Generator

refinement-trail

One function in the inverse library, called 3 times across 3 essays. Below: what it draws at its defaults, what it draws at every value an essay asks for, the 13 claims it put to the test while drawing them, and where it stands against the rule this site is named for.

At its defaults it draws iterative refinement of the inverse-and-multiply solve at κ = 10^14. The backward error starts at 4.5·10⁻⁵ and falls by about κu a step — 8.1·10⁻⁹, 5.3·10⁻¹², 3.3·10⁻¹⁵, 3.1·10⁻¹⁷, 2.8·10⁻¹⁷ — reaching the LU route's 2.2·10⁻¹⁷ after 5 corrections, each costing 2n² flops against the 2n³ the inversion cost. The forward error, drawn above, does not improve: 0.015 to 7.1·10⁻⁴, against the LU route's 2.8·10⁻⁴. What refinement at working precision buys is stability, and the accuracy floor belongs to the problem.

refinement-trail is one function in lib/figures/inverse.js — the inverse — an object almost nobody needs, and the backward error of forming it. Everything below came out of it during this build, at arguments taken from the essays rather than invented for this page. A figure here is the figure a reader meets in an essay, and if the generator changes, this page changes with it.

At its defaults

Drawn even though every essay passes arguments — which on this site is every essay, at 100% of placements since the standard pass. A default nothing exercises is a trap for the next essay to call this with none, and this is the page where a default that has drifted from the figures around it becomes visible.

Iterative refinement of the inverse-and-multiply solve at κ = 10^14The backward error starts at 4.5·10⁻⁵ and falls by about κu a step — 8.1·10⁻⁹, 5.3·10⁻¹², 3.3·10⁻¹⁵, 3.1·10⁻¹⁷, 2.8·10⁻¹⁷ — reaching the LU route's 2.2·10⁻¹⁷ after 5 corrections, each costing 2n² flops against the 2n³ the inversion cost. The forward error, drawn above, does not improve: 0.015 to 7.1·10⁻⁴, against the LU route's 2.8·10⁻⁴. What refinement at working precision buys is stability, and the accuracy floor belongs to the problem.01234510⁻¹⁸10⁻¹⁵10⁻¹²10⁻⁹10⁻⁶10⁻³1correction steprelative errorLU route: η = 2.2·10⁻¹⁷LU route: forward 2.8·10⁻⁴forward errorbackward errorwhat a correction buysη before refinement4.5·10⁻⁵η after four steps2.8·10⁻¹⁷forward, unchanged7.1·10⁻⁴cost of a step, flops1800the residual is repairableand the accuracy floor is the problem's

The backward error starts at 4.5·10⁻⁵ and falls by about κu a step — 8.1·10⁻⁹, 5.3·10⁻¹², 3.3·10⁻¹⁵, 3.1·10⁻¹⁷, 2.8·10⁻¹⁷ — reaching the LU route's 2.2·10⁻¹⁷ after 5 corrections, each costing 2n² flops against the 2n³ the inversion cost. The forward error, drawn above, does not improve: 0.015 to 7.1·10⁻⁴, against the LU route's 2.8·10⁻⁴. What refinement at working precision buys is stability, and the accuracy floor belongs to the problem.

logKappa: 10

The arguments are the ones A correction cheaper than the problem passes. A value drawn at the generator's defaults instead would be a picture no essay asked for and no assertion has been run against.

Iterative refinement of the inverse-and-multiply solve at κ = 10^10The backward error starts at 6.4·10⁻⁹ and falls by about κu a step — 1.5·10⁻¹⁶, 2.2·10⁻¹⁷, 2.4·10⁻¹⁷, 2.4·10⁻¹⁷, 2·10⁻¹⁷ — reaching the LU route's 2.9·10⁻¹⁷ after 5 corrections, each costing 2n² flops against the 2n³ the inversion cost. The forward error, drawn above, does not improve: 1.1·10⁻⁶ to 4.9·10⁻⁸, against the LU route's 2·10⁻⁸. What refinement at working precision buys is stability, and the accuracy floor belongs to the problem.01234510⁻¹⁸10⁻¹⁵10⁻¹²10⁻⁹10⁻⁶10⁻³1correction steprelative errorLU route: η = 2.9·10⁻¹⁷LU route: forward 2·10⁻⁸forward errorbackward errorwhat a correction buysη before refinement6.4·10⁻⁹η after four steps2·10⁻¹⁷forward, unchanged4.9·10⁻⁸cost of a step, flops1800the residual is repairableand the accuracy floor is the problem's

