The idea of using polynomial methods to improve simple smoother iterations within a multigrid method for a symmetric positive definite (SPD) system is revisited. When the single-step smoother itself corresponds to an SPD operator, there is in particular a very simple iteration, a close cousin of the Chebyshev semi-iterative method, based on the Chebyshev polynomials of the fourth instead of first kind, that optimizes a two-level bound going back to Hackbusch. A full V-cycle bound for general polynomial smoothers is derived using the V-cycle theory of McCormick. The fourth-kind Chebyshev iteration is quasi-optimal for the V-cycle bound. The optimal polynomials for the V-cycle bound can be found numerically, achieving an about 18% lower error contraction factor bound than the fourth-kind Chebyshev iteration, asymptotically as the number of smoothing steps goes to infinity. Implementation of the optimized iteration is discussed, and the performance of the polynomial smoothers are illustrated with a simple numerical example.
翻译:使用多格方法来改进对称正确定(SPD)系统的多格方法中简单更平滑的迭代。 当单步平滑器本身与 SPD 操作员对应时, 特别有一个非常简单的迭代, 即Chebyshev 半迭代方法的近亲表妹, 其基础是Chebyshev 第四种而不是第一种的Chebyshev 半迭代方法, 该方法优化了返回 Hackbusch 的双层捆绑。 使用麦考密克的V周期理论为普通多元平滑器制成一个完整的V周期。 第四种切比舍夫的迭代是V- 周期捆绑的准最佳迭代。 V- 循环捆绑定的最佳多元代方法可以用数字方式找到, 与第四种Chebyshev 的缩缩缩因相约束的大约18%的低误差缩因数, 与平滑步骤的数量相同, 与平滑步骤数量相同, 执行最优化的迭代试例是简单的数字。