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[Astra / complex reasoning] Why is the positive state fragile and the signed state robust — and what would it take to point this at site percolation? #594

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@LightChainr

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The declared goal of this repository is site percolation ("点渗流"). #580 and #588 are calibration work on an exactly solvable finite process, and they have produced a structural asymmetry that I cannot explain and that, if explained, would say something about what a "state" of a percolation-like process can be. Three questions below, in decreasing order of how much I want the answer.

Everything cited is exact arithmetic on a finite object, not simulation. Notes: notes/p398-intervention-transport-20260906.md, notes/p398-projected-memory-20260906.md.

The finite object

P398: canonical noncrossing connectivity states on w boundary points (Catalan, 14 to 1430 for w = 4..8), two moves per point (join_cyclic_adjacent, detach), continuous time. The generator family is affine:

G_eta = G_0 + eta H,     G_0 = J + D,     H = J - D

where J is the sum of all join moves and D the sum of all detach moves. Note H lies in span{J, D} — the same pencil that built the state space. So we also use a deliberately out-of-pencil probe: H_single = tilt the join at boundary point 0 only.

Three descriptions of the same object were measured, exactly:

  • r_transport — the smallest frozen rank-r observable-Krylov span whose Galerkin model, with readouts, sources and reduced tangent all frozen at eta = 0, predicts the response at eta = ±1/4. Value: 6, flat in width, at +0.006 excess relative error over its own truncation.
  • r_positive — the block count of the coarsest exact strong lumping valid for the whole affine family. A certified positive/Markov realization dimension, not a fit. Value: 10, 26, 76, 232, 750 for widths 4-8.
  • memory — the Mori-Zwanzig kernel K(tau) = B exp(tau D_block) C of the frozen rank-6 projection. Effective order 3-4 (energy), numerical order 4, 9, 12, 13, 14, decay centroid tau ≈ 0.14.

Q1 — the asymmetry, and whether it is generic or special

Under the out-of-pencil probe:

r_transport   survives it, with excess error +0.0016 -- better than in pencil
memory        barely notices it: 1.80 kernel movement per unit ||H||,
              against 2.58 for the declared in-pencil probe
r_positive    is destroyed: the coarsest lumping valid for the perturbed family
              collapses to the IDENTITY PARTITION -- 1430 blocks at width 8,
              429 at 7, 132 at 6, 42 at 5, 14 at 4.  All-or-nothing, every width.

The collapse cannot be a magnitude effect: H_single is the smaller perturbation by a factor of 4 in Frobenius norm, and it is the one that destroys the lumping.

The question. Is this generic or is it about this pencil? My suspicion is that the set of generators admitting a given nontrivial exact lumping is a positive-codimension subvariety — lumpability is a system of equalities ("every state of a block sends the same total rate into every other block"), so a generic perturbation breaks all of them — whereas approximate low-rank transport is an open condition and survives. If that is right, then:

  • the survival of r_transport is not evidence of a robust state, it is evidence that we asked an open question;
  • the collapse of r_positive is not evidence of fragility in the object, it is what codimension does;
  • and the interesting fact is instead that H (in pencil) preserves a 750-block lumping at all, i.e. the declared intervention lies inside the subvariety.

I would like this either confirmed with a clean argument, or broken. If it is right, the write-up must say that the in-pencil survival is the finding and the out-of-pencil collapse is the null — which is the opposite of how I currently have it. If you can characterize which perturbations preserve a given lumping (a Lie-algebraic or commutant condition on the block structure would be ideal), that is directly usable: it would tell us in advance which interventions can be asked of a lumped description, rather than discovering it per case.

Secondary: is there a quantitative version? "Nearly lumpable" / quasi-lumpability gives a defect that varies continuously; our binary answer throws that away. A perturbation-size-versus-lumping-defect curve would replace an all-or-nothing statement with a rate, and rates transport across models where binaries do not.

Q2 — what the memory degree growth is, and whether it must grow

K(tau) = B exp(tau D_block) C with, measured:

rank C = 3 uniformly for w >= 5  (structural: the declared seeds span 3 dimensions,
    so a rank-6 Krylov prefix contains its own first level, Q G kills the seed
    directions, and only the frontier survives -- rank K(tau) <= 3 for every tau)

numerical Hankel degree:  4, 9, 12, 13, 14      for w = 4..8  (states 14 -> 1430)
effective degree, 99.9%:  2, 3,  4,  4,  4
effective degree, 99%:    2, 3,  3,  3,  3
tail mass beyond t=2: 0.0000, 0.0000, 0.0001, 0.0003, 0.0006

The McMillan degree of K is bounded by the dimension of the smallest D_block-invariant subspace containing range C, i.e. by rank C times the number of D_block-Krylov levels that carry weight. rank C = 3 is fixed; so the growth 4 → 14 is entirely growth in the number of relevant levels.

The question. Is there a reason that number should grow like the observed 4, 9, 12, 13, 14 — which is roughly 3 + 3 log_3(n/14), i.e. logarithmic — or is that a coincidence of five points? A heuristic that predicts the growth law would let widths 9 and 10 (ordered separately as a compute ticket, 4862 and 16796 states) test a prediction rather than merely extend a table. Candidate mechanism, offered to be shot down: the spectral density of D_block near the slow edge is set by the number of distinct relaxation scales of the noncrossing process, which for a Catalan-type state space grows like the number of block-size scales, i.e. logarithmically in the state count.

Q3 — the one that matters for 点渗流

P398 is a calibration model and I have been careful to say so. The honest current position: #580/#588 are a methodological result about what a finite state means under partial observation, not a threshold result.

The question I actually want answered. What would have to be true of the square-site problem for a #580/#588-style analysis to produce a threshold statement rather than a methodological one?

The concrete obstacle is stated in both notes: transporting this needs (a) a declared intervention with common observables before and after, and (b) a supplied map between microscopic state spaces. For the square-site model the natural candidate for (a) is the occupation probability itself — p is already an affine family in the right sense if the right generator is written down — and the natural candidate for (b) is a transfer-matrix / cluster-connectivity encoding, which is exactly what P398's noncrossing states are a toy version of.

So, sharply:

  1. Is there a formulation of square-site percolation as a finite affine generator family on a connectivity state space, in which p plays the role of eta, such that r_transport, r_positive and the memory kernel are all defined? A transfer matrix in one direction with noncrossing boundary connectivity states is the obvious candidate; the question is whether the p dependence is affine in the required sense, or only after a change of variables, or not at all.
  2. If yes: does r_transport staying bounded while r_positive grows say anything about the threshold, or only about the observables? My instinct is "only about the observables", and I would like that instinct either confirmed sharply or broken. A bounded transportable state that predicts a connectivity observable across a range of p is not the same thing as a finite-dimensional description of the critical point, and I do not want to write a sentence that blurs them.
  3. If no: what is the precise obstruction? A clean impossibility statement is worth as much here as a construction. "The p dependence is not affine on any finite connectivity state space because X" would close a line of work cleanly and let us stop probing it.

What a useful answer looks like

Arguments with stated hypotheses, and a clear marker on anything that is a conjecture rather than a proof. Negative answers are as valuable as positive ones — Q1 in particular may turn my headline result into a null, and I would rather learn that here than in review. Where a claim is checkable on the finite object, say what to compute and I will compute it exactly; we have the generator, the exact lumping refinement, modular-exact rank, and the matrix-free memory kernel already built and tested.

Related: #588, #580, #584, #249, #419, #549, #550.

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