Let $A\in\mathbb{R}^{n\times n}$ be a symmetric matrix such that the quadratic function $$f(x)=x^\top Ax-2(x_1+\ldots+x_n)$$ is uniformly bounded from below by a constant. Does it imply that $A$ is positive definite?
By using the eigenvalue decompostion of $A$ and making orthogonal transformations for $x$, we can easily show that $A$ must be positive semidefinite. Is it necessary that $A$ is positive definite in this case?
No, $A$ does not need to be positive definite. Consider the matrix $$A=\begin{bmatrix} 1 & 1 \\ 1 & 1\end{bmatrix}$$
This matrix is symmetric with $$f(x,y)=x(x+y)+y(x+y)-2(x+y)=(x+y-2)(x+y)$$
This functions is bounded below. Letting $c=x+y$, then this reads $f(x,y)=c^2-2c$, which attains a minimum of $-1$ when $c=1$, so $f$ is bounded below. However, $A$ is not positive definite, since one of its eigenvalues is $0$. In particular, for $x=\begin{bmatrix} 1 \\ -1\end{bmatrix}$ satisfies $x^TAx=0$.