A comment by Rob Pratt (of SAS) on OR Stack Exchange pointed out two things that are glaringly obvious in hindsight but that somehow I keep forgetting. Both pertain to an expression of the form $x'Qx + c'x,$ either in an objective function or in a second order cone constraint, where $x$ is a vector of variables and $Q$ and $c$ are parameters.

The first observation does not depend on the nature of the $x$ variables. We can without loss of generality assume that $Q$ is symmetric. If it is not, replace $Q$ with the symmetric matrix $\hat{Q} = \frac{1}{2}\left(Q + Q'\right),$ which is symmetric. A wee bit of algebra should convince you that $x'\hat{Q}x = x'Qx.$

The second observation is specific to the case where the $x$ variables are binary (which was the case in the ORSE question which drew the comment from Rob). When minimizing an objective function of the form $x'Qx + c'x$ or when using it in a second order cone constraint of the form $x'Qx + c'x \le 0,$ you want the $Q$ matrix to be positive definite. When $x$ is binary, this can be imposed easily.

Suppose that $x$ is binary and $Q$ is symmetric but *not* positive definite. The following argument uses the euclidean 2-norm. Let $$\Lambda = \max_{\parallel y \parallel = 1} -y'Qy,$$ so that $y'Qy \ge -\Lambda$ for any unit vector $y.$ Under the assumption that $Q$ is not positive definite, $\Lambda \ge 0.$ Choose some $\lambda > \Lambda$ and set $\hat{Q} = Q + \lambda I,$ where $I$ is the identity matrix of appropriate dimension. For any nonzero vector $y,$

So $\hat{Q}$ is positive definite. Of course, $x'\hat{Q}x \neq x'Qx,$ but this is where the assumption that $x$ is binary sneaks in. For $x_i$ binary we have $x_i^2 = x_i.$ So

$$ \begin{align*} x'\hat{Q}x & =x'Qx+\lambda x'Ix\\ & =x'Qx+\lambda\sum_{i}x_{i}^{2}\\ & =x'Qx+\lambda e'x \end{align*} $$where $e=(1,\dots,1).$ That means the original expression $x'Qx + c'x$ is equal to $x'\hat{Q}x+(c-\lambda e)'x,$ giving us an equivalent expression with a positive definite quadratic term.

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