openAI-math-dataset / lean /OAI /Probability /InvariantIsing /Arrays /NSpinTensorAncestorInput.lean
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import OAI.Probability.InvariantIsing.Arrays.NSpinTensorRetained
import OAI.Probability.IsingPerceptron.NormalizedRestrictionPi
import OAI.Probability.IsingPerceptron.SamplingIndependent
namespace OAI
/-!
The finite Ising tensor application of the conditional marked-path law.
The conditional marked-path law is the finite two-path specialization of
Panchenko--Talagrand, C. R. Acad. Sci. Paris I 345 (2007), 653--656,
Section 3, Lemma 3.1, equation (8), p.655, and Corollary 3.2, equation (9),
p.656. The mark spaces are complete separable metric spaces with their Borel
sigma algebras; ancestor conditional distributions may be arbitrary and
the measurable terminal need only satisfy `E exp X < infinity`.
The Gaussian-vector terminal satisfies this exponential integrability
hypothesis.
The law describes the joint branching and marks, including their
conditional ancestor distributions.
Averaging the fixed-root law gives the random-root law.
Forest edge `i` has shared mark exactly when `i < commonDepth`.
-/
noncomputable section
open MeasureTheory ProbabilityTheory IsingPerceptron
open scoped BigOperators NNReal
namespace InvariantIsing
/-- The published marking theorem's exponential integrability hypothesis
holds for the actual finite Ising terminal on a finite Gaussian path. -/
theorem tensorFinitePath_exp_integrable {N m k : ℕ} (hN : 0 < N)
(eig : Fin N → ℝ) (U : Rotation N) (c : Fin N → ℝ)
(I : Fin m → Finset (Fin N)) (degree : Fin k → Fin m → ℕ) (amplitude : Fin k → ℝ)
(n : ℕ) (v : ℕ → SpinTensorIndex I degree → ℝ≥0)
(z : SpinTensorIndex I degree → ℝ) :
Integrable (fun w : Fin n → SpinTensorIndex I degree → ℝ =>
Real.exp (spinTensorTerminal eig U c I degree amplitude (z + ∑ i, w i)))
(Measure.pi (fun i : Fin n =>
(tensorGaussianLaw I degree (v i) : Measure (SpinTensorIndex I degree → ℝ)))) := by
obtain ⟨C, L, _, hL, hbound⟩ := spinTensorTerminal_linearGrowth eig U c I degree amplitude
have hprod : Integrable (fun w : Fin n → SpinTensorIndex I degree → ℝ =>
∏ i, Real.exp (L * ‖w i‖))
(Measure.pi (fun i : Fin n =>
(tensorGaussianLaw I degree (v i) : Measure (SpinTensorIndex I degree → ℝ)))) :=
Integrable.fintype_prod (f := fun (i : Fin n) (a : SpinTensorIndex I degree → ℝ) =>
Real.exp (L * ‖a‖)) fun i => tensorGaussianLaw_moments hN I degree (v i) L
apply (hprod.const_mul (Real.exp (C + L * ‖z‖))).mono'
(((measurable_spinTensorTerminal eig U c I degree amplitude).comp
(measurable_const.add (Finset.measurable_sum _ fun i _ => measurable_pi_apply i))).exp.aestronglyMeasurable)
apply ae_of_all
intro w
rw [Real.norm_eq_abs, abs_of_pos (Real.exp_pos _), ← Real.exp_sum, ← Real.exp_add]
apply Real.exp_le_exp.mpr
calc
_ ≤ |spinTensorTerminal eig U c I degree amplitude (z + ∑ i, w i)| := le_abs_self _
_ ≤ C + L * ‖z + ∑ i, w i‖ := hbound _
_ ≤ C + L * (‖z‖ + ∑ i, ‖w i‖) := by
apply add_le_add_right (mul_le_mul_of_nonneg_left _ hL)
exact (norm_add_le _ _).trans (add_le_add_right (norm_sum_le _ _) _)
_ = C + L * ‖z‖ + ∑ i, L * ‖w i‖ := by rw [mul_add, Finset.mul_sum]; ring
private lemma tensor_abs_integral_bound {A : Type*} [MeasurableSpace A]
