How properties of a 2D hermitian matrix restrict the 2D matrix's elements

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I have read different definitions, or properties, of a Hermitian matrix, and still am not sure if I have a sufficient number of properties to define a Hermitian matrix.

Suppose the following is true about Hermitian Matrices.

$M\vec{a} = \lambda\vec{a}$

where all scalars $\lambda$s (eigenvalues) are real.

Lets just use a 2D matrix.

If $M = \begin{bmatrix} a & b \\ c & d \end{bmatrix}$, then $det\begin{bmatrix} a-\lambda & b \\ c & d-\lambda \end{bmatrix}=0$.

This means that (by quadratic solution to characteristic equation) $$\lambda = \frac{(a+d)\pm\sqrt{(a+d)^2-4*(a^2-cb)}}{2}$$

For lambda to be real (in both + and - cases), there are certain restrictions that must be obeyed. However they are not as restrictive as the definition of a Hermitian matrix.

One restriction is that $$Im(a+d)=0$$ (imaginary components cancel). Another is $$(a+d)^2-4*(a^2-cb) >= 0 $$ (>= or just >?) and simultaneously $$Im((a+d)^2-4*(a^2-cb))=0$$

Even though Hermitian matrices do not allow imaginary diagonal elements, I'm pretty sure I could think of a matrix that would satisfy these conditions with imaginary $a$ and $d$ elements.

I'm guessing I'm not understanding the properties of a Hermitian matrix. What am I missing?

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By definition, a complex square matrix $A$ is hermitian if and only if $A^H = A$. Where $A^H = \bar A^T$ denotes the conjugate transposed of $A$.

It is the result of the spectral theorem, that all eigenvalues of a hermitian matrix are real and there exists eigenvector basis.

The matrix $$ \begin{bmatrix} 0 & 1 \\ 0 & 0 \end{bmatrix} $$ has clearly only real eigenvalues, but is not hermitian.

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After looking in my Griffiths quantum mechanics book, I think I now realize that the Hermitian Operator defines what a Hermitian Matrix is. Anyways, I wonder if the following properties is enough to define what a Hermitian Matrix is.

1) All eigenvalues are real

2) The eigenvectors are mutually orthogonal (Inner product between any of them yields $0$).

3) Eigenvectors span all of the space