Heavy-ball residual recurrence Created 2026-09-24 Updated 2026-09-24
For and ,
Thus is a polynomial in applied to the initial residual and lies in the corresponding Krylov subspace.
Linear-system residual 2026-10-06
The residual of an approximate solution of is . It is the unbalanced right-hand side, while the solution error is . The Conjugate gradient method makes residuals orthogonal to successive Krylov subspaces.
The Krylov subspace is . Let be the first index for which depends linearly on . Such an index exists with , since and any vectors are dependent. The first vectors are independent. The relation for shows that their span is invariant under : multiplying any generator by stays in that span. Repeated multiplication makes every higher power stay there too. Therefore
Once a Krylov subspace stops growing, it cannot resume growth.
The th Krylov subspace is
Because has a complete eigenbasis, decompose
where is the projection of onto the eigenspace belonging to the th distinct eigenvalue ; some may vanish. Then
Every generator of therefore belongs to , and
Since , the Heavy-ball method is
Multiplication by and use of give the heavy-ball residual recurrence
With the usual initialization , both initial residuals equal . Induction in the recurrence shows that
for a polynomial of degree at most . Therefore
This is under the zero-indexed Krylov subspace convention in the question; under the convention whose order- space ends at , it is .
Vandermonde matrix Created 2026-10-06 Updated 2026-10-07
A Vandermonde matrix has entries . Distinct nodes give determinant , explaining independence of polynomial evaluations and distinct-eigenvalue Krylov subspaces.