fill-rank
At its defaults it draws columns needed by the block between a separator's two halves, against the length of the separator. The block is 3×4, 5×6, 7×8, 11×12 across the sweep, so its size more than triples. In the separator's own numbering — the unknowns in the order they sit on the line — it needs 3, 4, 5, 6 columns at 10⁻⁸: about one more per doubling, which is a logarithm. Renumber the same Schur complement by one symmetric permutation and the same block needs 3, 5, 7, 11 — all of them at eight digits and tighter, and a multiple of the geometric count at every tolerance drawn. Nothing about the matrix changed. What changed is that a cluster of a shuffled numbering is scattered along the whole separator, so every block mixes near interactions with far ones and there is no smooth kernel left to compress. The ordering that works here is not chosen: it is the one the separator's geometry already has, which is why nested dissection leaves a compressible fill and a fill-reducing ordering chosen on the graph alone need not.
fill-rank is one function in lib/figures/hfill.js —
the fill — dense, and not independent, on the separator nested dissection leaves. 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 block is 3×4, 5×6, 7×8, 11×12 across the sweep, so its size more than triples. In the separator's own numbering — the unknowns in the order they sit on the line — it needs 3, 4, 5, 6 columns at 10⁻⁸: about one more per doubling, which is a logarithm. Renumber the same Schur complement by one symmetric permutation and the same block needs 3, 5, 7, 11 — all of them at eight digits and tighter, and a multiple of the geometric count at every tolerance drawn. Nothing about the matrix changed. What changed is that a cluster of a shuffled numbering is scattered along the whole separator, so every block mixes near interactions with far ones and there is no smooth kernel left to compress. The ordering that works here is not chosen: it is the one the separator's geometry already has, which is why nested dissection leaves a compressible fill and a fill-reducing ordering chosen on the graph alone need not.
logTol: -4
The arguments are the ones A rank that is a number of digits 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 block is 3×4, 5×6, 7×8, 11×12 across the sweep, so its size more than triples. In the separator's own numbering — the unknowns in the order they sit on the line — it needs 3, 3, 3, 4 columns at 10⁻⁴: about one more per doubling, which is a logarithm. Renumber the same Schur complement by one symmetric permutation and the same block needs 3, 5, 7, 10 — all of them at eight digits and tighter, and a multiple of the geometric count at every tolerance drawn. Nothing about the matrix changed. What changed is that a cluster of a shuffled numbering is scattered along the whole separator, so every block mixes near interactions with far ones and there is no smooth kernel left to compress. The ordering that works here is not chosen: it is the one the separator's geometry already has, which is why nested dissection leaves a compressible fill and a fill-reducing ordering chosen on the graph alone need not.
logTol: -8
The arguments are the ones The factor is not sparse 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 block is 3×4, 5×6, 7×8, 11×12 across the sweep, so its size more than triples. In the separator's own numbering — the unknowns in the order they sit on the line — it needs 3, 4, 5, 6 columns at 10⁻⁸: about one more per doubling, which is a logarithm. Renumber the same Schur complement by one symmetric permutation and the same block needs 3, 5, 7, 11 — all of them at eight digits and tighter, and a multiple of the geometric count at every tolerance drawn. Nothing about the matrix changed. What changed is that a cluster of a shuffled numbering is scattered along the whole separator, so every block mixes near interactions with far ones and there is no smooth kernel left to compress. The ordering that works here is not chosen: it is the one the separator's geometry already has, which is why nested dissection leaves a compressible fill and a fill-reducing ordering chosen on the graph alone need not.
logTol: -12
The arguments are the ones The fill that is not independent 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 block is 3×4, 5×6, 7×8, 11×12 across the sweep, so its size more than triples. In the separator's own numbering — the unknowns in the order they sit on the line — it needs 3, 5, 6, 7 columns at 10⁻¹²: about one more per doubling, which is a logarithm. Renumber the same Schur complement by one symmetric permutation and the same block needs 3, 5, 7, 11 — all of them at eight digits and tighter, and a multiple of the geometric count at every tolerance drawn. Nothing about the matrix changed. What changed is that a cluster of a shuffled numbering is scattered along the whole separator, so every block mixes near interactions with far ones and there is no smooth kernel left to compress. The ordering that works here is not chosen: it is the one the separator's geometry already has, which is why nested dissection leaves a compressible fill and a fill-reducing ordering chosen on the graph alone need not.
