solver-backward
At its defaults it draws backward error with and without the structure, for levinson and for elimination, n = 12. Both solvers are backward stable on this family by the usual measure: the smallest perturbation of any kind that explains either answer stays below 3.1·10⁻¹⁷ at every ρ, and the two curves are indistinguishable. Insisting the perturbation be a symmetric Toeplitz matrix — the kind of object the problem was posed with — lifts both by orders, and at ρ = 0.999 Levinson's rises by a factor of 2.48·10⁶. Neither number is alarming in absolute terms; what is worth carrying is that the reassuring one is the one that is reported, and the two are not measuring the same thing.
solver-backward is one function in lib/figures/structbe.js —
structured backward error — whether the nearby problem is the same kind of problem. 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.
Both solvers are backward stable on this family by the usual measure: the smallest perturbation of any kind that explains either answer stays below 3.1·10⁻¹⁷ at every ρ, and the two curves are indistinguishable. Insisting the perturbation be a symmetric Toeplitz matrix — the kind of object the problem was posed with — lifts both by orders, and at ρ = 0.999 Levinson's rises by a factor of 2.48·10⁶. Neither number is alarming in absolute terms; what is worth carrying is that the reassuring one is the one that is reported, and the two are not measuring the same thing.
n: 12
The arguments are the ones A nearby problem of the wrong kind 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.
Both solvers are backward stable on this family by the usual measure: the smallest perturbation of any kind that explains either answer stays below 3.1·10⁻¹⁷ at every ρ, and the two curves are indistinguishable. Insisting the perturbation be a symmetric Toeplitz matrix — the kind of object the problem was posed with — lifts both by orders, and at ρ = 0.999 Levinson's rises by a factor of 2.48·10⁶. Neither number is alarming in absolute terms; what is worth carrying is that the reassuring one is the one that is reported, and the two are not measuring the same thing.
n: 20
The arguments are the ones A nearby problem of the wrong kind 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.
Both solvers are backward stable on this family by the usual measure: the smallest perturbation of any kind that explains either answer stays below 4.2·10⁻¹⁷ at every ρ, and the two curves are indistinguishable. Insisting the perturbation be a symmetric Toeplitz matrix — the kind of object the problem was posed with — lifts both by orders, and at ρ = 0.999 Levinson's rises by a factor of 3.059·10⁶. Neither number is alarming in absolute terms; what is worth carrying is that the reassuring one is the one that is reported, and the two are not measuring the same thing.
n: 8
The arguments are the ones A nearby problem of the wrong kind 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.
Both solvers are backward stable on this family by the usual measure: the smallest perturbation of any kind that explains either answer stays below 4.7·10⁻¹⁷ at every ρ, and the two curves are indistinguishable. Insisting the perturbation be a symmetric Toeplitz matrix — the kind of object the problem was posed with — lifts both by orders, and at ρ = 0.999 Levinson's rises by a factor of 9.478·10⁴. Neither number is alarming in absolute terms; what is worth carrying is that the reassuring one is the one that is reported, and the two are not measuring the same thing.
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 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.
Levinson is backward stable at ρ = 0.5 — asserted 8 times
a positive definite Toeplitz matrix, whose reflection coefficients stay inside the unit circle
a size the structured minimisation can be solved at for every ρ
and its structured backward error is the larger
because the perturbation that explains it is not Toeplitz
LU is for square matrices
Against the rule
It draws a decomposition and prints its residual. It calls
solverSweep,
and every figure above carries the badge — which residualcheck verifies by looking
for it in the emitted SVG rather than by finding the call that builds one. A badge that is
constructed and then left out of the body is the failure that check exists for.
Across the library: the rule bites on 113
of 219 generators —
98 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.
A nearby problem of the wrong kind
A good algorithm returns the exact answer to a nearby problem. A hundred and eighteen essays have measured the distance and not one has asked what the nearby problem looks like. On a Toeplitz system it is a rank-one matrix that is constant along none of its diagonals — and the smallest one that is Toeplitz is two and a half million times larger.
Structure, and the solver that cannot see itThe condition number of the model
Describe a 40×40 Toeplitz matrix by its 1,600 entries and its condition number is 78,800. Describe it by the one number it actually contains and the condition number is 61.9. The three decades in between are not an approximation or a bound — they are what κ has been over-stating, and the drop is not where the linear algebra is.