parallel banded linear system solvers in generalized Eigenvalue problems' -- subject(s): Eigenvalues


What are eigenvalues and eigenvectors?

An eigenvector is a vector which, when transformed by a given matrix, is merely multiplied by a scalar constant; its direction isn't changed. An eigenvalue, in this context, is the factor by which the eigenvector is multiplied when transformed.