Proving the uniqueness of eigenspaces

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Discussion Overview

The discussion revolves around proving the uniqueness of eigenspaces in the context of linear operators and their kernels. Participants explore various algebraic manipulations and approaches to demonstrate that if certain conditions hold for eigenvalues, then the corresponding eigenvectors must be unique. The scope includes mathematical reasoning and technical explanations related to linear algebra.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant presents a proof involving the kernels of operators related to eigenvalues and manipulates equations to derive conditions on eigenvectors.
  • Another participant suggests simplifying the problem by defining new operators and shows how to expand the square of these operators to analyze the eigenvector conditions.
  • A different participant discusses the uniqueness of inverses and the implications of applying operators multiple times, questioning the effect of singular operators on solution sets.
  • Further contributions involve using properties of polynomials and their greatest common divisors to argue about the uniqueness of solutions under certain conditions.
  • Concerns are raised about whether certain manipulations change the solution set, particularly in relation to singular operators.
  • Participants explore generalizing their findings to higher powers of operators, discussing potential methods for proving uniqueness in those cases.

Areas of Agreement / Disagreement

Participants express differing views on the complexity of the problem and the validity of various approaches. While some methods are discussed in detail, no consensus is reached on a single definitive proof or method for establishing uniqueness.

Contextual Notes

Participants acknowledge the potential complications arising from singular operators and the assumptions made during their proofs. There are also discussions about the limitations of their approaches when extending results to higher powers of operators.

Who May Find This Useful

This discussion may be useful for students and researchers interested in linear algebra, particularly those exploring eigenvalues, eigenvectors, and the properties of linear operators.

Eclair_de_XII
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TL;DR
Let ##A## be a linear transformation that maps some vector space to itself. Let ##\lambda,\mu## be two distinct scalars and define ##T_k:=A-k\cdot I##, where ##I## denotes the identity transformation. Show that the following hold:

\begin{eqnarray}
\ker(T_\lambda^2)\cap\ker(T_\mu^2)=0
\end{eqnarray}
Let ##x\in\ker(T_\lambda^2)\cap\ker(T_\mu^2)##. Then the following must hold:

\begin{eqnarray}
(A^2-2\lambda\cdot A+\lambda^2I)x=0\\
(A^2-2\mu\cdot A+\mu^2I)x=0
\end{eqnarray}

Subtracting the latter equation from the former gives us:

\begin{eqnarray}
0-0&=&0\\
&=&(-2\lambda\cdot Ax+\lambda^2x)-(-2\mu\cdot Ax+\mu^2x)\\
0&=&-2(\lambda-\mu)Ax+(\lambda-\mu)(\lambda+\mu)x
\end{eqnarray}

Bearing in mind that performing row operations on any system of linear equations does not change its solution set, we proceed by dividing both sides of the equality by ##\lambda-\mu##:

\begin{eqnarray}
0&=&-2Ax+(\lambda+\mu)x\\
&=&-2Ax+(\lambda+\lambda+(\mu-\lambda)x\\
&=&-2Ax+2\lambda\cdot x+(\mu-\lambda)x\\
&=&2(\lambda\cdot I-A)x+(\mu-\lambda)x\\
&=&2T_\lambda x+(\mu-\lambda)x
\end{eqnarray}

By definition, ##x\in\ker(T_\lambda+\frac{1}{2}(\lambda-\mu)I)## whenever ##I## is restricted to ##\ker(T_\lambda^2)\cap\ker(T_\mu^2)##. It can be shown through similar means that ##x\in\ker(T_\mu+\frac{1}{2}(-\lambda+\mu)I)##.

(I am still figuring out how to finish this proof, if it can be finished.)
 
Last edited:
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the problem is unnecessarily complicated. denote A-lambda.Id by B, and then denote A-mu.Id by B-c.Id, where c= mu-lambda ≠0. then try to show that if B^2 x=0 and also (B-c)^2 x = 0, where c≠0, then x = 0.
 
Last edited:
Sure. I show first that ##(B-c)^2## can be expanded like a polynomial.

\begin{eqnarray}
(B-cI)^2&=&[B^2-B(cI)-(cI)B+c^2I]\\
&=&[B^2-c(BI)-c(BI)+c^2I]\\
&=&[B^2-2c(BI)+c^2I]\\
\end{eqnarray}

Let ##x\in\ker(B^2)\cap\ker[(B-c)^2]##.

\begin{eqnarray}
0&=&B^2x\\
&=&(B-cI)^2x\\
&=&0-0\\
&=&(2cB-c^2I)x\\
&=&(2B-cI)x\\
&=&(B+B-cI)x\\
-Bx&=&(B-cI)x
\end{eqnarray}

By uniqueness of the inverse, either ##B-cI=-B## or ##x=0##. The former fails to hold if ##B\neq\frac{1}{2}cI##, in which case, ##x=0##.

If this solution were correct, I am wondering how I would show this is true (if it is true) for higher powers. I don't like thinking about the amount of algebra I'd need to do to prove it in the general case like how I did it for the case when the power is just two.
 
Last edited:
or, applying B again at step 19 implies cBx= 0, so Bx = 0, so from step 18, also c^2 x = 0, so x = 0.

a basic algebra fact is that in the integers and in the polynomial ring over a field, and in any euclidean domain, the greatest common divisor of two elements can be written as a linear combination of those elements. Hence if P,Q are relatively prime polynomials, so their gcd is 1, there are polynomials f, g, such that fP+gQ = 1. Then for any map A, plugging A into both sides of this equation, gives f(A)P(A) + g(A)Q(A) = Id. Now assuming P(A)x = Q(A)x = 0, gives that 0 = x.

In your original problem, P = (X-lambda)^2, and Q = (X-mu)^2.
 
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Thank you. That is very helpful.

mathwonk said:
applying B again at step 19 implies cBx= 0
Will that not change the solution set, though, if for example, ##B## is singular? Wait, never mind. I think that the new solution set obtained from applying ##B## to both sides would just be a superset of the original solution set. And since the new solution set is trivial, it must follow that the original solution set is also trivial.
 
Last edited:
using this idea on your original problem directly, note that if P = X-a, and Q = X-b, with a ≠b, then P-Q = b-a ≠0, so we can take f = 1/(b-a) and g = -1/(b-a), to get fP+gQ = 1.

Then to do the case of P^2 and Q^2, just cube both sides of this equation. Every term on the left will be divisible by either P^2 or Q^2, and the right side will still equal 1. So we get some equation of form FP^2 + GQ^2 = 1. the same trick works for all higher powers. I.e. to deal with P^n and Q^n, raise the equation to the power 2n-1, I guess.
 
i don't understand your concern in post #5, since if B is not singular, you are done immediately, so we may assume if we wish that B is singular, but that is irrelevant to the argument. I am just trying to prove that x = 0. from step 19 we know that 2Bx = cx, so applying B again gives 2B^2x = cBx, but B^2 x = 0, by hypothesis, so cBx = 0. but c≠0 so Bx = 0. now either step 18 or 19 gives that 0 = cx or 0 = c^2x, either way x = 0.
 

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