scaling-recovery
At its defaults it draws what two lines of scaling are worth: the same quadratic in nine systems of units. The forward error against the closed form for an overdamped chain of 8 masses, before and after Fan–Lin–Van Dooren scaling. The unscaled curve runs 7.49·10⁻¹⁴ to 0.001258 — every digit gone by the far end — and the scaled one runs 1.26·10⁻¹³ to 8.23·10⁻¹⁴, flat to within a factor of 2.01. The scaling is γ = √(‖K‖/‖M‖) and δ = 2/(‖K‖ + γ‖C‖), computed from three norms and nothing else, and the map back is λ = γμ with no rounding in the statement. Flatness is the half that matters: after scaling every stop of the sweep IS the same problem, so there is nothing left for the change of units to do.
scaling-recovery is one function in lib/figures/qepscale.js —
the units a polynomial is written in — two lines of scaling, a prediction that is half right, and a format's edge. 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.
The forward error against the closed form for an overdamped chain of 8 masses, before and after Fan–Lin–Van Dooren scaling. The unscaled curve runs 7.49·10⁻¹⁴ to 0.001258 — every digit gone by the far end — and the scaled one runs 1.26·10⁻¹³ to 8.23·10⁻¹⁴, flat to within a factor of 2.01. The scaling is γ = √(‖K‖/‖M‖) and δ = 2/(‖K‖ + γ‖C‖), computed from three norms and nothing else, and the map back is λ = γμ with no rounding in the statement. Flatness is the half that matters: after scaling every stop of the sweep IS the same problem, so there is nothing left for the change of units to do.
n: 8
The arguments are the ones A backward-stable answer to a problem nobody asked 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.
The forward error against the closed form for an overdamped chain of 8 masses, before and after Fan–Lin–Van Dooren scaling. The unscaled curve runs 7.49·10⁻¹⁴ to 0.001258 — every digit gone by the far end — and the scaled one runs 1.26·10⁻¹³ to 8.23·10⁻¹⁴, flat to within a factor of 2.01. The scaling is γ = √(‖K‖/‖M‖) and δ = 2/(‖K‖ + γ‖C‖), computed from three norms and nothing else, and the map back is λ = γμ with no rounding in the statement. Flatness is the half that matters: after scaling every stop of the sweep IS the same problem, so there is nothing left for the change of units to do.
n: 12
The arguments are the ones A backward-stable answer to a problem nobody asked 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.
The forward error against the closed form for an overdamped chain of 12 masses, before and after Fan–Lin–Van Dooren scaling. The unscaled curve runs 3.72·10⁻¹⁴ to 0.3958 — every digit gone by the far end — and the scaled one runs 1.04·10⁻¹³ to 3.02·10⁻¹⁴, flat to within a factor of 8.1. The scaling is γ = √(‖K‖/‖M‖) and δ = 2/(‖K‖ + γ‖C‖), computed from three norms and nothing else, and the map back is λ = γμ with no rounding in the statement. Flatness is the half that matters: after scaling every stop of the sweep IS the same problem, so there is nothing left for the change of units to do.
n: 4
The arguments are the ones Six routes to one spectrum 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.
The forward error against the closed form for an overdamped chain of 4 masses, before and after Fan–Lin–Van Dooren scaling. The unscaled curve runs 7.01·10⁻¹⁵ to 4.331·10⁻⁴ — every digit gone by the far end — and the scaled one runs 7.67·10⁻¹⁵ to 4.77·10⁻¹⁵, flat to within a factor of 2.25. The scaling is γ = √(‖K‖/‖M‖) and δ = 2/(‖K‖ + γ‖C‖), computed from three norms and nothing else, and the map back is λ = γμ with no rounding in the statement. Flatness is the half that matters: after scaling every stop of the sweep IS the same problem, so there is nothing left for the change of units to do.
n: 6
The arguments are the ones The scaling that buys ten orders 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.
