Let $M$ be a symmetric matrix and $a \in \mathbb{R}$, $a \geq 0$. How do I go about showing that the set $$C = \left\{ \lambda_{\min}(M) \geq a : M \, \text{symmetric} \right\}$$ is a convex set?
If we restrict ourselves to positive definite matrices, I had the following idea:
$$\lambda_{\min}(M) \geq a \iff \lambda_{\min}(M)^{-1} \leq a^{-1} \iff \lambda_{\max}(M^{-1}) \leq a^{-1}$$
Now, since $\lambda_{\max}$ is a norm of symmetric matrices, the above set is a ball, hence convex. But I can't prove it for general symmetric matrices, which aren't necessarily invertible. Any help is greatly appreciated.