Relative error of scaling and squaring against the number of squarings, μ = 4

At its defaults it draws relative error of scaling and squaring against the number of squarings, μ = 4. Each point computes e^(A/2ˢ) by a Padé approximant and squares it s times, against a closed-form exponential. At s = 0 the approximant is being used far outside its range and the error is 6·10⁻¹²; the best is 6.88·10⁻¹⁶ at s = 2; at s = 15 it has risen again to 3.16·10⁻¹². The right-hand rise is the squaring phase amplifying its own rounding, which is why a library chooses s from ‖A‖ rather than taking as many as it can afford.

squaring-cost is one function in lib/figures/funm.js — matrix functions — the definition that is not a method, and the vector that was wanted. 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.

Each point computes e^(A/2ˢ) by a Padé approximant and squares it s times, against a closed-form exponential. At s = 0 the approximant is being used far outside its range and the error is 6·10⁻¹²; the best is 6.88·10⁻¹⁶ at s = 2; at s = 15 it has risen again to 3.16·10⁻¹². The right-hand rise is the squaring phase amplifying its own rounding, which is why a library chooses s from ‖A‖ rather than taking as many as it can afford.

Each point computes e^(A/2ˢ) by a Padé approximant and squares it s times, against a closed-form exponential. At s = 0 the approximant is being used far outside its range and the error is 6·10⁻¹²; the best is 6.88·10⁻¹⁶ at s = 2; at s = 15 it has risen again to 3.16·10⁻¹². The right-hand rise is the squaring phase amplifying its own rounding, which is why a library chooses s from ‖A‖ rather than taking as many as it can afford.

Each point computes e^(A/2ˢ) by a Padé approximant and squares it s times, against a closed-form exponential. At s = 0 the approximant is being used far outside its range and the error is 4.01·10⁻¹⁵; the best is 2.12·10⁻¹⁶ at s = 1; at s = 15 it has risen again to 3.16·10⁻¹². The right-hand rise is the squaring phase amplifying its own rounding, which is why a library chooses s from ‖A‖ rather than taking as many as it can afford.

Each point computes e^(A/2ˢ) by a Padé approximant and squares it s times, against a closed-form exponential. At s = 0 the approximant is being used far outside its range and the error is 5.55·10⁻¹¹; the best is 9.08·10⁻¹⁶ at s = 2; at s = 15 it has risen again to 3.16·10⁻¹². The right-hand rise is the squaring phase amplifying its own rounding, which is why a library chooses s from ‖A‖ rather than taking as many as it can afford.

Every figure above checked its own claims on the way to being drawn, and a claim that failed would have stopped the picture rather than shipped a wrong one. Those checks 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.

7 distinct claims across 4 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.

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 217 of 397 generators — 199 print a residual and 18 are exempt with a published reason; 180 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.