The joint representation interface (R4 converse piece 3, #107) #
The specification a rank-n representation must satisfy. Interface only: no existence theorem
is proved or claimed here, at any rank.
Why the primitive is a coupling #
The previous design took a map RankLatentSpace n → LowerFactorSpace n and derived the joint
law as a relatively independent joining over the intrinsic factor. That derivation is what failed:
it makes the latents conditionally independent of the structure given the intrinsic factor, so
when that factor is trivial the latents are independent of the array. Austin's random complete
bipartite graph X_{uv} = z_u ⊕ z_v (arXiv:0801.1698, §3.6) has trivial rank-2 factor and hidden
colours that are correlated with the array while individually unrecoverable from it, so no such
joining can represent it.
The primitive here is therefore the coupling P itself. The decoder direction is unchanged —
structure recovered from latents — which was never the problem.
Local, and rank-truncated #
Two further constraints, both load-bearing:
- Recovery is local. Global recovery of the whole lower factor from the whole latent cube
would let a decoder read unrelated coordinates elsewhere in the universe, and would not descend
to the eventual label-free kernels. Each block at
Ais recovered fromlocalLatents A. - Screening is rank-truncated. Higher-rank coordinates containing
Alegitimately share the latents atA, so screening a block from all higher ranks would be false. The rank-nblock atAis screened from the other blocks of rank at mostn.
Staging: U_A is not in scope at rank n #
For A.card = n, the coordinate U_A is absent from RankLatentSpace S n outright, since
RankLatentIndex S n ranges over supports of cardinality strictly below n
(rankLatentIndex_ne_of_card_eq). So screening may put the entire RankLatentSpace S n on the
far side without contradiction, and B ⊆ A within RankLatentIndex n automatically means
B ⊊ A. Kallenberg's Lemma 7.24 is staged the same way — its coupled array is truncated below
the working dimension, and the fresh uniforms enter only at the successor step, here supplied by
the RankLatentSpace (n+1) ≃ᵐ RankLatentSpace n × (RankSupport S n → ℝ) split.
Acceptance tests #
Two examples, each blind to the other's failure mode; a specification in this family needs both.
- Bipartite colours
X_{uv} = z_u ⊕ z_v— correlation: hidden lower-rank latents may be correlated with the array while individually unrecoverable. This refutes factor-law coding, and passes here withscreeningnon-vacuous, since the edge is a deterministic function of the two colours. - I.i.d. edges
X_{uv} = U_{uv}— staging: the top-rank latent is absent during screening and introduced only at randomization. The bipartite example cannot detect a rank off-by-one, because its edges use no rank-2 latent at all.
Local latents #
The latent coordinates visible at A: supports contained in A. Within RankLatentIndex n
this automatically means proper subsets when A.card = n.
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The local latent space at A.
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- RelSignature.LocalLatentSpace A n = (RelSignature.LocalLatentIndex A n → ℝ)
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Restriction of the latent array to the coordinates visible at A.
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The staging lemma: at rank n the latent array carries no coordinate at a support of
cardinality n. This is why screening may place the whole of RankLatentSpace S n opposite the
rank-n block, and why B ⊆ A needs no separate properness side condition.
Consequently a visible support at a rank-n set is a proper subset of it.
Blocks of raw relation coordinates #
Raw relation coordinates whose tagged support is exactly A. Raw coordinates, not basis
events: the eventual descent to label-free kernels is indexed by these.
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The rank-A block of the structure.
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Read the block at A off a structure.
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The rank-truncated remainder #
Coordinates of rank at most n other than those at A. The truncation is essential:
coordinates of rank above n that contain A legitimately share A's latents, so screening
against them would be false.
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The remaining rank-≤ n structure.
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- RelSignature.RestSpace n A = (RelSignature.RestIndex n A → Bool)
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The rank-truncated remainder observation: the other blocks of rank at most n, together
with the whole latent array — which at rank n contains no coordinate at A.
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The specification #
A joint rank-n representation. The primitive is the coupling P, not a coding map.
Deliberately independent of CoherentBasis: the specification mentions only the law, the raw
relation coordinates, and the latent array. The refuted design was phrased against the basis and
its factor maps, and that dependence is part of what led it to a factor-law primitive.
No existence theorem accompanies this definition, at any rank. Whether a non-trivial
RankRepresentation n exists is the actual content of the converse, and is exactly what the
refuted RankCoding design mistook for a bookkeeping step. Constructing one is expected to need
a stationary extension to a fresh auxiliary vertex pool, transfer along that extension, and the
polling clusters of Austin's Proposition 3.12.
- P : MeasureTheory.Measure (S.RelStructure S.Vinfinite × S.RankLatentSpace n)
The coupling of the structure with the rank-
nlatents. - isProbabilityMeasure_P : MeasureTheory.IsProbabilityMeasure self.P
It is a probability measure.
Its structure marginal is the law.
Its latent marginal is the i.i.d. source.
- invariant (σ : ↥S.FinSuppPerm) : MeasureTheory.Measure.map (Prod.map (RelStructure.relabel ↑σ) ⇑(rankLatentRelabel σ n)) self.P = self.P
Joint relabeling invariance: a relabeling acts on both coordinates at once.
- lower_recovers (A : Finset ((s : S.Srt) × S.Vinfinite s)) : A.card < n → ∃ (g : LocalLatentSpace A n → BlockSpace A), Measurable g ∧ blockMap A ∘ Prod.fst =ᵐ[self.P] g ∘ localLatents A n ∘ Prod.snd
Local recovery: each block below rank
nis a function of the latents visible at its own support — not of the latent array at large. - screening (A : Finset ((s : S.Srt) × S.Vinfinite s)) : A.card = n → ProbabilityTheory.CondIndepFun (MeasurableSpace.comap (localLatents A n ∘ Prod.snd) inferInstance) ⋯ (blockMap A ∘ Prod.fst) (restObservation n A) self.P
Local screening-off, rank-truncated: the rank-
nblock atAis conditionally independent of the other rank-≤ nblocks and the latent array, given the latents visible atA. Kallenberg'sX̃_A ⊥⊥_{ξ̂_A} (X ∖ X̃_A, ξ)at the working rank.