{μ : Measure A} [IsProbabilityMeasure μ] (f : A → ℝ) {C : ℝ}
(hf : ∀ a, |f a| ≤ C) : |∫ a, f a ∂μ| ≤ C := by
have hh : ∀ᵐ a ∂μ, ‖f a‖ ≤ C := ae_of_all _ fun a => by
simpa only [Real.norm_eq_abs] using hf a
simpa only [Real.norm_eq_abs, probReal_univ, mul_one] using
norm_integral_le_of_norm_le_const (μ := μ) (f := f) hh
/-- Iterated conditional expectation of two Gaussian increment paths. Before
their branching depth the two paths receive the same tilted increment;
afterwards their next increments are conditionally independent. -/
def tensorAncestorPairPathMean {N m k : ℕ}
(eig : Fin N → ℝ) (U : Rotation N) (c : Fin N → ℝ)
(I : Fin m → Finset (Fin N)) (degree : Fin k → Fin m → ℕ) (amplitude : Fin k → ℝ)
(n : ℕ) (b : ℕ → ℝ) (v : ℕ → SpinTensorIndex I degree → ℝ≥0) (d : ℕ) :
(q : ℕ) → ℕ → (SpinTensorIndex I degree → ℝ) → (SpinTensorIndex I degree → ℝ) →
((Fin q → (SpinTensorIndex I degree → ℝ) × (SpinTensorIndex I degree → ℝ)) → ℝ) → ℝ
| 0, _, _, _, F => F Fin.elim0
| q + 1, i, z₁, z₂, F =>
if i < d then
∫ a, tensorAncestorPairPathMean eig U c I degree amplitude n b v d q (i + 1)
(z₁ + a) (z₂ + a) (fun w => F (Fin.cons (a, a) w))
∂tensorAncestorMarkKernel eig U c I degree amplitude n b v i z₁
else
∫ a₁, ∫ a₂, tensorAncestorPairPathMean eig U c I degree amplitude n b v d q (i + 1)
(z₁ + a₁) (z₂ + a₂) (fun w => F (Fin.cons (a₁, a₂) w))
∂tensorAncestorMarkKernel eig U c I degree amplitude n b v i z₂
∂tensorAncestorMarkKernel eig U c I degree amplitude n b v i z₁
theorem tensorAncestorPairPathMean_abs_le {N m k : ℕ} (hN : 0 < N)
(eig : Fin N → ℝ) (U : Rotation N) (c : Fin N → ℝ)
(I : Fin m → Finset (Fin N)) (degree : Fin k → Fin m → ℕ) (amplitude : Fin k → ℝ)
(n : ℕ) (b : ℕ → ℝ) (v : ℕ → SpinTensorIndex I degree → ℝ≥0)
(hb : CascadeExponents n b) (d q i : ℕ)
(z₁ z₂ : SpinTensorIndex I degree → ℝ)
(F : (Fin q → (SpinTensorIndex I degree → ℝ) × (SpinTensorIndex I degree → ℝ)) → ℝ)
{C : ℝ} (hF : ∀ w, |F w| ≤ C) :
|tensorAncestorPairPathMean eig U c I degree amplitude n b v d q i z₁ z₂ F| ≤ C := by
induction q generalizing i z₁ z₂ with
| zero => exact hF _
| succ q ih =>
have := tensorAncestorMarkKernel_markov hN eig U c I degree amplitude n b v hb i
dsimp only [tensorAncestorPairPathMean]
split_ifs
· apply tensor_abs_integral_bound
intro a
exact ih (i + 1) (z₁ + a) (z₂ + a)
(fun w => F (Fin.cons (a, a) w)) (fun w => hF _)
· have hinner (a₁ : SpinTensorIndex I degree → ℝ) :
|∫ a₂, tensorAncestorPairPathMean eig U c I degree amplitude n b v d q (i + 1)
(z₁ + a₁) (z₂ + a₂) (fun w => F (Fin.cons (a₁, a₂) w))
∂tensorAncestorMarkKernel eig U c I degree amplitude n b v i z₂| ≤ C := by
apply tensor_abs_integral_bound
intro a₂
exact ih (i + 1) (z₁ + a₁) (z₂ + a₂)
(fun w => F (Fin.cons (a₁, a₂) w)) (fun w => hF _)
exact tensor_abs_integral_bound _ hinner
/-- The actual tilted two-leaf Gaussian path expectation, with the spin
residual integrated in the finite Ising terminal. -/
def tensorTiltedPairPathMean {N m k : ℕ}
(eig : Fin N → ℝ) (U : Rotation N) (c : Fin N → ℝ)
(I : Fin m → Finset (Fin N)) (degree : Fin k → Fin m → ℕ) (amplitude : Fin k → ℝ)
(n : ℕ) (b : ℕ → ℝ) (v : ℕ → SpinTensorIndex I degree → ℝ≥0)
(z : SpinTensorIndex I degree → ℝ)
