null-basis-sweep
At its defaults it draws the reduced hessian and the answer, against how badly the basic columns were chosen. γ is the condition number of the first 4 columns of A, and the naive rule calls exactly those columns basic. Its reduced Hessian's condition number climbs from 83.77 to 4.871·10¹⁸ across ten decades of γ — the square, because κ(ZᵀHZ) ≤ κ(H)κ(Z)² and the bound is attained. Choosing the basic columns by a column-pivoted QR instead holds it between 31.72 and 43.09 at every stop. The two forward errors, measured against a BigInt answer, follow their own condition numbers: 0.3173 against 8.07·10⁻¹⁶ at γ = 10¹⁰. κ(A) is 10⁶ throughout and never moves — nothing about the problem's difficulty changes across this axis, only which columns a one-line rule happens to pick.
null-basis-sweep is one function in lib/figures/nullbasis.js —
the basis of a constraint — three spans of one null space, and the square between them. 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.
γ is the condition number of the first 4 columns of A, and the naive rule calls exactly those columns basic. Its reduced Hessian's condition number climbs from 83.77 to 4.871·10¹⁸ across ten decades of γ — the square, because κ(ZᵀHZ) ≤ κ(H)κ(Z)² and the bound is attained. Choosing the basic columns by a column-pivoted QR instead holds it between 31.72 and 43.09 at every stop. The two forward errors, measured against a BigInt answer, follow their own condition numbers: 0.3173 against 8.07·10⁻¹⁶ at γ = 10¹⁰. κ(A) is 10⁶ throughout and never moves — nothing about the problem's difficulty changes across this axis, only which columns a one-line rule happens to pick.
m: 4
The arguments are the ones A condition number sent to infinity 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.
γ is the condition number of the first 4 columns of A, and the naive rule calls exactly those columns basic. Its reduced Hessian's condition number climbs from 83.77 to 4.871·10¹⁸ across ten decades of γ — the square, because κ(ZᵀHZ) ≤ κ(H)κ(Z)² and the bound is attained. Choosing the basic columns by a column-pivoted QR instead holds it between 31.72 and 43.09 at every stop. The two forward errors, measured against a BigInt answer, follow their own condition numbers: 0.3173 against 8.07·10⁻¹⁶ at γ = 10¹⁰. κ(A) is 10⁶ throughout and never moves — nothing about the problem's difficulty changes across this axis, only which columns a one-line rule happens to pick.
m: 2
The arguments are the ones A preconditioner that need not know the constraint 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.
γ is the condition number of the first 2 columns of A, and the naive rule calls exactly those columns basic. Its reduced Hessian's condition number climbs from 148.6 to 2.711·10¹⁹ across ten decades of γ — the square, because κ(ZᵀHZ) ≤ κ(H)κ(Z)² and the bound is attained. Choosing the basic columns by a column-pivoted QR instead holds it between 64.71 and 75.33 at every stop. The two forward errors, measured against a BigInt answer, follow their own condition numbers: 0.8965 against 2.01·10⁻¹⁵ at γ = 10¹⁰. κ(A) is 10⁶ throughout and never moves — nothing about the problem's difficulty changes across this axis, only which columns a one-line rule happens to pick.
m: 6
The arguments are the ones The basis nobody chose on purpose 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.
γ is the condition number of the first 6 columns of A, and the naive rule calls exactly those columns basic. Its reduced Hessian's condition number climbs from 27.85 to 7.309·10¹³ across ten decades of γ — the square, because κ(ZᵀHZ) ≤ κ(H)κ(Z)² and the bound is attained. Choosing the basic columns by a column-pivoted QR instead holds it between 6.175 and 20.89 at every stop. The two forward errors, measured against a BigInt answer, follow their own condition numbers: 0.05908 against 5.51·10⁻¹⁶ at γ = 10¹⁰. κ(A) is 10⁶ throughout and never moves — nothing about the problem's difficulty changes across this axis, only which columns a one-line rule happens to pick.
m: 3
The arguments are the ones The basis nobody chose on purpose 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.
γ is the condition number of the first 3 columns of A, and the naive rule calls exactly those columns basic. Its reduced Hessian's condition number climbs from 277.2 to 8.131·10¹⁷ across ten decades of γ — the square, because κ(ZᵀHZ) ≤ κ(H)κ(Z)² and the bound is attained. Choosing the basic columns by a column-pivoted QR instead holds it between 43.16 and 55.06 at every stop. The two forward errors, measured against a BigInt answer, follow their own condition numbers: 0.5617 against 3.07·10⁻¹⁶ at γ = 10¹⁰. κ(A) is 10⁶ throughout and never moves — nothing about the problem's difficulty changes across this axis, only which columns a one-line rule happens to pick.
m: 5
The arguments are the ones The basis nobody chose on purpose 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.
γ is the condition number of the first 5 columns of A, and the naive rule calls exactly those columns basic. Its reduced Hessian's condition number climbs from 36.88 to 6.626·10¹⁶ across ten decades of γ — the square, because κ(ZᵀHZ) ≤ κ(H)κ(Z)² and the bound is attained. Choosing the basic columns by a column-pivoted QR instead holds it between 24.27 and 27.3 at every stop. The two forward errors, measured against a BigInt answer, follow their own condition numbers: 0.3844 against 2.1·10⁻¹⁶ at γ = 10¹⁰. κ(A) is 10⁶ throughout and never moves — nothing about the problem's difficulty changes across this axis, only which columns a one-line rule happens to pick.
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.
10 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 basis rule this file implements
a constraint no larger than the problem
a finite double, since an infinity is not a rational
a problem the exact solve can afford at every stop
and the pivoted one does not rise
fewer constraints than unknowns
fewer constraints than unknowns, so something is left to minimise
LU is for square matrices
matmul shapes agree
the naive reduced Hessian rises with γ²
Against the rule
It draws a decomposition and prints its residual. It calls
basisComparison,
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 165
of 306 generators —
150 print a residual and
15 are exempt with a published reason;
141 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 condition number sent to infinity
An interior-point method manufactures an ill-conditioned matrix on every iteration, deliberately, because the separating of a diagonal is how it discovers which constraints are active. Written one way the answer keeps fifteen digits at a condition number of 3·10¹⁵. Written the other way — the way almost every code writes it — it has none left.
The matrix a constraint makesA preconditioner that need not know the constraint
Keep the constraint block exactly and replace the objective block by anything positive definite on the null space. The preconditioned matrix then has 2m eigenvalues at exactly one, and its remaining n − m are the generalised eigenvalues of a pencil in which the constraint does not appear. Sweep its condition number over six decades and they do not move in six digits.
Orthogonality, measuredThe basis nobody chose on purpose
A method that eliminates a constraint has to pick a basis for its null space, and every basis is correct. Their condition numbers are eight orders apart, the reduced problem inherits the square, and the choice is usually made by a one-line rule nobody thought of as a numerical decision.
Randomised, and the guarantee that changes kindThe half of a problem a sketch may touch
A sketch guarantees that a norm is preserved to within a factor. An equality constraint is a statement that a quantity is zero, and no multiplicative guarantee says anything about zero. Sketch a constrained problem written as a weighted one and the constraint is not destroyed — it is demoted, from a violation of 1/τ² to one of ε/τ, exactly half the exponent.
The matrix a constraint makesTwo ways to remove a constraint
A constrained system can be reduced by eliminating the multipliers or by eliminating the constrained directions. Both give the same answer in exact arithmetic and inherit different condition numbers — one of them squares the constraint's, and the other does not contain it at all.