/**
* Standardized data struct to pipe additional data to the solver.
- * Here, it doesn't store anything but just exists for consistency
+ * Here, it does not store anything but just exists for consistency
* with the other solver classes.
*/
struct AdditionalData
* which is based on a different formula to compute $\beta_k$ in the process
* of constructing a new search direction that is A-orthogonal against the
* previous one. Rather than using the Fletcher--Reeves update formula with
- * $\beta_k = \frac{\mathbf{r}^T_{k+1} \mathbf{z}^T_{k+1}}{\mathbf{r}^T_{k}
- * \mathbf{z}^T_{k}}$ for computing the new search direction (here
+ * $\beta_k = \frac{\mathbf{r}^T_{k+1} \mathbf{z}_{k+1}}{\mathbf{r}^T_{k}
+ * \mathbf{z}_{k}}$ for computing the new search direction (here
* $\mathbf{r}_{k+1}$ is the residual in step $k+1$ and $\mathbf{z}_{k+1} =
* P^{-1} \mathbf{r}_{k+1}$) as in the classical conjugate gradient algorithm,
* this class selects the Polak-Ribiere formula $\beta_k =
- * \frac{\mathbf{r}^T_{k+1} \left(\mathbf{z}^T_{k+1} -
- * \mathbf{z}^T_{k}\right)}{\mathbf{r}^T_{k} \mathbf{z}^T_{k}}$. The
- * additional term $\mathbf{r}^T_{k+1} \mathbf{z}^T_{k}$ is zero for linear
+ * \frac{\mathbf{r}^T_{k+1} \left(\mathbf{z}_{k+1} -
+ * \mathbf{z}_{k}\right)}{\mathbf{r}^T_{k} \mathbf{z}_{k}}$. The
+ * additional term $\mathbf{r}^T_{k+1} \mathbf{z}_{k}$ is zero for linear
* symmetric-positive definite preconditioners due to the construction of the
* search directions, so the behavior of SolverFlexibleCG is equivalent for
* those kinds of situations and merely increases costs by requiring an
/**
* Standardized data struct to pipe additional data to the solver.
- * Here, it doesn't store anything but just exists for consistency
+ * Here, it does not store anything but just exists for consistency
* with the other solver classes.
*/
struct AdditionalData