Dense graph limits and graphons

The declarations the status of Tau Ceti's roadmap names as Tau Ceti has them at commit ace60277.

TheoremThe Lovász–Szegedy characterization of homomorphism densities#

A graph parameter is the homomorphism density of a graphon on an atomless standard Borel carrier (Ω, μ), such as the unit interval, if and only if it is isomorphism invariant, multiplicative, normalized and reflection positive.

TauCeti.DenseGraphLimits.lovasz_szegedy_representability.{u_1} {Ω : Type u_1} [MeasurableSpace Ω]
  [StandardBorelSpace Ω] (μ : MeasureTheory.Measure Ω) [MeasureTheory.IsProbabilityMeasure μ]
  [MeasureTheory.NullSingletonClass μ] (f : TauCeti.DenseGraphLimits.GraphParam) :
  (∃ W,
      ∀ (n : ℕ) (F : SimpleGraph (Fin n)) [inst : DecidableRel F.Adj],
        f n F = TauCeti.DenseGraphLimits.homDensity F W) ↔
    TauCeti.DenseGraphLimits.IsIsoInvariant f ∧
      TauCeti.DenseGraphLimits.IsMultiplicative f ∧
        TauCeti.DenseGraphLimits.IsNormalized f ∧ TauCeti.DenseGraphLimits.IsReflectionPositive f
Uses 4

TheoremEvery exchangeable law on infinite graphs is a graphon mixture, for exactly one mixing measure#

The integral form of the Diaconis–Janson correspondence: the law is the bind of a unique probability measure on graphon space against the joint sampling laws.

TauCeti.DenseGraphLimits.InfiniteExchangeableGraphLaw.existsUnique_bind_infiniteSampleLawOnSpace
  (L : TauCeti.DenseGraphLimits.InfiniteExchangeableGraphLaw) :
  ∃! P, (↑P).bind TauCeti.DenseGraphLimits.infiniteSampleLawOnSpace = L.law
Uses 3

TheoremDissociated relational laws of graphs are graphon sampling laws#

An exchangeable relational law of the language of graphs whose marginals are concentrated on simple graphs is dissociated exactly when it is the relational law of the sampling law of a graphon, which may be taken on any atomless standard Borel carrier (Ω, μ), such as the unit interval.

TauCeti.DenseGraphLimits.isDissociated_iff_exists_toRelationalLaw_sampleExchangeableLaw.{u_1}
  {Ω : Type u_1} [MeasurableSpace Ω] (μ : MeasureTheory.Measure Ω)
  [MeasureTheory.IsProbabilityMeasure μ] [StandardBorelSpace Ω] [MeasureTheory.NullSingletonClass μ]
  {ν : TauCeti.Probability.ExchangeableRelationalLaw FirstOrder.Language.graph}
  (hν :
    ∀ (n : ℕ),
      ∀ᵐ (c : TauCeti.RelationalConfiguration FirstOrder.Language.graph (Fin n)) ∂ν.law n,
        c.IsSimpleGraph) :
  ν.IsDissociated ↔ ∃ W, ν = (TauCeti.DenseGraphLimits.sampleExchangeableLaw W).toRelationalLaw
Uses 5

TheoremCut-distance convergence is convergence of all homomorphism densities#

Cut-distance convergence is convergence of all homomorphism densities, for graphons on arbitrary, possibly different, probability carriers, indexed by any type and taken along any filter: δ□(Wᵢ, W) → 0 if and only if t(F, Wᵢ) → t(F, W) for every finite simple graph F. Sequences are the case of atTop on ℕ.

