Eigenvalues <1 imply 0 as a limit

In summary, the question is asking to show that when a complex matrix A has a spectral radius less than 1, its nth power approaches 0 as n goes to infinity. The solution is straightforward when A has a full set of eigenvectors, but becomes more difficult when it does not. In that case, A can still be put into Jordan Normal Form, where the nth power will have the n powers of the eigenvalues on the diagonal and constants times lower powers of the eigenvalues above the diagonal. This can be seen in the example given.
  • #1
slamminsammya
14
0
The following question was posed on an old qualifying exam for linear algebra:

Suppose A is an n by n complex matrix, and that A has spectral radius <1 (the eigenvalue with largest norm has norm <1). Show that A^n approaches 0 as n goes to infinity.

The solution is easy when the eigenspace of A is equal to n, for one can show that A is similar to a diagonal matrix whose entries are the eigenvalues of A. I am having trouble showing that A must go to 0 in the case when the geometric multiplicity of the eigenvalues is less than n (when the eigenspace of A fails to span the space).
 
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  • #2
If A does not have a "full set" of eigenvectors, it can still be put into "Jordan Normal Form", with the eigenvalues along the diagonal and "1"s in some of the positions just above the normal form. It can be shown that the nth power of such a matrix have the n powers of the eigenvalues on the diagonal and constants, times lower powers of the eigenvalues above the diagonal.

For example, the nth power of
[tex]\begin{bmatrix}a & 1 & 0 \\ 0 & a & 1 \\ 0 & 0 & a\end{bmatrix}[/tex]
is
[tex]\begin{bmatrix}a^n & na^{n-1} & n(n-1)a^{n-2}\\ 0 & a^n & na^{n-1} \\ 0 & 0 & a^n\end{bmatrix}[/tex].
 

What does it mean when eigenvalues are less than 1?

When the eigenvalues of a matrix are less than 1, it indicates that the matrix is shrinking the magnitude of its inputs. In other words, the matrix is decreasing the size of the vectors it operates on.

How do eigenvalues relate to the limit of a matrix?

If all the eigenvalues of a matrix are less than 1, then the limit of that matrix as it is repeatedly multiplied will approach 0. This is because each multiplication by the matrix will shrink the vector, eventually resulting in a vector of length 0.

Can a matrix have eigenvalues less than 1 and still have a non-zero limit?

Yes, it is possible for a matrix to have eigenvalues less than 1 and still have a non-zero limit. This can occur if the eigenvalues are complex numbers, as they can still contribute to the limit even if their magnitude is less than 1.

What is the significance of eigenvalues less than 1 in applications?

Eigenvalues less than 1 have various implications in different applications. For example, in population dynamics, they can indicate that the population will eventually decrease to 0. In signal processing, they can indicate that a system is stable and will not diverge over time.

How are eigenvalues less than 1 used in data analysis?

In data analysis, eigenvalues less than 1 can be used to reduce the dimensionality of a dataset. By identifying and removing dimensions with low eigenvalues, the remaining dimensions can capture the majority of the variation in the data with less information loss.

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