The forward error against the closed form for an overdamped chain of 6 masses, before and after Fan–Lin–Van Dooren scaling. The unscaled curve runs 9.14·10⁻¹⁵ to 0.006738 — every digit gone by the far end — and the scaled one runs 2.59·10⁻¹⁴ to 1.02·10⁻¹⁴, flat to within a factor of 7.39. The scaling is γ = √(‖K‖/‖M‖) and δ = 2/(‖K‖ + γ‖C‖), computed from three norms and nothing else, and the map back is λ = γμ with no rounding in the statement. Flatness is the half that matters: after scaling every stop of the sweep IS the same problem, so there is nothing left for the change of units to do.
n: 10
The arguments are the ones The scaling that buys ten orders 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.
The forward error against the closed form for an overdamped chain of 10 masses, before and after Fan–Lin–Van Dooren scaling. The unscaled curve runs 3.1·10⁻¹³ to 0.07412 — every digit gone by the far end — and the scaled one runs 6.09·10⁻¹⁴ to 2.72·10⁻¹⁴, flat to within a factor of 5.65. The scaling is γ = √(‖K‖/‖M‖) and δ = 2/(‖K‖ + γ‖C‖), computed from three norms and nothing else, and the map back is λ = γμ with no rounding in the statement. Flatness is the half that matters: after scaling every stop of the sweep IS the same problem, so there is nothing left for the change of units to do.
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.
17 distinct claims across 6 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.
a chain long enough to have a spectrum and short enough to draw
a linearisation has as many eigenvalues as it has rows
a positive change of units
a positive mass
a quadratic with both outer coefficients present
a reduction this file knows
a size the sweep can afford
an inverse iterate that is a vector
an overdamped chain, whose spectrum is entirely real
and the scaled one does not
damping that removes energy rather than adding it
every computed eigenvalue is matched to an unused exact one
LU is for square matrices
matmul shapes agree
some real eigenpair to measure
the unscaled error grows across the sweep
two spectra of the same size
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 173
of 325 generators —
158 print a residual and
15 are exempt with a published reason;
152 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.
A backward-stable answer to a problem nobody asked
One quadratic eigenvalue problem, in nine systems of units, with a change of variable that is exact in both directions. The residual the solver prints stays at the rounding level at every stop. The answer loses eleven orders of magnitude, and the two facts are consistent.
Iterating, instead of factorisingA Krylov space for a problem that is not linear
A quadratic eigenvalue problem has no matrix to build a Krylov space out of. The recurrence that builds one anyway stores half as many numbers, returns twice as many Ritz values — and stops being a basis at twenty vectors while the answer it gives keeps improving.
The eigenvalue problem that is not linearA matrix that depends on its own eigenvalue
A damped structure does not produce Ax = λx. It produces (λ²M + λC + K)x = 0, where the matrix whose null vector is wanted is a function of the number being solved for — so there is nothing to factorise, an n × n problem has 2n answers, and the eigenvectors cannot be a basis.
The eigenvalue problem that is not linearA spectrum that comes in reciprocal pairs
A palindromic quadratic reads the same backwards, so λ is an eigenvalue exactly when 1/λ is. A general solver discards that, computes the large half of the spectrum perfectly and the small half to seven digits — and the small half is a division away from being perfect too.
The eigenvalue problem that is not linearEvery eigenvalue real, and a test that says so
A quadratic eigenvalue problem has no reason to have real eigenvalues. One class does, as a property rather than an outcome, and the proof is a Cholesky that completes. The boundary of the class has a closed form, and at the boundary the arithmetic loses half its digits with nothing ill conditioned anywhere.
The eigenvalue problem that is not linearSix routes to one spectrum
Three linearisations of one quadratic, each reduced to a standard eigenvalue problem two ways. All six have exactly the same eigenvalues in exact arithmetic. On a well-scaled problem they differ by noise; on a badly scaled one by a factor of forty; and two of the six are the same matrix.
The eigenvalue problem that is not linearThe scaling that buys ten orders
Two lines computed from three norms, a change of variable that is exact in both directions, and the whole of the loss the previous essay measured comes back — flat, at every stop, because after scaling every stop is the same problem.
The arithmetic underneathThe units that overflow before the answer does
A change of variable that is exact in the algebra requires γ² times a matrix to be a number the format can hold. In binary64 that is a bound nobody meets by accident. In binary32 it arrives at 10¹⁹ and in fp16 at 256, and past it there is no answer rather than a poor one.