For a fixed , convergence for every initial error is equivalent to for all , where . ThusA single parameter works for every finite precisely when : the largest tends to two as , so every eventually fails, whereas has all eigenvalues strictly between and one for each finite grid.
For such the lowest-frequency eigenvalue satisfies, using ,An initial error proportional to retains exactly the factor . Hence the worst-case spectral radius cannot improve on a factor of the form , with independent of grid size, and reducing a slow-mode error by a fixed fraction takes order iterations. This is a worst-case rate assertion, not a lower bound for every individual initial error: a vector containing only faster modes, or the zero vector, need not exhibit the slow mode.
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