 Solution

Use the fine matrix $A_h$ and right-hand side from part (b), with diagonal $D_h$. Starting from an iterate $v$, take $\nu$ weighted Jacobi smoothing stepsForm the residual $r_h=b_h-A_{h}v$. For coarse interior indices $j=1,\dots ,m/2-1$, use full-weighting restrictionThe prolongation operator matrix $P$ is linear interpolation of a coarse correction: $(Pe{)}_{2j}=e_j$ and $(Pe{)}_{2j+1}=(e_j+e_{j+1})/2$, with zero endpoint corrections. Thus $R=P^T/2$. Choose the Galerkin coarse-grid operator $A_c=R{A}_{h}P$, solve $A_c{e}_c=R{r}_h$ exactly, and correct $v\leftarrow v+P{e}_c$. The entries of $A_h$, $R$ and $P$ above specify every matrix in the cycle. A rediscretized coarse operator is another standard choice if used consistently.

For a nonsingular coarse operator, the fine-grid iteration matrix of this pre-smoothed two-grid cycle isThe purpose of under-relaxation is to damp fine-grid oscillations, leaving smoother error for coarse-grid correction. For the diffusion-dominated one-dimensional operator, $\omega =2/3$ is the usual effective choice; the high-frequency symbol $1-\omega (1-\cos \xi )$ then has modulus at most $1/3$ for $\pi /2\le |\xi |\le \pi$. Coefficients and convection can change the best parameter, so this is a motivated choice rather than a universal optimum. Under the diagonal-dominance condition, the unweighted Jacobi matrix already has norm less than one in the maximum norm, and its convex combination with the identity remains convergent for $0<\omega <1$.