The backward error starts at 6.4·10⁻⁹ and falls by about κu a step — 1.5·10⁻¹⁶, 2.2·10⁻¹⁷, 2.4·10⁻¹⁷, 2.4·10⁻¹⁷, 2·10⁻¹⁷ — reaching the LU route's 2.9·10⁻¹⁷ after 5 corrections, each costing 2n² flops against the 2n³ the inversion cost. The forward error, drawn above, does not improve: 1.1·10⁻⁶ to 4.9·10⁻⁸, against the LU route's 2·10⁻⁸. What refinement at working precision buys is stability, and the accuracy floor belongs to the problem.

logKappa: 14

The arguments are the ones Buying the accuracy back passes. A value drawn at the generator's defaults instead would be a picture no essay asked for and no assertion has been run against.

Iterative refinement of the inverse-and-multiply solve at κ = 10^14The backward error starts at 4.5·10⁻⁵ and falls by about κu a step — 8.1·10⁻⁹, 5.3·10⁻¹², 3.3·10⁻¹⁵, 3.1·10⁻¹⁷, 2.8·10⁻¹⁷ — reaching the LU route's 2.2·10⁻¹⁷ after 5 corrections, each costing 2n² flops against the 2n³ the inversion cost. The forward error, drawn above, does not improve: 0.015 to 7.1·10⁻⁴, against the LU route's 2.8·10⁻⁴. What refinement at working precision buys is stability, and the accuracy floor belongs to the problem.01234510⁻¹⁸10⁻¹⁵10⁻¹²10⁻⁹10⁻⁶10⁻³1correction steprelative errorLU route: η = 2.2·10⁻¹⁷LU route: forward 2.8·10⁻⁴forward errorbackward errorwhat a correction buysη before refinement4.5·10⁻⁵η after four steps2.8·10⁻¹⁷forward, unchanged7.1·10⁻⁴cost of a step, flops1800the residual is repairableand the accuracy floor is the problem's

The backward error starts at 4.5·10⁻⁵ and falls by about κu a step — 8.1·10⁻⁹, 5.3·10⁻¹², 3.3·10⁻¹⁵, 3.1·10⁻¹⁷, 2.8·10⁻¹⁷ — reaching the LU route's 2.2·10⁻¹⁷ after 5 corrections, each costing 2n² flops against the 2n³ the inversion cost. The forward error, drawn above, does not improve: 0.015 to 7.1·10⁻⁴, against the LU route's 2.8·10⁻⁴. What refinement at working precision buys is stability, and the accuracy floor belongs to the problem.

What it checked while drawing

Every figure above asserted its own claims on the way to being drawn, and a claim that failed would have failed the build rather than drawn a wrong picture. Those assertions used to leave no trace at all: a passing one returned true and the only evidence the figure had checked anything was that nothing crashed. The list below is what they actually said, collected by running this generator with an observer installed — not a description of what it is believed to check.

13 distinct claims across 3 sets of arguments, grouped below by shape — because most of them are one sentence with a different number in it, and how many separate times that sentence was put to the test is the informative part.

step 1 takes the backward error down by at least two decades — asserted 3 times

the constructed matrix has κ = 100000000000000 — asserted 2 times

a conditioning where the effect is above rounding and below breakdown

a power of ten rather than an exponent literal

a size the repeated inversions can afford

and after four of them it is where the LU route started

and the refinement bought orders of magnitude of stability against a small factor of accuracy

LU is for square matrices

matmul shapes agree

while the forward error stays at the LU route's number, which is the problem's floor

Against the rule

The rule does not apply to it. It factorises nothing, so there is no residual it could be withholding. That is worth stating rather than leaving blank: a site that reported the rule as satisfied by every generator would be counting mostly generators the rule never reached.

Across the library: the rule bites on 92 of 198 generators — 77 print a residual and 15 are exempt with a published reason; 106 factorise nothing. Read from lib/residual-rule.js, which is the same body the gate enforces from, and the gate's last check fails the build if this page and it disagree about any generator.

Where it is called

Changing this generator changes every figure on this list. That is what makes the list worth publishing rather than keeping in a check script.

The whole library · All essays · What must fail