If $M$ is an arbitrary real $n \times n$ matrix, then which of the following matrices will have non-negative eigenvalues?
Step 1: Recall property of symmetric matrices.
For any real matrix $M$, both $MM^T$ and $M^TM$ are symmetric matrices. Symmetric matrices always have real eigenvalues.
Step 2: Positive semi-definiteness.
For any vector $x \in \mathbb{R}^n$:
\[
x^T(MM^T)x = (M^Tx)^T(M^Tx) = \|M^Tx\|^2 \geq 0
\]
This shows that all eigenvalues of $MM^T$ are non-negative.
Similarly,
\[
x^T(M^TM)x = (Mx)^T(Mx) = \|Mx\|^2 \geq 0
\]
Hence all eigenvalues of $M^TM$ are also non-negative.
Step 3: Why not $M^2$ or $(M^T)^2$?
In general, $M^2$ and $(M^T)^2$ need not be symmetric and can have negative or even complex eigenvalues. So they do not guarantee non-negative eigenvalues.
\[
\boxed{\text{Therefore, the correct options are (B) and (C).}}
\]
Cholesky decomposition is carried out on the following square matrix [A]. \[ [A] = \begin{bmatrix} 8 & -5 \\ -5 & a_{22} \end{bmatrix} \] Let \( l_{ij} \) and \( a_{ij} \) be the (i,j)\textsuperscript{th elements of matrices [L] and [A], respectively. If the element \( l_{22} \) of the decomposed lower triangular matrix [L] is 1.968, what is the value (rounded off to the nearest integer) of the element \( a_{22} \)?}
| Point | Staff Readings Back side | Staff Readings Fore side | Remarks |
|---|---|---|---|
| P | -2.050 | - | 200.000 |
| Q | 1.050 | 0.95 | Change Point |
| R | - | -1.655 | - |