I found out that there exist positive definite matrices that are non-symmetric, and I know that symmetric positive definite matrices have positive eigenvalues.

Does this hold for non-symmetric matrices as well?

**Answer**

Let $A \in M_{n}(\mathbb{R})$ be any non-symmetric $n\times n$ matrix but “positive definite” in the sense that:

$$\forall x \in \mathbb{R}^n, x \ne 0 \implies x^T A x > 0$$

The eigenvalues of $A$ need not be positive. For an example, the matrix in David’s comment:

$$\begin{pmatrix}1&1\\-1&1\end{pmatrix}$$

has eigenvalue $1 \pm i$. However, the real part of any eigenvalue $\lambda$ of $A$ is always positive.

Let $\lambda = \mu + i\nu\in\mathbb C $ where $\mu, \nu \in \mathbb{R}$ be an eigenvalue of $A$. Let $z \in \mathbb{C}^n$ be a right eigenvector associated with $\lambda$. Decompose $z$ as $x + iy$ where $x, y \in \mathbb{R}^n$.

$$(A – \lambda) z = 0 \implies \left((A – \mu) – i\nu\right)(x + iy) = 0

\implies \begin{cases}(A-\mu) x + \nu y = 0\\(A – \mu) y – \nu x = 0\end{cases}$$

This implies

$$x^T(A-\mu)x + y^T(A-\mu)y = \nu (y^T x – x^T y) = 0$$

and hence

$$\mu = \frac{x^TA x + y^TAy}{x^Tx + y^Ty} > 0$$

In particular, this means any real eigenvalue $\lambda$ of $A$ is positive.

**Attribution***Source : Link , Question Author : Community , Answer Author : achille hui*