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.
Past exam of the mathematics course of the University of Cambridge 2005 ii Paper 2 38A Solution Created 2026-09-24 Updated 2026-09-24
Past exam of the mathematics course of the University of Cambridge 2015 ii Paper 4 37E a i Solution Created 2026-09-24 Updated 2026-10-06
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. ThereforeOnce a Krylov subspace stops growing, it cannot resume growth.
Past exam of the mathematics course of the University of Cambridge 2020 ii Paper 2 40E a Solution Created 2026-09-24 Updated 2026-09-29
The th Krylov subspace isBecause has a complete eigenbasis, decomposewhere is the projection of onto the eigenspace belonging to the th distinct eigenvalue ; some may vanish. ThenEvery generator of therefore belongs to , and
Past exam of the mathematics course of the University of Cambridge 2023 ii Paper 3 40C b Solution Created 2026-09-24 Updated 2026-09-25
Since , the Heavy-ball method isMultiplication by and use of give the heavy-ball residual recurrenceWith the usual initialization , both initial residuals equal . Induction in the recurrence shows thatfor a polynomial of degree at most . ThereforeThis 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.