Trace of Matrix Product as Scalar Product

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Homework Help Overview

The discussion revolves around the properties of a scalar product defined on the vector space of real symmetric n × n matrices, specifically focusing on the trace of the product of two matrices. Participants are tasked with demonstrating that this definition meets the criteria for a scalar product.

Discussion Character

  • Conceptual clarification, Mathematical reasoning, Assumption checking

Approaches and Questions Raised

  • Participants explore the implications of the trace operation and its properties, questioning the meaning of transposing a scalar and the conditions under which the inner product equals zero. There is also discussion about the necessity of proving certain properties related to symmetric matrices.

Discussion Status

The conversation is ongoing, with participants providing insights and raising questions about specific rules for the scalar product. Some guidance has been offered regarding the properties of the trace, but no consensus has been reached on how to fully demonstrate the required conditions.

Contextual Notes

Participants are navigating the constraints of the problem, particularly the requirement to show that the inner product is non-negative and equals zero only for the zero matrix, while also considering the implications of working within the space of symmetric matrices.

unscientific
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Homework Statement



Let V be the real vector space of all real symmetric n × n matrices and define the scalar product of two matrices A, B by (Tr (A) denotes the trace of A)

Show that this indeed fulfils the requirements on a scalar product.

tracescalarproduct1.png


Homework Equations



Conditions for a scalar product:

tracescalarproduct2.png


The Attempt at a Solution



I'm not sure how to show the last part. Which can be summarized as:

<A|B> = 0 if ATA = I and BTB = I

The first 3 parts of my attempt are shown below:

tracescalarproduct3.png
 
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For (2), you say ##\mathrm{Tr}(AB)^T##. I don't really know what you mean with this. What is the transpose of a number? And why should

\mathrm{Tr}(AB)^T = \mathrm{Tr}(B^T A^T)

For (3), you should still show that the inner product is ##\geq 0## and that it is ##=0## iff ##A=0##.
 
For rule 1, I think the OP means Tr ((AB)^T), not (Tr(AB))^T. The 1st line of the proof is unnecessary. The 2nd line looks good to me. However, you are using the fact that Tr(A) = Tr(A^T). This is easy to prove and you should add that proof in. For rule 2, you still need to prove that <A|A> = 0 implies A = 0. You will need to use the fact that the underlying space only includes symmetric matrices.
 
Last edited:
Vic Sandler said:
For rule 1, I think the OP means Tr ((AB)^T), not (Tr(AB))^T. The 1st line of the proof is unnecessary. The 2nd line looks good to me. However, you are using the fact that Tr(A) = Tr(A^T). This is easy to prove and you should add that proof in. For rule 2, you still need to prove that <A|A> = 0 implies A = 0. You will need to use the fact that the underlying space only includes symmetric matrices.

Yeah Tr(A) = Tr(A^T) because for any A_{ij} component where i=j, switching their positions don't change anything.

I'm more concerned about the point number 4. Which can be summarized as:

<A|B> = 0 if ATA = I and BTB = I
 
unscientific said:
I'm more concerned about the point number 4. Which can be summarized as:

<A|B> = 0 if ATA = I and BTB = I
Point number 4 says nothing of the kind. Consider A=B=I. Obviously ATA = I, as does BTB. Yet <A,B> is not zero.

Instead think of point #4 as being a definition of what it means for two quantities to be deemed as being "orthogonal" to one another.
 

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