Eigenvalue of matrix proof by induction

In summary, the proof by induction for the eigenvalue of a matrix involves demonstrating that if a square matrix has an eigenvalue for a smaller size, it also possesses an eigenvalue for a larger size. The base case typically starts with a 1x1 matrix, where the eigenvalue is simply the matrix itself. The inductive step assumes true for an n x n matrix and proves it for an (n+1) x (n+1) matrix by showing that the characteristic polynomial maintains a structure that guarantees the existence of at least one eigenvalue. This method effectively establishes the eigenvalue property for all square matrices through systematic reasoning.
  • #1
TanWu
17
5
Homework Statement
Show that if ##\alpha## is an eigenvalue of matrix ##B## then ##\alpha^{n}## is an eigenvalue of matrix ##B^{n}## for positive integer ##n##
Relevant Equations
##\alpha## is eigenvalue
##B\vec x = \alpha \vec x##
We consider base case (##n = 1##), ##B\vec x = \alpha \vec x##, this is true, so base case holds.

Now consider case ##n = 2##, then ##B^2\vec x = B(B\vec x) = B(\alpha \vec x) = \alpha(B\vec x) = \alpha(\alpha \vec x) = \alpha^2 \vec x##

Now consider ##n = m## case,

##B^m\vec x = B(B^{m - 1} \alpha) = B^m \alpha = \alpha^m \vec x##

Now consider ##n = m + 1## case,
##B^{m + 1}\alpha = B(B^m \alpha) = B(\alpha^m \vec x) = \alpha^m(B\vec x) = \alpha^k(\alpha \vec x) = \alpha^{m + 1}\vec x##

Is that correct use of induction?
gratitude expressed to those who help.
 
Last edited by a moderator:
Physics news on Phys.org
  • #2
You can formulate more precisely. Instead of saying "consider ##n=m## case", we can say "assume that ## B^nx = \alpha ^nx ## for some ##n\geqslant 2##". Then for the case ##n+1## we have the equalities
[tex]
B^{n+1}x = BB^nx = B\alpha ^nx = \alpha ^nBx = \alpha ^n\alpha x = \alpha ^{n+1}x.
[/tex]
Right now you haven't made it explicit what your induction assumption is. Anyone familiar with the technique is able to fill in the gaps.
 
  • Like
Likes TanWu
  • #3
TanWu said:
Homework Statement: Show that if ##\alpha## is an eigenvalue of matrix ##B## then ##\alpha^{n}## is an eigenvalue of matrix ##B^{n}## for positive integer ##n##
Relevant Equations: $\alpha$ is eigenvalue
##B\vec x = \alpha \vec x##

We consider base case (##n = 1##), ##B\vec x = \alpha \vec x##, this is true, so base case holds.

Now consider case ##n = 2##, then ##B^2\vec x = B(B\vec x) = B(\alpha \vec x) = \alpha(B\vec x) = \alpha(\alpha \vec x) = \alpha^2 \vec x##
You shouldn't need to show it for ##n=2##. After the base case, state the induction hypothesis:
$$B^m\vec x = \alpha^m \vec x$$
is true for some integer ##m>1##.

Apply the induction hypothesis to show its true for ##m+1##, as you have done so. Then you can conclude it's true for all integers.
 
  • Like
Likes TanWu
  • #4
It is not wrong to check the claim up to ##m## manually. Sometimes that's even helpful. The induction hypothesis then is that the claim is true
  1. for some ##n\geqslant m## (weak induction);
  2. for all ##k\leqslant n##, where ##n\geqslant m## (strong induction).
In both cases the task is to prove the claim is true for ##n+1##. It doesn't matter which form of induction we use, they are equivalent.
 
Last edited:
  • Like
Likes docnet
  • #5
Sounds good, though I feel it's more concise/elegant to use weak induction here. But just to clarify, the claim being true for ##n+1##, or proving the claim is true for ##n+1##, is not any part of the induction hypothesis. Rather, it's the consequence that would follow if the induction hypothesis is true.
 
  • Like
Likes nuuskur
  • #6
Fair play on your last point. As for the first one, optimisation can be done later. First and foremost, it is important the argument is correct.
 
  • Like
Likes docnet
  • #7
@PeroK I have a nagging feeling that my statement in #5 about the induction hypothesis is not correct. If you have a moment, can you please point out what's wrong about it? Thank you.
 
  • #8
docnet said:
But just to clarify, the claim being true for n+1, or proving the claim is true for n+1, is not any part of the induction hypothesis.
Right. The induction hypothesis in this case is assuming that ##B^m\vec x = a^m\vec x## is true. Using this hypothesis, you show that it follows that ##B^{m+1}\vec x = a^{m+1}\vec x## must also be true. Of course you need to also establish that some base case is true.
 
  • Like
Likes nuuskur, PeroK and docnet

FAQ: Eigenvalue of matrix proof by induction

What is an eigenvalue of a matrix?

An eigenvalue of a matrix is a scalar value that, when multiplied by a corresponding eigenvector, produces the same result as applying the matrix to that eigenvector. Mathematically, for a square matrix A and a non-zero vector v, if there exists a scalar λ such that Av = λv, then λ is an eigenvalue of A.

What does proof by induction mean in the context of eigenvalues?

Proof by induction is a mathematical technique used to prove statements that are asserted for all natural numbers. In the context of eigenvalues, it can be used to show properties of eigenvalues or eigenvectors that hold for all matrices of a certain size, typically starting from a base case and then assuming it holds for an arbitrary case k to prove it for k+1.

How do you set up a proof by induction for eigenvalues?

To set up a proof by induction for eigenvalues, you first establish a base case, usually for a small matrix size (like 1x1 or 2x2). Then, you assume that the statement holds for an arbitrary n (inductive hypothesis), and you need to show that it also holds for n+1. This typically involves manipulating the characteristic polynomial or other properties of eigenvalues and matrices.

What is the characteristic polynomial and its role in finding eigenvalues?

The characteristic polynomial of a square matrix A is a polynomial obtained from the determinant of (A - λI), where I is the identity matrix and λ is a scalar. The roots of this polynomial are the eigenvalues of the matrix. In proofs involving induction, the characteristic polynomial plays a crucial role in establishing relationships between eigenvalues of matrices of different sizes.

Can you provide a simple example of using induction to prove a property of eigenvalues?

Certainly! For example, you might want to prove that any n x n matrix has exactly n eigenvalues (counting multiplicities). You would start with a base case for n=1, where the eigenvalue is simply the single entry of the 1x1 matrix. Then, assuming the statement holds for an n x n matrix, you would show that the determinant of the (n+1)x(n+1) matrix leads to a polynomial of degree n+1, thus proving that it has n+1 eigenvalues when you apply the inductive step.

Back
Top