Solving a Puzzling Problem: No A Exists for Symmetric Matrix B

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Give an example of a 2X2 symmetric matrix B that cannot be written as B = ATA. Give an explanation as to why no such A exists for the matrix B you have given.


I know that the product ATA is a symmetric matrix, but how could there be no such A that exists for some matrix B?

I'm really stuck on this problem, and I would appreciate it if anyone could help. Thank you so much in advance.
 
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What is the nature of the eigenvalues of ATA?
 
If you write

A=\begin{pmatrix}a&b\\ c&d\end{pmatrix}

and calculate ATA, it's immediately obvious that the result is not the most general form of a symmetric 2×2 matrix. No more calculations are necessary. Just stare at the result until you get it.
 
1 2
2 3

I did out the product of ATA and came up with this matrix B that couldn't be written as such. Am I correct?
 
You are correct about the above matrix. Try to figure out why (hint: determinants).
What do you think about the following matrix:
<br /> A=\begin{pmatrix}1&amp;10\\ 10&amp;-1\end{pmatrix}<br />
 
Determinants are quite the right answer, either. Both the identity matrix and its additive inverse,

\bmatrix -1 &amp; 0 \\ 0 &amp; -1\endbmatrix

have the same determinant. The identity matrix can obviously be written in the form ATA. Its additive inverse cannot.
 
The OP's task was just to find an example of a symmetric matrix that can't be expressed as ATA, and noting that det ATA≥0 is certainly a good start. It explains why

1 2
2 3

is the kind of matrix we're looking for. My idea was to note that the elements on the diagonal of ATA are ≥0. That explains both

1 10
10 -1

and

-1 0
0 -1

Not sure if there are symmetric matrices with both the determinant and the diagonal elements ≥0 that can't be written as ATA. I'm too tired to think about that right now.
 
You can get away with looking at the determinant and the diagonal elements for a 2x2. That trick won't work for anything larger than 2x2. What always works is to look at the eigenvalues, like I said in post #2. Given a real nxm matrix A, the eigenvalues of the matrix ATA are always non-negative. If any eigenvalue of some matrix B is negative then it is impossible to write B in the form ATA.
 
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