logTol: -2
The arguments are the ones The fill that is not independent 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 block is 3×4, 5×6, 7×8, 11×12 across the sweep, so its size more than triples. In the separator's own numbering — the unknowns in the order they sit on the line — it needs 2, 2, 2, 2 columns at 0.01: about one more per doubling, which is a logarithm. Renumber the same Schur complement by one symmetric permutation and the same block needs 3, 4, 6, 9 — all of them at eight digits and tighter, and a multiple of the geometric count at every tolerance drawn. Nothing about the matrix changed. What changed is that a cluster of a shuffled numbering is scattered along the whole separator, so every block mixes near interactions with far ones and there is no smooth kernel left to compress. The ordering that works here is not chosen: it is the one the separator's geometry already has, which is why nested dissection leaves a compressible fill and a fill-reducing ordering chosen on the graph alone need not.
logTol: -6
The arguments are the ones The fill that is not independent 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 block is 3×4, 5×6, 7×8, 11×12 across the sweep, so its size more than triples. In the separator's own numbering — the unknowns in the order they sit on the line — it needs 3, 4, 4, 5 columns at 10⁻⁶: about one more per doubling, which is a logarithm. Renumber the same Schur complement by one symmetric permutation and the same block needs 3, 5, 7, 10 — all of them at eight digits and tighter, and a multiple of the geometric count at every tolerance drawn. Nothing about the matrix changed. What changed is that a cluster of a shuffled numbering is scattered along the whole separator, so every block mixes near interactions with far ones and there is no smooth kernel left to compress. The ordering that works here is not chosen: it is the one the separator's geometry already has, which is why nested dissection leaves a compressible fill and a fill-reducing ordering chosen on the graph alone need not.
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 grid the two dense half-factorisations are affordable at — the left half is a 21-square and its elimination is cubic in that — asserted 4 times
the same Schur complement, differently numbered, never needs fewer columns at a separator of 7 — asserted 4 times
an accuracy the block has singular values across
an odd grid, so the separator is a column and the two halves are equal
an operator this file defines
and at the longest separator the renumbered block is within two columns of the whole of it
and the rank moves by a handful of columns
LU is for square matrices
matmul shapes agree
the block more than triples across the sweep, so a rank that does not move is a measurement
while the separator's own numbering needs well under all of them
Against the rule
It draws a decomposition and prints its residual. It calls
rankAgainstSeparator,
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 141
of 264 generators —
126 print a residual and
15 are exempt with a published reason;
123 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 rank that is a number of digits
Ask a kernel block for two digits and it costs two columns; ask for fourteen and it costs nine. The curve is a straight line at 0.55 columns a decade, and the bound the geometry gives is a straight line too — at 3.32, which is the same shape and six times the price.
Sparsity, and what elimination costsThe factor is not sparse
A sparse matrix has a factor that is not sparse, and the gap between them is the entire reason iterative methods exist. The entries elimination creates can be counted before any arithmetic runs, from the graph alone.
Sparsity, and what elimination costsThe fill that is not independent
Eliminate both halves of a grid and what is left on the separator is 100 per cent nonzero — the sparsity field's result, unchanged. Its off-diagonal block is 11 by 12 and six columns describe it to eight digits. Renumber the separator and the same block needs all eleven.
Neither sparse nor denseThe same matrix, numbered twice
One symmetric permutation. The condition number is 24.3948 either way to eight digits and the Frobenius norm is 6.13996414·10³ either way to twelve. The partition that stored 27,008 numbers now finds no admissible pair anywhere and stores all 65,536, and the format that compresses regardless stores 118,208.
Neither sparse nor denseThe size the rank does not notice
Sample a kernel block at 32, 64, 128 and 256 points a side and it needs five columns, five, five and five. Sample the touching block next to it at the same four sizes and it needs nine, eleven, twelve and thirteen. Same kernel, same accuracy, one number and a logarithm.
Sparsity, and what elimination costsTwo ends of the same arrow
One matrix, one row moved from the front of the elimination order to the back, and the factor goes from completely dense to no fill at all. Both factorisations are exact to rounding, and nothing numerical chose between them.
Sparsity, and what elimination costsWhat the symbolic phase can only bound
Without pivoting, the fill can be computed from the graph and the count is exact — 233 predicted, 233 measured. With pivoting it is 233 predicted and 242 measured, and what survives is a bound that is right at every threshold and loose by 1.7 times at the largest grid drawn.
Neither sparse nor denseWhich pairs are allowed to be small
A hierarchical representation is a partition of the matrix into blocks, and the rule that produces it reads four numbers per pair of index clusters and not one entry of the matrix. On a 256-square it yields 112 blocks, 66 of them stored as two thin factors, none of rank above five.