(Φ : ℕ × (Fin n → (SpinTensorIndex I degree → ℝ) × (SpinTensorIndex I degree → ℝ)) → ℝ) : ℝ :=
∫ p : TensorCoordinateData I degree n,
referenceReplicaMean (labeledLeafLaw n p.1)
(fun α => spinTensorTerminal eig U c I degree amplitude
(labeledEnergy n (markForestOfCoords (SpinTensorIndex I degree → ℝ) n p.2) α z))
(fun σ : Fin 2 → LabeledLeaf n => Φ
(labeledCommonDepth n (σ 0) (σ 1),
fun i => (p.2 (edgeAt n (σ 0) i), p.2 (edgeAt n (σ 1) i))))
∂tensorCoordinateLaw I degree n b v
/-- The exact finite tensor specialization of the published joint marked
path law. The unperturbed cascade supplies the shared-prefix depth and
the normalized ancestor kernels supply the conditional marks. -/
def TensorAncestorPairLaw {N m k : ℕ}
(eig : Fin N → ℝ) (U : Rotation N) (c : Fin N → ℝ)
(I : Fin m → Finset (Fin N)) (degree : Fin k → Fin m → ℕ) (amplitude : Fin k → ℝ)
(n : ℕ) (b : ℕ → ℝ) (v : ℕ → SpinTensorIndex I degree → ℝ≥0) : Prop :=
∀ z : SpinTensorIndex I degree → ℝ,
∀ Φ : ℕ × (Fin n → (SpinTensorIndex I degree → ℝ) × (SpinTensorIndex I degree → ℝ)) → ℝ,
Measurable Φ → (∃ C : ℝ, ∀ p, |Φ p| ≤ C) →
tensorTiltedPairPathMean eig U c I degree amplitude n b v z Φ =
∫ α : ℕ → LabeledLeaf n,
tensorAncestorPairPathMean eig U c I degree amplitude n b v
(labeledCommonDepth n (α 0) (α 1)) n 0 z z
(fun w => Φ (labeledCommonDepth n (α 0) (α 1), w))
∂cascadeReplicaLaw n b
/-- Conditional two-path marking law for finite hierarchical tensor fields. -/
def PanchenkoTalagrandTensorPairInput : Prop :=
∀ N m k : ℕ, 0 < N →
∀ (eig : Fin N → ℝ) (U : Rotation N) (c : Fin N → ℝ)
(I : Fin m → Finset (Fin N)) (degree : Fin k → Fin m → ℕ) (amplitude : Fin k → ℝ)
(n : ℕ) (b : ℕ → ℝ) (v : ℕ → SpinTensorIndex I degree → ℝ≥0),
CascadeExponents n b → TensorAncestorPairLaw eig U c I degree amplitude n b v
/-- The independent root Gaussian is averaged after the fixed-root path
identity. Root level zero and forest levels one through `n` agree with
the flat tensor coefficient convention. -/
theorem tensorRootedPairPath_identity (hpub : PanchenkoTalagrandTensorPairInput)
{N m k : ℕ} (hN : 0 < N)
(eig : Fin N → ℝ) (U : Rotation N) (c : Fin N → ℝ)
(I : Fin m → Finset (Fin N)) (degree : Fin k → Fin m → ℕ) (amplitude : Fin k → ℝ)
(n : ℕ) (b : ℕ → ℝ) (v : ℕ → SpinTensorIndex I degree → ℝ≥0)
(hb : CascadeExponents n b)
(Φ : (SpinTensorIndex I degree → ℝ) ×
(ℕ × (Fin n → (SpinTensorIndex I degree → ℝ) × (SpinTensorIndex I degree → ℝ))) → ℝ)
(hΦ : Measurable Φ) (hΦb : ∃ C : ℝ, ∀ p, |Φ p| ≤ C) :
(∫ z, tensorTiltedPairPathMean eig U c I degree amplitude n b (fun i => v (i + 1)) z
(fun p => Φ (z, p))
∂(tensorGaussianLaw I degree (v 0) : Measure (SpinTensorIndex I degree → ℝ))) =
∫ z, ∫ α : ℕ → LabeledLeaf n,
tensorAncestorPairPathMean eig U c I degree amplitude n b (fun i => v (i + 1))
(labeledCommonDepth n (α 0) (α 1)) n 0 z z
(fun w => Φ (z, labeledCommonDepth n (α 0) (α 1), w))
∂cascadeReplicaLaw n b
∂(tensorGaussianLaw I degree (v 0) : Measure (SpinTensorIndex I degree → ℝ)) := by
apply integral_congr_ae
apply ae_of_all
intro z
apply hpub N m k hN eig U c I degree amplitude n b (fun i => v (i + 1)) hb z
· exact hΦ.comp (measurable_const.prodMk measurable_id)
· obtain ⟨C, hC⟩ := hΦb
exact ⟨C, fun p => hC (z, p)⟩
end InvariantIsing
end
end OAI