File size: 12,938 Bytes
b317718
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
import OAI.Probability.InvariantIsing.Arrays.NSpinTensorGaussianLaw
import OAI.Probability.InvariantIsing.Gaussian.BaseGaussianVariance
import OAI.Probability.IsingPerceptron.NamespaceSplit

namespace OAI

/-! The flat Gaussian spin/leaf pressure has the actual cascade mean. -/

noncomputable section

open MeasureTheory ProbabilityTheory IsingPerceptron
open scoped BigOperators NNReal

namespace InvariantIsing

def tensorFlatLog {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) (v : ℕ → SpinTensorIndex I degree → ℝ≥0) (p : LabeledTree n × (ℕ → ℝ)) : ℝ :=
  Real.log (∫ x : Spin N × LabeledLeaf n, Real.exp (rotatedEnergy eig U x.1 + fieldEnergy c x.1 +
    cylinderField (tensorLeafCoefficients U I degree amplitude n (fun i => v i) x) p.2)
    ∂labeledSpinReference n (uniformSpinPrior N : Measure (Spin N)) p.1)

lemma measurable_tensorFlatLog {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) (v : ℕ → SpinTensorIndex I degree → ℝ≥0) :
    Measurable (tensorFlatLog eig U c I degree amplitude n v) := by
  have hE : Measurable (fun p : (LabeledTree n × (ℕ → ℝ)) × (Spin N × LabeledLeaf n) =>
      rotatedEnergy eig U p.2.1 + fieldEnergy c p.2.1 +
        cylinderField (tensorLeafCoefficients U I degree amplitude n (fun i => v i) p.2) p.1.2) := by
    apply measurable_from_prod_countable_left
    intro x
    have hc : Measurable (fun _ : LabeledTree n × (ℕ → ℝ) =>
        rotatedEnergy eig U x.1 + fieldEnergy c x.1) := measurable_const
    exact hc.add ((measurable_cylinderField
      (tensorLeafCoefficients U I degree amplitude n (fun i => v i) x)).comp measurable_snd)
  have : ∀ p : LabeledTree n × (ℕ → ℝ), IsProbabilityMeasure
      ((labeledSpinReference n (uniformSpinPrior N : Measure (Spin N)) ∘ Prod.fst) p) :=
    fun p => by
      change IsProbabilityMeasure (labeledSpinReference n (uniformSpinPrior N : Measure (Spin N)) p.1)
      infer_instance
  exact (measurable_random_referencePartition
    ((measurable_labeledSpinReference_general n (uniformSpinPrior N : Measure (Spin N))).comp measurable_fst) hE).log

private lemma tensorLeafCoefficients_finite_bound {N m k : ℕ} (U : Rotation N)
    (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) :
    ∃ B : ℝ, ∀ x : Spin N × LabeledLeaf n,
      (tensorLeafCoefficients U I degree amplitude n (fun i => v i) x).sum (fun _ c => c ^ 2) ≤ B := by
  classical
  let Q : Spin N → ℝ := fun σ => ∑ i : Fin (n + 1), ∑ j : SpinTensorIndex I degree,
    (v i j : ℝ) * spinTensorFeature U I degree amplitude σ j ^ 2
  refine ⟨∑ σ, Q σ, fun x => ?_⟩
  rw [← cylinderCross_self, tensorLeafCoefficients_cross]
  simp only [labeledCommonDepth_self,
    show ∀ i : Fin (n + 1), i.1 ≤ n from fun i => Nat.le_of_lt_succ i.isLt, ite_true]
  calc
    _ = Q x.1 := by
      apply Finset.sum_congr rfl
      intro i _
      apply Finset.sum_congr rfl
      intro j _
      ring
    _ ≤ ∑ σ, Q σ := Finset.single_le_sum (f := Q)
      (fun _ _ => Finset.sum_nonneg fun _ _ => Finset.sum_nonneg fun _ _ =>
        mul_nonneg (NNReal.coe_nonneg _) (sq_nonneg _)) (Finset.mem_univ x.1)