TauCeti.DenseGraphLimits.tendsto_cutDist_iff_forall_homDensity_tendsto.{u_1, u_3, u_4}
  {Ω' : Type u_1} [MeasurableSpace Ω'] {μ' : MeasureTheory.Measure Ω'}
  [MeasureTheory.IsProbabilityMeasure μ'] {ι : Type u_3} {l : Filter ι} {Ωι : ι → Type u_4}
  [(i : ι) → MeasurableSpace (Ωι i)] {μι : (i : ι) → MeasureTheory.Measure (Ωι i)}
  [∀ (i : ι), MeasureTheory.IsProbabilityMeasure (μι i)]
  (Ws : (i : ι) → TauCeti.DenseGraphLimits.Graphon (Ωι i) (μι i))
  (W : TauCeti.DenseGraphLimits.Graphon Ω' μ') :
  Filter.Tendsto (fun i => TauCeti.DenseGraphLimits.cutDist (Ws i) W) l (nhds 0) ↔
    ∀ (n : ℕ) (F : SimpleGraph (Fin n)) [inst : DecidableRel F.Adj],
      Filter.Tendsto (fun i => TauCeti.DenseGraphLimits.homDensity F (Ws i)) l
        (nhds (TauCeti.DenseGraphLimits.homDensity F W))
Uses 4 · Used by 1

TheoremEvery convergent graph sequence has a limit graphon#

Every convergent graph sequence has a limit graphon (Lovász--Szegedy), on every atomless standard Borel carrier (Ω, μ), such as the unit interval. A sequence of finite graphs on nonempty vertex sets converges in the cut distance of step graphons to some graphon on (Ω, μ) if and only if every finite homomorphism density t(F, Gₙ) is a Cauchy, hence convergent, sequence.

TauCeti.DenseGraphLimits.exists_graphon_tendsto_cutDist_finiteGraphGraphon_iff_forall_homDensityFin_cauchySeq.{u_1}
  {Ω : Type u_1} [MeasurableSpace Ω] (μ : MeasureTheory.Measure Ω)
  [MeasureTheory.IsProbabilityMeasure μ] {m : ℕ → ℕ} [StandardBorelSpace Ω]
  [MeasureTheory.NullSingletonClass μ] (hm : ∀ (n : ℕ), 0 < m n)
  (G : (n : ℕ) → SimpleGraph (Fin (m n))) :
  (∃ W,
      Filter.Tendsto
        (fun n =>
          TauCeti.DenseGraphLimits.cutDist (TauCeti.DenseGraphLimits.finiteGraphGraphon (G n)) W)
        Filter.atTop (nhds 0)) ↔
    ∀ (n : ℕ) (F : SimpleGraph (Fin n)) [DecidableRel F.Adj],
      CauchySeq fun k => TauCeti.DenseGraphLimits.homDensityFin F (G k)
Uses 5

TheoremLovász--Szegedy compactness over atomless standard Borel carriers#

The cut-distance quotient of graphons on a standard Borel space with an atomless probability measure is a compact metric space, being isometric to GraphonSpaceI.

TauCeti.DenseGraphLimits.GraphonSpace.instCompactSpace.{u_1} {Ω : Type u_1} [MeasurableSpace Ω]
  [StandardBorelSpace Ω] {μ : MeasureTheory.Measure Ω} [MeasureTheory.IsProbabilityMeasure μ]
  [MeasureTheory.NullSingletonClass μ] : CompactSpace (TauCeti.DenseGraphLimits.GraphonSpace Ω μ)
Uses 4

TheoremFrieze--Kannan weak regularity#

Every graphon has a measurable block-average step graphon within ε in cut norm, on a partition with at most 4 ^ ⌈1 / ε²⌉ parts.

TauCeti.DenseGraphLimits.weak_regularity_frieze_kannan.{u_1} {Ω : Type u_1} [MeasurableSpace Ω]
  (μ : MeasureTheory.Measure Ω) [MeasureTheory.IsProbabilityMeasure μ]
  (W : TauCeti.DenseGraphLimits.Graphon Ω μ) {ε : ℝ} (hε : 0 < ε) :
  ∃ P,
    ∃ (hP : ∀ p ∈ P.parts, MeasurableSet p),
      P.parts.card ≤ 4 ^ ⌈1 / ε ^ 2⌉₊ ∧
        TauCeti.DenseGraphLimits.cutNorm μ
            (W.toSymmKernel - (TauCeti.DenseGraphLimits.stepGraphonAvg P hP W).toSymmKernel) ≤
          ε
Used by 7

DefinitionTauCeti.DenseGraphLimits.cutDist#

The cut distance of two graphons: the infimum, over couplings of their carriers, of the cut norm of the overlaid difference.

