getting too close to each other (atoms cannot overlap):

$$\label{eq:maxent-stress}
    \min_x \sum_{vw \in S} \omega_{vw} (\lVert x_v - x_w \rVert - d_{vw})^2 \; - \alpha H(x),$$

where $H(x) = -\operatorname{sgn}(q) \sum_{vw \notin S} \lVert x_v - x_w \rVert ^{-q}, q > -2$, is the entropy term, $\omega_{vw}$ a weighting factor for edge $\{v,w\}$, $\alpha \geq 0$ a user-defined control parameter, and $\operatorname{sgn}(q)$ the signum function with the special case that $sgn(0) = 1$.

To minimize function (\[eq:maxent-stress\]), Gansner [*et al.*]{} [@gansner2013] derive a solution from successively solving Laplacian linear systems of the form $Lx=b$ for $x$. A noteworthy feature of this successive iteration towards a local minimum is that the solution of the current iteration depends on the solution of the previous iteration, since the current right-hand side is computed from the solution in the previous iteration. Note that the computation of distances between vertex pairs not in $S$ is not required for function (\[eq:maxent-stress\]). Instead, vertex pairs not in $S$ are related to each other via the entropy term, which enters the right-hand side, too. If the parameter $q$ is set to be smaller than zero, the entropy term of vertex $u$ acts as a sum of attractive forces 