kron-inverse
At its defaults it draws the kronecker spectrum of the inverse of a kronecker sum on 8 points a side. A Kronecker product B ⊗ C, read as a four-index array and cut between its two index pairs, is exactly rank one. The inverse of T ⊕ T is rank 8 at the same cut, so the format is not closed under inversion — which is why a solve in it goes through the eigenbasis rather than through an inverse. What the spectrum says is that it is nearly closed: the singular values are 1, 0.19, 0.0262, 0.00214 of the first, and the number of Kronecker terms needed runs 3, 5, 6, 7, 8, 8 at 10⁻², 10⁻⁴, 10⁻⁶, 10⁻⁸, 10⁻¹⁰ and 10⁻¹². That is 0.50 terms a decade — the same shape, and nearly the same number, as the 0.554 columns a decade the hierarchy field measures for a kernel block, arrived at from a different direction entirely.
kron-inverse is one function in lib/figures/tensor.js —
an index that is a tuple — a matrix that is d small ones, and the inverse that is nearly one. 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.
A Kronecker product B ⊗ C, read as a four-index array and cut between its two index pairs, is exactly rank one. The inverse of T ⊕ T is rank 8 at the same cut, so the format is not closed under inversion — which is why a solve in it goes through the eigenbasis rather than through an inverse. What the spectrum says is that it is nearly closed: the singular values are 1, 0.19, 0.0262, 0.00214 of the first, and the number of Kronecker terms needed runs 3, 5, 6, 7, 8, 8 at 10⁻², 10⁻⁴, 10⁻⁶, 10⁻⁸, 10⁻¹⁰ and 10⁻¹². That is 0.50 terms a decade — the same shape, and nearly the same number, as the 0.554 columns a decade the hierarchy field measures for a kernel block, arrived at from a different direction entirely.
n: 8
The arguments are the ones A rank that is not a property of the tensor 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.
A Kronecker product B ⊗ C, read as a four-index array and cut between its two index pairs, is exactly rank one. The inverse of T ⊕ T is rank 8 at the same cut, so the format is not closed under inversion — which is why a solve in it goes through the eigenbasis rather than through an inverse. What the spectrum says is that it is nearly closed: the singular values are 1, 0.19, 0.0262, 0.00214 of the first, and the number of Kronecker terms needed runs 3, 5, 6, 7, 8, 8 at 10⁻², 10⁻⁴, 10⁻⁶, 10⁻⁸, 10⁻¹⁰ and 10⁻¹². That is 0.50 terms a decade — the same shape, and nearly the same number, as the 0.554 columns a decade the hierarchy field measures for a kernel block, arrived at from a different direction entirely.
n: 14
The arguments are the ones A solve that is d decompositions 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.
A Kronecker product B ⊗ C, read as a four-index array and cut between its two index pairs, is exactly rank one. The inverse of T ⊕ T is rank 11 at the same cut, so the format is not closed under inversion — which is why a solve in it goes through the eigenbasis rather than through an inverse. What the spectrum says is that it is nearly closed: the singular values are 1, 0.205, 0.045, 0.00694 of the first, and the number of Kronecker terms needed runs 3, 5, 7, 8, 10, 11 at 10⁻², 10⁻⁴, 10⁻⁶, 10⁻⁸, 10⁻¹⁰ and 10⁻¹². That is 0.80 terms a decade — the same shape, and nearly the same number, as the 0.554 columns a decade the hierarchy field measures for a kernel block, arrived at from a different direction entirely.
n: 4
The arguments are the ones A solve that is d decompositions 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.
A Kronecker product B ⊗ C, read as a four-index array and cut between its two index pairs, is exactly rank one. The inverse of T ⊕ T is rank 4 at the same cut, so the format is not closed under inversion — which is why a solve in it goes through the eigenbasis rather than through an inverse. What the spectrum says is that it is nearly closed: the singular values are 1, 0.131, 0.00641, 9·10⁻⁵ of the first, and the number of Kronecker terms needed runs 2, 3, 4, 4, 4, 4 at 10⁻², 10⁻⁴, 10⁻⁶, 10⁻⁸, 10⁻¹⁰ and 10⁻¹². That is 0.20 terms a decade — the same shape, and nearly the same number, as the 0.554 columns a decade the hierarchy field measures for a kernel block, arrived at from a different direction entirely.
n: 10
The arguments are the ones A solve that is d decompositions 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.
A Kronecker product B ⊗ C, read as a four-index array and cut between its two index pairs, is exactly rank one. The inverse of T ⊕ T is rank 9 at the same cut, so the format is not closed under inversion — which is why a solve in it goes through the eigenbasis rather than through an inverse. What the spectrum says is that it is nearly closed: the singular values are 1, 0.199, 0.034, 0.00373 of the first, and the number of Kronecker terms needed runs 3, 5, 6, 7, 8, 9 at 10⁻², 10⁻⁴, 10⁻⁶, 10⁻⁸, 10⁻¹⁰ and 10⁻¹². That is 0.60 terms a decade — the same shape, and nearly the same number, as the 0.554 columns a decade the hierarchy field measures for a kernel block, arrived at from a different direction entirely.
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.
6 distinct claims across 5 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 size the inverse can be formed at
and a decade of accuracy costs under two terms
Jacobi needs a symmetric matrix
matmul shapes agree
the cut is drawn for two index pairs
the inverse is not one Kronecker product
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 146
of 287 generators —
131 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 rank that is not a property of the tensor
The same eight real numbers have rank three over the reals and rank two over the complexes, and a random 2 × 2 × 2 tensor has rank two with probability exactly π/4. Neither sentence has an analogue for matrices, where the rank is one number and a random matrix has the largest one.
When the index is a tupleA solve that is d decompositions
A Kronecker sum is closed under nothing useful — its inverse is not a Kronecker sum and no factorisation of it is one. What it has instead is eigenvectors that are Kronecker products, so a solve with 1,728 unknowns takes one decomposition of a 12 × 12 matrix and nothing else.
Iterating, instead of factorisingAn iterate that must be made smaller
Applying a Kronecker-sum operator to a low-rank iterate multiplies its ranks by d and adding two of them adds their ranks, so a solver in a compressed format cannot keep what it produces. Every step is followed by a truncation — and whether that truncation is a floor on the residual depends on the right-hand side rather than on the truncation.
Iterating, instead of factorisingAn operator with no entries
At the sizes where linear algebra is expensive the matrix does not exist. What exists is a subroutine that returns Av. Every Krylov method survives that unchanged; every algorithm that reads an entry disappears. And the derivative such a code computes is accurate to ten digits instead of sixteen, which turns out to cost nothing at all.
When the index is a tupleThe format that does not notice the dimension
A Tucker core is r^d numbers, so the format that repaired the definition still cannot go past five indices. Cutting between the indices rather than across them gives d − 1 ranks instead of d, storage linear in the number of indices, and a family whose ranks are two everywhere by an addition formula.
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.