Prove Positive Operators Sum is Positive on V

In summary, the proof shows that the sum of any two positive operators on vector space V is also positive. This is because a positive operator is self-adjoint and has non-negative eigenvalues, which hold true for both T and X in this case. So, by adding the two operators together, we can see that the resulting operator is also self-adjoint and has non-negative eigenvalues, making it positive.
  • #1
evilpostingmong
339
0

Homework Statement


Prove that the sum of any two positive operators on V is positive.

Homework Equations


The Attempt at a Solution


This problem seems pretty simple. But I could be wrong. Should I name two
positive operators T and X such that T=SS* and X=AA*? I have a bad
history of seeing a proof and thinking "wow, this'll be cake" which leads to lazy thinking.
Should I just choose two vectors v1 and v2 and establish two inner products, <SS*v1, v2>+<AA*v1, v2>?
I know that A* is real if X is positive, same goes for S. So <AA*v1, v2>=<Av1, Av2>=<A^2v1, v2>. If I'm
right here, its easy street.
 
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  • #2
And what is V? Is it vector space ?
 
  • #3
yes its a vector space. So V is invariant under T (this chapter deals with self-adjoint operators, so I think that this is what is to be assumed).
I have a proof in mind but won't post it if what I said (in the first post ) is wrong.
 
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  • #4
Ok let V be invariant under T. Now let v be an eigenvector under T.
Let V be invariant under X. let v be an eigenvector under X.
Now since T and X are positive, we assume that <Tv, v> >=0 and <Xv, v> >=0 and that
T and X are invariant. Now if <Tv, v> >=0 and <Xv, v>=0, then <(T+X)v, v>=<Tv, v> which
is >=0. If T is a 0 map, <(T+X)v, v>=<Xv, v> which is also >=0. If T and X are not 0 maps, and T and X are both positive, then <(T+X)v, v> is > both <Tv, v> and <Xv, v> since both <Tv, v> and <Xv, v> are >0 if neither are 0 maps. Now if both T and X are 0 maps, then <(T+X)v, v>=0, also >=0.

Now we must show that T+X is self adjoint Since we assume that T and X are positive, T=T* and X=X*. So (T+X)v=Tv+Xv and (T*+X*)v=T*v+X*v. Since Tv=T*v and Xv=X*v, Tv+Xv= T*v+X*v. Therefore T+X is self adjoint.
 
  • #5
Ignore me, just here to mark the post and will do it later.
 
  • #6
I assume a positive operator is a positive-definite matrix(correct me if I am wrong), do you know what the definition is?
 
  • #7
kof9595995 said:
I assume a positive operator is a positive-definite matrix(correct me if I am wrong), do you know what the definition is?

You are correct. My book says that a positive definite operator is a positive operator
but didn't use a matrix when describing one. But I assume you're correct in that
by the def of a positive operator: 1. Must be self adjoint 2. <Tv, v> >=0
I would imagine the same to be true for the matrix: its conjugate transpose must equal
the original matrix when dealing with a complex space and its transpose must equal
its original form when dealing with a real space. So itself adjoint. And <Tv, v> >=0.
Which implies all eigenvalues of T must be >=0. Oh and when I said original matrix
I meant the matrix you want to "transpose".
 
  • #8
In the 4th post you take v as an eigenvector, I really don't see why,since the definition requires <Tv, v> >0(I think the >=0 case is semi positive definite) for any v, another fallacy in your proof is X and S may not share the same eigenvector. And positive-definite matrix can not be 0 matrix, you don't need to discuss it.
Just let v be any vector, the proof will be OK.
 
  • #9
kof9595995 said:
In the 4th post you take v as an eigenvector, I really don't see why,since the definition requires <Tv, v> >0(I think the >=0 case is semi positive definite) for any v, another fallacy in your proof is X and S may not share the same eigenvector. And positive-definite matrix can not be 0 matrix, you don't need to discuss it.
Just let v be any vector, the proof will be OK.

Whoops, my bad. As long as the scalar <Tv, v> (say Tv=a1v1+...+anvn where Tv=/=cv where c is some scalar) is >=0, T is positive.
So if I were to go back and revise, just replace "eigenvector" with any vector and the proof
is correct, right? And yes, T and S may not share the same eigenvector.
For example, if T were a 3x3 matrix where every entry on this matrix differ, and
S were a 3x3 identity matrix, its clear that an eigenvector of S is (1 1 0) but
(1 1 0) may not be an eigenvector of T since T(1 1 0) would amount to
(a+b, d+e, 0) where a+b=/=d+e so (a+b, d+e, 0) is not a scalar multiple of (1 1 0).
But we are only focusing on the scalars <Tv, v> and <Sv, v>. So v is arbitrary.
btw this assumes that the basis for V is {(1 1 0), (0 0 1), (0 1 1)}
 
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1. What is a positive operator?

A positive operator on a vector space V is a linear transformation that maps any vector in V to a non-negative scalar multiple of that vector. This means that the operator preserves the direction of the vector and only scales it by a positive factor.

2. What does it mean for the sum of positive operators to be positive on V?

If the sum of two positive operators on a vector space V results in another positive operator, it means that the combined transformation still preserves the positivity of vectors in V. In other words, the sum of the two operators will only scale vectors by positive factors and not change their direction.

3. How can we prove that the sum of positive operators is positive on V?

To prove that the sum of positive operators is positive on V, we can use the definition of positive operators and show that the sum of any two positive operators maps any vector in V to a non-negative scalar multiple of that vector. This can be done by showing that the sum of the two operators is also a linear transformation and satisfies the properties of a positive operator.

4. Are there any conditions or restrictions for the sum of positive operators to be positive on V?

Yes, there are conditions for the sum of positive operators to be positive on V. One important condition is that the two operators must commute, meaning that their order of application does not affect the final result. If the operators do not commute, then the sum may not result in a positive operator on V.

5. How is the concept of positive operators and their sums relevant in real-world applications?

The concept of positive operators and their sums is relevant in many areas of mathematics, physics, and engineering. In quantum mechanics, positive operators represent observables and their sums represent the total energy of a system. In optimization problems, positive operators are used to define positive definite matrices, which are essential for finding the minimum or maximum of a function. In control theory, positive operators are used to represent stable systems. Overall, the concept of positive operators and their sums is a fundamental concept in many fields of science and engineering.

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