Concept

Incomplete factorisation — where it appears

A factorisation with entries deliberately discarded, which is not the exact factorisation of anything and is a preconditioner rather than a solver.

Named by 2 essays across 2 fields — each of them below, with the objects they name alongside it.

10⁻¹⁷10⁻¹⁴10⁻¹¹10⁻⁸10⁻⁵10⁻²-1-0.500.51relative backward error acceptedfraction of the work not doneQR deflation criterionincomplete Cholesky droplow-rank truncationthree fields, no shared arithmeticslope, deflation criterion0.039slope, drop tolerance0.051slope, rank truncation0.23widest apart, as a ratio5.7a tolerance is an offerand the three offers are one offer

The zero you are allowed to write

A deflation criterion sets a subdiagonal entry to zero because it is small. A drop tolerance discards an entry of a factor because it is small. A truncation discards a singular value because it is small. Three fields, three vocabularies, no shared arithmetic — and plotted as work saved against error accepted, one curve.

error · deliberate zero
10⁻¹⁷10⁻¹⁵10⁻¹³10⁻¹¹10⁻⁹10⁻⁷10⁻⁵10⁻³10⁻¹10⁻¹⁴10⁻¹²10⁻¹⁰10⁻⁸10⁻⁶10⁻⁴10⁻²1εrelative error in J(x)vforwardcentralcancellationtruncationagainst a derivative that is exactforward floor1.3·10⁻¹⁰central floor1.1·10⁻¹²truncation slope, forward1truncation slope, central2no ε reaches the roundoffand the analytic derivative is free of the choice

An operator with no entries

At the sizes where linear algebra is expensive the matrix does not exist. What exists is a subroutine that returns Av. Every Krylov method survives that unchanged; every algorithm that reads an entry disappears. And the derivative such a code computes is accurate to ten digits instead of sixteen, which turns out to cost nothing at all.

iterative · matrix free

Named alongside it

The objects these essays reach for when they reach for this one.

PreconditioningBackward errorCancellationDeflationDrop toleranceEckart–YoungFinite differenceJacobianKrylov subspaceLow-rank approximationMatrix-freeNewton iteration

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