Linear Algebra - four "true or false" questions about matrices and linear systems

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I'm reviewing for my linear algebra course, and have four "true or false" questions that I'm struggling to prove. I've included my approach to the solutions in brackets below them:

1) If $A^2 = B^2$, then A = B or A = -B, where A and B are nxn matrices
(Not sure how to approach this one at all)

2) Every 3x3 skew symmetric matrix is singular
(Pretty sure I have this one correct: Because this is a skew symmetric matrix, $\det(A) = \det(A^T) = \det(-A) = (-1)^n\det(A)$, and when n is odd $\det(A) = -\det(A)$, so $2\det(A) = 0$ and therefore $\det(A) = 0$. As such, the answer is "False" because it is only singular when n is odd)

3) Any system of n linear equations in n variables has at most n solutions
(A system can have infinitely many solutions if the determinant is zero, right? I just don't know how to prove it)

4) For a square matrix A, A is invertible if and only if $AA^T$ is
(Not sure how to approach this one, either)

4

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1: Nope. Consider $\left(\begin{smallmatrix}0&1\\0&0\end{smallmatrix}\right)$ and $\left(\begin{smallmatrix}0&0\\0&0\end{smallmatrix}\right)$, or $\left(\begin{smallmatrix}1&0\\0&1\end{smallmatrix}\right)$ and $\left(\begin{smallmatrix}1&0\\0&-1\end{smallmatrix}\right)$.

2: By your reasoning it's true since we're only considering $n=3$.

3: You're right; this is false. It's enough to have a counter-example such as $$ x+y = 0\\ 2x + 2y =0 $$ 4: This is true; note $\det(AA^T)=\det(A) \det(A^T) = [\det(A)]^2$. Conclude $\det(A)=0 \iff \det(AA^T) = 0$

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Here is an incomplete answer.

For 4), you need to prove both:

(i) $A$ is invertible implies $AA^{T}$ is invertible

(ii) $AA^{T}$ is invertible implies $A$ is invertible.

To prove (i), suppose $A$ is invertible. Then $A^{-1}$ exists. Then $(A^{-1})^{T}$, the transpose of the inverse matrix, exists. Now, recall that for any matrices $A$ and $B$, $(AB)^{T} = B^{T}A^{T}$. Then multiplying $AA^{T}$ by $(A^{-1})^{T}$, we get $AA^{T}(A^{-1})^{T} = A(A^{-1}A)^{T} = A(I^{T}) = AI = A$, and so $AA^{T}(A^{-1})^{T} = A$. Thus, multiplying on the right of each side of the equation by $A^{-1}$ gives $AA^{T}(A^{-1})^{T}A^{-1} = AA^{-1} = I$. So, the inverse of $AA^{T}$ is $(A^{-1})^{T}A^{-1}$.

The proof for (ii) is not exactly like the proof above, but I think it can be worked out using only as much thought as the proof above. But it looks like some other users have given a much shorter and simpler proof for 4.

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For number 4, $$\det(AA^t) = \det(A)\det(A^t) = \det(A)^2.$$ Hence $\det(A) = 0 \iff \det(AA^t) = 0$.

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I think that it is not necessarily best to prove that invertibility of $A$ is equivalent to that of $A^T$ using the determinant. Indeed, as user46944 pointed out at https://math.stackexchange.com/a/930345/87579, one can explicitly construct an inverse for $A A^T$ from one for $A$. This might not be slick, but I think that it gives a more immediate insight into what's going on.

For the converse, note that, if $B \mathrel{:=} A A^T$ is invertible, then $A(A^T B^{-1}) = I$, so that $A$ has a right inverse. In general, this is all that one can say (consider the shift operator $A(x_0, x_1, x_2, \dotsc) = (x_1, x_2, \dotsc)$, for which $A A^T = I$). In the finite-dimensional case, an operator is (two-sided) invertible if and only if it has either one-sided inverse, so we are done.