The two graphons may live on different probability spaces, and no standard Borel or atomless hypothesis is imposed on either.

TauCeti.DenseGraphLimits.cutDist.{u_1, u_2} {Ω₁ : Type u_1} {Ω₂ : Type u_2} [MeasurableSpace Ω₁]
  [MeasurableSpace Ω₂] {μ₁ : MeasureTheory.Measure Ω₁} {μ₂ : MeasureTheory.Measure Ω₂}
  [MeasureTheory.IsProbabilityMeasure μ₁] [MeasureTheory.IsProbabilityMeasure μ₂]
  (U : TauCeti.DenseGraphLimits.Graphon Ω₁ μ₁) (W : TauCeti.DenseGraphLimits.Graphon Ω₂ μ₂) : ℝ
Used by 8

TheoremTauCeti.DenseGraphLimits.cutDist_triangle#

The coupling-primary graphon cut distance satisfies the triangle inequality on arbitrary probability carriers.

TauCeti.DenseGraphLimits.cutDist_triangle.{u_1, u_2, u_3} {Ω₁ : Type u_1} {Ω₂ : Type u_2}
  {Ω₃ : Type u_3} [MeasurableSpace Ω₁] [MeasurableSpace Ω₂] [MeasurableSpace Ω₃]
  {μ₁ : MeasureTheory.Measure Ω₁} {μ₂ : MeasureTheory.Measure Ω₂} {μ₃ : MeasureTheory.Measure Ω₃}
  [MeasureTheory.IsProbabilityMeasure μ₁] [MeasureTheory.IsProbabilityMeasure μ₂]
  [MeasureTheory.IsProbabilityMeasure μ₃] (U : TauCeti.DenseGraphLimits.Graphon Ω₁ μ₁)
  (W : TauCeti.DenseGraphLimits.Graphon Ω₂ μ₂) (X : TauCeti.DenseGraphLimits.Graphon Ω₃ μ₃) :
  TauCeti.DenseGraphLimits.cutDist U X ≤
    TauCeti.DenseGraphLimits.cutDist U W + TauCeti.DenseGraphLimits.cutDist W X
Uses 2 · Used by 7

DefinitionTauCeti.DenseGraphLimits.Graphon.unitIntervalRepr#

A graphon on the unit interval at cut distance zero from W, for W on an arbitrary probability carrier.

The representative is an arbitrary choice; cutDist_unitIntervalRepr_left and cutDist_unitIntervalRepr_right show that no cut distance depends on it.

TauCeti.DenseGraphLimits.Graphon.unitIntervalRepr.{u_1} {Ω : Type u_1} [MeasurableSpace Ω]
  {μ : MeasureTheory.Measure Ω} [MeasureTheory.IsProbabilityMeasure μ]
  (W : TauCeti.DenseGraphLimits.Graphon Ω μ) :
  TauCeti.DenseGraphLimits.Graphon (↑unitInterval) MeasureTheory.volume
Uses 2 · Used by 5

StructureTauCeti.Probability.ExchangeableRelationalLaw#

An exchangeable random structure of L, presented by its consistent finite marginals: a probability law on the configurations on Fin k for every k, consistent under restriction along every injection of vertices.

TauCeti.Probability.ExchangeableRelationalLaw.{u_1, u_2} (L : FirstOrder.Language) : Type u_2
Used by 1

DefinitionExchangeable laws on infinite graphs are the exchangeable relational laws of the language of graphs on ℕ concentrated on simple graphs, that is, on symmetric irreflexive configurations#

The inverse pulls the law back along the encoding.

TauCeti.DenseGraphLimits.InfiniteExchangeableGraphLaw.relationalLawEquiv :
  TauCeti.DenseGraphLimits.InfiniteExchangeableGraphLaw ≃
    { μ //
      ∀ᵐ (c : TauCeti.RelationalConfiguration FirstOrder.Language.graph ℕ) ∂μ.law, c.IsSimpleGraph }

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