*
* <h3>Implementation</h3>
*
- * In principle, the implementation of the error estimation is simple: let \f[
- * \eta_K^2 = \sum_{F\in\partial K} c_F \int_{\partial K_F} \left[a
- * \frac{\partial u_h}{\partial n}\right]^2 do \f] be the error estimator for
+ * In principle, the implementation of the error estimation is simple: let
+ * @f[
+ * \eta_K^2
+ * =
+ * \sum_{F\in\partial K}
+ * c_F \int_{\partial K_F} \left[a \frac{\partial u_h}{\partial n}\right]^2
+ * @f]
+ * be the error estimator for
* cell $K$. $[\cdot]$ denotes the jump of the argument at the face. In the
* paper of Ainsworth $ c_F=\frac {h_K}{24} $, but this factor is a bit
* esoteric, stemming from interpolation estimates and stability constants which
* may hold for the Poisson problem, but may not hold for more general
- * situations. Alternatively, we consider the case when $ c_F=\frac {h_F}{2p_F}
- * $, where $ h_F $ is face diagonal and $ p_F=max(p^+,p^-) $ is the maximum
+ * situations. Alternatively, we consider the case when $c_F=\frac {h_F}{2p_F}$,
+ * where $h_F$ is face diagonal and $p_F=max(p^+,p^-)$ is the maximum
* polynomial degree of adjacent elements; or $c_F=h_K$. The choice between
* these factors is done by means of the enumerator, provided as the last
* argument in all functions.