Linear Algebra: Positive Operators

In summary: So in the complex case, I think it might be something like this:<x,Ax>=a*b+<y,Bx>The sum of two self-adjoint vectors is always self-adjoint, so this equation is always true. To see that this equation is equivalent to <x,Ax>=a*b, you can use the distributive law:<Tx,x>=<T(x+y),x+y>+<Tx,y>So, <Tx,x> always equals <Tx,y> because <Tx,x> and <T(x+y),x+y> are the same vector.
  • #1
LPB
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Homework Statement



Let A and B be nxn positive self-adjoint matrices such that for all x [tex]\in[/tex] Cn, x*Ax = x*Bx. Prove that A = B. Equivalently, prove that if A, B are positive operators on H such that <Ax,x> = <Bx,x> [tex]\forall[/tex] x [tex]\in[/tex] H, then A = B. Hint: See Lemma 2.12.


Homework Equations



Lemma 2.12:
Let H be a Hilbert space over R or C and let T:H [tex]\rightarrow[/tex] H be a self-adjoint linear operator. Then we have:
(i) <Tx,x> is real for all x [tex]\in[/tex] H.
(ii) If H is over R, then for all x,y [tex]\in[/tex] H we have
<Tx,y> = 1/4 [<T(x+y),x+y> - <T(x-y),x-y>].
(iii) If H is over C, then for all x,y [tex]\in[/tex] H we have
<Tx,y> = 1/4 [<T(x+y),x+y> - <T(x-y),x-y>] + i/4 [<T(x+iy),x+iy> - <T(x-iy),x-iy>] .


The Attempt at a Solution



If we already know that <Ax,x> = <Bx,x>, doesn't it automatically follow that A = B? I'm not sure what has to be proven. I went through part (iii) of Lemma 2.12 and plugged in <Ax,x> for <Tx,y>, and everything canceled out so that <Ax,x> = <Ax,x>, but I don't think that this helped me at all. I'm just not sure what I'm being asked to prove...
 
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  • #2
No, it doesn't follow that <x,Ax>=<x,Bx> implies that A=B. Take the real case. If x=[a,b], A=[[0,1],[0,0]] and B=[[0,0],[1,0]] (I hope the matrix notation is clear), then <x,Ax>=a*b and <x,Bx>=a*b. They are equal. But A is not equal to B. But then the operators A and B are not self adjoint either. Can you come up with an counterexample for the complex case? You can learn a lot by trying to find a counterexample to a theorem if you relax one of the premises.
 
  • #3
I see what you're saying. Could a simple counterexample for the complex case be A=[[0,i],[0,0]] and B=[[0,0],[i,0]] (keeping x=[a,b])?

If the operator matrices are self-adjoint, it seems A would always equal B ... for instance, A=B=[[0,1],[1,0]] or A=B=[[0,i],[-i,0]]. Is this right? OK, so I see that it makes sense to prove what the question is asking. Only ... how would I start the proof?

And from the question, it seems that A and B must also be positive ... I know that if an operator T is positive, then not only is it self-adjoint, but also <Tx,x> >= 0 ... I don't see how this is essential. Can you give an example of a self-adjoint operator that is not positive? Maybe I'll be able to see the connection then.

Thank you!
 
  • #4
An example of a matrix that's self-adjoint but not positive is [[-1,0],[0,-1]]. I.e. -I. That's easy, isn't it? I still don't really see what 'positive' has to do with this. Your lemma only requires the matrix to be self-adjoint. And it looks to me like the lemma is all you need. It let's you express <xT,y> as a sum of similar expressions where the two vectors are equal.
 

Related to Linear Algebra: Positive Operators

1. What is a positive operator in linear algebra?

A positive operator in linear algebra is a linear transformation that preserves the direction of vectors and increases their lengths. This means that when a positive operator is applied to a vector, the resulting vector will still be in the same direction but will have a larger magnitude.

2. How is positivity defined for operators in linear algebra?

Positivity for operators in linear algebra is defined using the concept of positive definiteness. An operator is considered positive if it satisfies the condition that the inner product of any non-zero vector with its image under the operator is always positive.

3. What are some examples of positive operators?

Some common examples of positive operators include the identity operator, which leaves all vectors unchanged, and the scaling operator, which multiplies all vectors by a positive constant. The derivative operator and the integral operator are also positive operators.

4. How are positive operators used in applications?

Positive operators are used in many applications, including optimization problems, signal processing, and quantum mechanics. In optimization, positive operators can be used to find the maximum or minimum value of a function. In signal processing, positive operators can be used to filter or enhance signals. In quantum mechanics, positive operators are used to represent physical observables such as energy and momentum.

5. How can one determine if an operator is positive in linear algebra?

To determine if an operator is positive, one can use the definition of positive definiteness mentioned earlier. This involves computing the inner product of a non-zero vector with its image under the operator and checking if the result is always positive. If it is, then the operator is considered positive.

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