Linear algebra: trace and dual space exercise

In summary: So if ##Tr(A^*A)=0##, then ##|a_{kp}|^2=0## for all ##k,p##, which means ##a_{kp}=0## for all ##k,p##. This means that every entry of ##A## is zero, and so ##A=0##. Therefore, ##A^*A=0##.In summary, the conversation discusses proving the statement ##A^*A=0## if and only if ##tr(A^*A)=0## for a matrix ##A##. The conversation also clarifies the meaning of ##A^*## as the matrix representing the hermitian conjugate of a linear transformation. The proof is shown for a
  • #1
mahler1
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Homework Statement .

Let ##A \in \mathbb C^{m\times n}##. Prove that tr##(A^*A)=0## if and only if ##A^*A=0## (here ##0## obviously means the zero matrix).


The attempt at a solution.

By definition of the trace of a matrix, the implication ← is obvious. I am having problems proving the other implication: first of all, I have doubts about the meaning of ##A^*##, if ##f:\mathbb C^n \to \mathbb C^m## is a linear transformation and ##A## is the associated matrix to ##f##, then ##f^t:{(\mathbb C^m)}^* \to {(\mathbb C^n)}^*## defined as ##f^t(\phi)=\phi \circ f## for all ##\phi \in {(\mathbb C^m)}^*##, so, I suppose ##A^*## just means the matrix which represents ##f^t##, am I right?

I have no idea how to prove ##tr(A^*A)=0 \implies A^*A=0##. I would appreciate any suggestions.
 
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  • #2
Try it first with a ##2\times 2## matrix. What are the diagonal elements of ##A^{*}A## if ##A=\left(\begin{smallmatrix}a&b\\c&d\end{smallmatrix}\right)##? Why does ##Tr(A^{*}A)=0## imply that ##a,b,c## and ##d## are all zero? (I'm supposing that the ##"*"## means hermitian conjugate). Then try to extend the solution to more general matrices.
 
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  • #3
hilbert2 said:
Try it first with a ##2\times 2## matrix. What are the diagonal elements of ##A^{*}A## if ##A=\left(\begin{smallmatrix}a&b\\c&d\end{smallmatrix}\right)##? Why does ##Tr(A^{*}A)=0## imply that ##a,b,c## and ##d## are all zero? (I'm supposing that the ##"*"## means hermitian conjugate). Then try to extend the solution to more general matrices.

Thanks for clearing up what it means ##A^*##. I want to check if this is correct:

By definition, the entry of the product matrix ##(A^*A)_{ij}=\sum_{k=1}^m (a^*)_{ik}a_{kj}##, but ##(a^*)_{ik}=\overline a_{ki}##, so ##\sum_{k=1}^m (a^*)_{ik}a_{kj}= \sum_{k=1}^m \overline a_{ki} a_{kj}##.

Now, ##tr(A^*A)=\sum_{p=1}^n (A^*A)_{pp}=\sum_{p=1}^n \sum_{k=1}^m (a^*)_{pk}a_{kp}=\sum_{p=1}^n \sum_{k=1}^m \overline a_{kp} a_{kp}=\sum_{p=1}^n \sum_{k=1}^m |a_{kp}|^2##.

Since ##tr(A^*A)=0 \implies \sum_{p=1}^n \sum_{k=1}^m |a_{kp}|^2=0 \implies a_{kp}=0 \space \forall 1\leq k \leq m, 1\leq p \leq n##. From here it follows ##A=0 \implies A^*A=0##.
 
  • #4
That looks correct. The idea is simply that if a sum of real non-negative numbers is zero, then every term in the sum must be zero.
 
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Related to Linear algebra: trace and dual space exercise

1. What is the trace of a matrix?

The trace of a matrix is the sum of the elements on the main diagonal of the matrix. It is also equal to the sum of the eigenvalues of the matrix.

2. What is the significance of the trace in linear algebra?

The trace is significant in linear algebra as it represents the sum of the eigenvalues, which can provide important information about the properties of the matrix. For example, the trace can be used to determine the determinant and the rank of a matrix. It is also useful in various applications such as signal processing and control theory.

3. How is the trace of a matrix calculated?

The trace of a matrix can be calculated by adding all the elements on the main diagonal of the matrix. For example, if we have a 3x3 matrix A, the trace would be equal to A11 + A22 + A33.

4. What is a dual space in linear algebra?

The dual space is the set of all linear functionals on a vector space. It is the space of all linear transformations from the original vector space to its underlying field. The dual space is often used in functional analysis and is crucial in understanding concepts such as duality and orthogonality.

5. How is the dual space related to the trace of a matrix?

The dual space is related to the trace of a matrix through the concept of the dual basis. The dual basis consists of the set of linear functionals that map each vector in the original basis to its corresponding element in the dual space. The trace of a matrix can be calculated using the dual basis by taking the sum of the products of the matrix elements with the corresponding dual basis elements.

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