Properties of Defective Matrices in Space?

In summary, the set of defective matrices is path-connected and has measure zero. Defective matrices form a manifold. There are known properties about the topology or geometry of the set of defective matrices, but I am not familiar with them.
  • #1
madness
815
70
TL;DR Summary
What is the geometry/topology of the set of defective matrices
Let me start by saying that my question will be somewhat vague by mathematical standards. I'm not a mathematician! I'm looking for some intuition about how defective matrices are distributed in the space of all matrices. I understand that they are rare and in some sense discontinuous - matrices switch from being non-normal to defective with an infinitesimal change of parameters. But for example, do they form some kind of manifold? Does the set of defective matrices have measure zero? Are there any interesting known properties about the topology or geometry of the set of defective matrices?

Thanks for your thoughts.
 
Physics news on Phys.org
  • #2
Define defective matrix please!
 
  • #4
I suspect I might be able to make some headway into my question using the Jordan normal form. We can use this as a constructive definition of the set of defective matrices. A defective matrix A must satisfy A = P*J*inv(P), where J is a Jordan matrix and P is an invertible matrix. Conversely for any invertible P and Jordan matrix J, such an A will be a defective matrix. In the most extreme case where the matrix has only one eigenvector, J has lambda on the diagonal, 1 on the superdiagonal and zeros elsewhere. We could then ask what the set of such A looks like for arbitrary (invertible) P. Then we could proceed to the more complicated cases where A has 2 eigenvectors, 3 eigenvectors, ... up to N-1 eigenvectors. I'm not sure I can even picture the constraints on A in the case of 1 eigenvector though!
 
Last edited:
  • #6
madness said:
Does the set of defective matrices have measure zero?
Yes I think so, because a matrix can only be defective if its characteristic polynomial has a repeated root (this is a necessary, not sufficient condition). This has probability zero.

madness said:
Are there any interesting known properties about the topology or geometry of the set of defective matrices?
I think the space of defective matrices is path-connected. Any Jordan block can be joined by a path of defective matrices to, say, the block with eigenvalue ##1## of the same size by continuously changing the eigenvalue. Do this for all blocks of a matrix in Jordan form simultaneously, and then continuously change the ##0## in the ##(i,i+1)## positions between blocks to a ##1## (this does not change that the matrix is still defective since if a matrix other than the identity has ##1## as its only eigenvalue, then it cannot be diagonalizable). This gives a path from any matrix in Jordan form to the Jordan block of the same size with eigenvalue ##1##. Since any defective matrix is of the form ##SJS^{-1}## where ##J## is a nontrivial Jordan form, this should prove path-connectedness.

Surprisingly, I think this space might actually be a manifold. I'll post an argument later.
fresh_42 said:
I don't see how we could translate the existence qualifier on eigenvectors into an algebraic
A matrix fails to be diagonalizable if and only if its minimal polynomial has repeated roots.
 
  • Like
Likes fresh_42
  • #7
Infrared said:
A matrix fails to be diagonalizable if and only if its minimal polynomial has repeated roots.
So the criterion could be that for ##\chi_\mathbb{C}(A)=\prod (x-\lambda_k)^{n_k}## we require ##\prod n_k \neq 1## which looks Zariski open and dense, and thus no variety!?
 
  • #8
fresh_42 said:
... which looks Zariski open and dense, and thus no variety!?
Consider ##x\not =0## in the affine line. It is open and dense, yet it is a variety. It can be realized as the zero set of ##xy=1## in the plane. For the zeros of a polynomial you have ##p(x_1,x_2,...,x_n)y=1##. Same way as why the general linear group is an algebraic group.
 
  • Like
Likes fresh_42
  • #9
fresh_42 said:
So the criterion could be that for ##\chi_\mathbb{C}(A)=\prod (x-\lambda_k)^{n_k}## we require ##\prod n_k \neq 1## which looks Zariski open and dense, and thus no variety!?

I think ##\chi## usually refers to characteristic polynomial, not minimal polynomial. Anyway, this set is way too small to be Zariski open- most matrices are diagonalizable. In particular, the space of matrices with distinct eigenvalues is disjoint from our space and is Zariski open (since the complement is the zero set of the discriminant of the characteristic polynomial), but two nonempty Zariski open sets in ##M_{n\times n}=\mathbb{R}^{n^2}## cannot be disjoint.

Let's think about the ##2\times 2## case more: To fix notation, let ##X## be the set of ##2\times 2## matrices which have a repeated eigenvalue, and let ##Y\subset X## be the subspace of non-diagonalizable (defective) matrices. Note that ##Y=X-\{cI:c\in\mathbb{R}\}##. This is because the only diagonalizable ##2\times 2## matrix with repeated eigenvalue ##\lambda## is ##\lambda I##. In particular, ##Y## is a open subset (even Zariski open) of ##X##.

Let ##A=\begin{pmatrix}a & b\\c & d\end{pmatrix}## and ##\chi_A(\lambda)=\lambda^2-(a+d)\lambda+(ad-bc)## be its characteristic polynomial. Then ##X## is the zero set of ##\text{disc}(\chi_A)=(a+d)^2-4(ad-bc)=(a-d)^2+4bc=0##.

Consider the map ##F(A)=(a-d)^2+4bc##. Note that ##\nabla F=(2(a-d),4c,4b,-2(a-d))## is zero if and only if ##a=d## and ##b=c=0##, i.e. ##A## is a scalar matrix. So ##X=F^{-1}(0)## is a manifold away from the scalar matrices. Since ##Y## is an open subset of ##X## not containing the scalar matrices, it should be a manifold.

I think the only part of this argument that doesn't generalize easily to higher dimensions is explicitly computing ##F## and ##\nabla F##.
 
Last edited:

What is a defective matrix?

A defective matrix is a square matrix that does not have a full set of linearly independent eigenvectors. This means that it cannot be diagonalized and does not have a complete set of eigenvalues.

What is the significance of studying defective matrices?

Studying defective matrices is important because they can arise in many real-world applications, such as in quantum mechanics and control theory. Understanding their properties and behavior can help us solve problems and make predictions in these fields.

How can defective matrices be identified?

Defective matrices can be identified by computing their eigenvalues and eigenvectors. If the matrix does not have a full set of linearly independent eigenvectors, it is considered defective.

Can defective matrices be useful?

Yes, defective matrices can still be useful in certain situations. For example, in control theory, they can represent systems with repeated eigenvalues, which can be manipulated to achieve desired outcomes.

How are defective matrices different from non-defective matrices?

The main difference between defective and non-defective matrices is that non-defective matrices have a full set of linearly independent eigenvectors and can be diagonalized, while defective matrices cannot. This leads to different properties and behaviors in terms of eigenvalues, eigenvectors, and matrix operations.

Similar threads

Replies
9
Views
1K
  • Science and Math Textbooks
Replies
27
Views
2K
  • Quantum Physics
Replies
6
Views
2K
  • Linear and Abstract Algebra
Replies
11
Views
2K
  • STEM Academic Advising
Replies
14
Views
702
  • Linear and Abstract Algebra
Replies
12
Views
6K
  • Set Theory, Logic, Probability, Statistics
Replies
4
Views
1K
  • Beyond the Standard Models
Replies
2
Views
3K
  • Linear and Abstract Algebra
Replies
18
Views
5K
Replies
11
Views
1K
Back
Top