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LeanPool.RareSubtreePatterns.Patterns.CutGraftBound

The cut-and-graft bound (Lemma lem:cut_graft) #

Source lines 2512–2546 (statement) and 2557–2621 (proof); inventory L6.1, P18.

Let 𝓔 be an event on finite plane trees, (𝓠_m)_{m ∈ I} a finite family of events with 𝐏(𝒯 ∈ 𝓠_m) > 0, 𝓑 βŠ† π’œ_β„“ and Ο„ : 𝓑 β†’ I such that (a) A[S'] ∈ 𝓔 for every A ∈ 𝓑 and S' ∈ 𝓠_{Ο„(A)}, and (b) whenever |T| β‰₯ β„“+1, T ∈ 𝓔 and T_{u_{β„“+1}(T)} ∈ 𝓔, one has Cut_β„“(T) ∈ 𝓑 and T_{u_{β„“+1}(T)} ∈ 𝓠_{Ο„(Cut_β„“(T))}. Then 𝐏(|𝒯| β‰₯ β„“+1, 𝒯 ∈ 𝓔, 𝒯_{u_{β„“+1}(𝒯)} ∈ 𝓔) ≀ 𝐏(𝒯 ∈ 𝓔) max_{m ∈ I} 𝐏(𝒯 ∈ 𝓔 | 𝒯 ∈ 𝓠_m).

The proof is the paper's: by the cut-and-graft factorization 𝐏(𝒯 = A[S]) = w(A) 𝐏(𝒯 = S), the left-hand side is at most βˆ‘_{A ∈ 𝓑} w(A) 𝐏(𝓔 ∩ 𝓠_{Ο„(A)}), while uniqueness of the decomposition and (a) give βˆ‘_{A ∈ 𝓑} w(A) 𝐏(𝓠_{Ο„(A)}) ≀ 𝐏(𝓔). (The paper groups the sum by m through W_m = βˆ‘_{Ο„(A) = m} w(A); we sum over A directly.)

The inequality holds for every offspring law ΞΌ: criticality and ΞΌ_1 β‰  1 (which make bienayme ΞΌ a probability measure) are not needed, so they are not assumed.

theorem PoissonDeclumping.PlaneTree.cut_graft_bound_aux (ΞΌ : PMF β„•) (β„“ : β„•) (E : Set PlaneTree) {I : Type u_1} (Q : I β†’ Set PlaneTree) (R : Set MarkedTree) (hR : R βŠ† cutFamily β„“) (Ο„ : MarkedTree β†’ I) (ha : βˆ€ A ∈ R, βˆ€ S ∈ Q (Ο„ A), A.graft S ∈ E) (hb : βˆ€ (T : PlaneTree), β„“ + 1 ≀ T.vertexCount β†’ T ∈ E β†’ T.fringeAt β„“ ∈ E β†’ cut β„“ T ∈ R ∧ T.fringeAt β„“ ∈ Q (Ο„ (cut β„“ T))) (c : ENNReal) (hc : βˆ€ (m : I), (bienayme ΞΌ) (E ∩ Q m) ≀ c * (bienayme ΞΌ) (Q m)) :
(bienayme ΞΌ) {T : PlaneTree | β„“ + 1 ≀ T.vertexCount ∧ T ∈ E ∧ T.fringeAt β„“ ∈ E} ≀ c * (bienayme ΞΌ) E

Core estimate of Lemma lem:cut_graft (total selector Ο„, arbitrary index type, and any constant c with 𝐏(𝓔 ∩ 𝓠_m) ≀ c 𝐏(𝓠_m) for all m).

The event {|T| β‰₯ β„“+1, T ∈ 𝓔, T_{u_{β„“+1}(T)} ∈ 𝓔} written with fringeTrees[β„“]? (as in PoissonDeclumping.pairProb) or with fringeAt.

theorem PoissonDeclumping.PlaneTree.lem_cut_graft (ΞΌ : PMF β„•) (β„“ : β„•) (E : Set PlaneTree) {I : Type u_1} [Fintype I] [Nonempty I] (Q : I β†’ Set PlaneTree) (hQ : βˆ€ (m : I), 0 < (bienayme ΞΌ) (Q m)) (R : Set MarkedTree) (hR : R βŠ† cutFamily β„“) (Ο„ : ↑R β†’ I) (ha : βˆ€ (A : ↑R), βˆ€ S ∈ Q (Ο„ A), (↑A).graft S ∈ E) (hb : βˆ€ (T : PlaneTree), β„“ + 1 ≀ T.vertexCount β†’ T ∈ E β†’ T.fringeAt β„“ ∈ E β†’ βˆƒ (hA : cut β„“ T ∈ R), T.fringeAt β„“ ∈ Q (Ο„ ⟨cut β„“ T, hA⟩)) :
(bienayme ΞΌ) {T : PlaneTree | β„“ + 1 ≀ T.vertexCount ∧ T ∈ E ∧ βˆƒ U ∈ T.fringeTrees[β„“]?, U ∈ E} ≀ (bienayme ΞΌ) E * Finset.univ.sup' β‹― fun (m : I) => (bienayme ΞΌ)[E | Q m]

Lemma lem:cut_graft (cut-and-graft bound, source lines 2512–2546). Here β„“ is any natural number (the paper fixes β„“ β‰₯ 1), fringeAt T β„“ = T.fringeTrees[β„“] is T_{u_{β„“+1}(T)}, π’œ_β„“ = cutFamily β„“, A[S] = A.graft S, and the index type I is finite and nonempty. The bound holds for the BienaymΓ© measure of any offspring law.

theorem PoissonDeclumping.PlaneTree.lem_cut_graft_real (ΞΌ : PMF β„•) (β„“ : β„•) (E : Set PlaneTree) {I : Type u_1} [Fintype I] [Nonempty I] (Q : I β†’ Set PlaneTree) (hQ : βˆ€ (m : I), 0 < (bienayme ΞΌ) (Q m)) (R : Set MarkedTree) (hR : R βŠ† cutFamily β„“) (Ο„ : ↑R β†’ I) (ha : βˆ€ (A : ↑R), βˆ€ S ∈ Q (Ο„ A), (↑A).graft S ∈ E) (hb : βˆ€ (T : PlaneTree), β„“ + 1 ≀ T.vertexCount β†’ T ∈ E β†’ T.fringeAt β„“ ∈ E β†’ βˆƒ (hA : cut β„“ T ∈ R), T.fringeAt β„“ ∈ Q (Ο„ ⟨cut β„“ T, hA⟩)) :
(bienayme ΞΌ).real {T : PlaneTree | β„“ + 1 ≀ T.vertexCount ∧ T ∈ E ∧ βˆƒ U ∈ T.fringeTrees[β„“]?, U ∈ E} ≀ (bienayme ΞΌ).real E * Finset.univ.sup' β‹― fun (m : I) => (bienayme ΞΌ)[|Q m].real E

Lemma lem:cut_graft, real-valued form: the left-hand side is the paper's A_n(β„“)-type probability 𝐏(|𝒯| β‰₯ β„“+1, 𝒯 ∈ 𝓔, 𝒯_{u_{β„“+1}(𝒯)} ∈ 𝓔).