private lemma tensorFlat_base_exp_integrable {N : ℕ} (eig : Fin N → ℝ) (U : Rotation N)
    (c : Fin N → ℝ) (n : ℕ) (T : LabeledTree n) :
    Integrable (fun x : Spin N × LabeledLeaf n => Real.exp (rotatedEnergy eig U x.1 + fieldEnergy c x.1))
      (labeledSpinReference n (uniformSpinPrior N : Measure (Spin N)) T) :=
  (Integrable.of_finite : Integrable
    (fun σ : Spin N => Real.exp (rotatedEnergy eig U σ + fieldEnergy c σ))
    (uniformSpinPrior N : Measure (Spin N))).comp_fst (labeledLeafLaw n T)

private lemma tensorFlat_base_log {N : ℕ} (eig : Fin N → ℝ) (U : Rotation N)
    (c : Fin N → ℝ) (n : ℕ) (T : LabeledTree n) :
    Real.log (∫ x : Spin N × LabeledLeaf n, Real.exp (rotatedEnergy eig U x.1 + fieldEnergy c x.1)
      ∂labeledSpinReference n (uniformSpinPrior N : Measure (Spin N)) T) =
      logPartition (fun σ => rotatedEnergy eig U σ + fieldEnergy c σ) := by
  unfold labeledSpinReference
  change Real.log (∫ x : Spin N × LabeledLeaf n,
    (fun σ : Spin N => Real.exp (rotatedEnergy eig U σ + fieldEnergy c σ)) x.1
    ∂(uniformSpinPrior N : Measure (Spin N)).prod (labeledLeafLaw n T)) = _
  rw [integral_fun_fst (μ := (uniformSpinPrior N : Measure (Spin N)))
    (ν := labeledLeafLaw n T) (fun σ : Spin N => Real.exp (rotatedEnergy eig U σ + fieldEnergy c σ))]
  simp only [probReal_univ, one_smul]
  exact finiteLogIntegral_uniformSpinPrior _

private lemma random_cylinder_log_integrable {Ω X : Type*}
    [MeasurableSpace Ω] [MeasurableSpace X] [Countable X] [MeasurableSingletonClass X]
    {P : Measure Ω} [IsProbabilityMeasure P] {ν : Ω → Measure X}
    (hν : Measurable ν) [∀ ω, IsProbabilityMeasure (ν ω)]
    (H : X → ℝ) (hH : ∀ ω, Integrable (fun x => Real.exp (H x)) (ν ω))
    (C : ℝ) (hC : ∀ ω, Real.log (∫ x, Real.exp (H x) ∂ν ω) = C)
    (A : X → ℕ →₀ ℝ) {B : ℝ} (hA : ∀ x, (A x).sum (fun _ c => c ^ 2) ≤ B) :
    Integrable (fun p : Ω × (ℕ → ℝ) => Real.log
      (∫ x, Real.exp (H x + cylinderField (A x) p.2) ∂ν p.1)) (P.prod gaussianCoordinates) := by
  have : ∀ ω, IsProbabilityMeasure ((ν ω).tilted H) := fun ω => isProbabilityMeasure_tilted (hH ω)
  have hHH : Measurable (fun p : Ω × X => H p.2) :=
    (measurable_of_countable H).comp measurable_snd
  have htilt : Measurable (fun ω => (ν ω).tilted H) :=
    measurable_random_tilted_measure (H := fun p : Ω × X => H p.2) hν hHH
  let G := fun p : Ω × (ℕ → ℝ) => cgf (fun x => cylinderField (A x) p.2) ((ν p.1).tilted H) 1
  have hmG : Measurable G := measurable_random_cylinder_cgf htilt A 1
  have hiG : Integrable G (P.prod gaussianCoordinates) := integrable_random_cylinder_cgf htilt A hA 1
  have : ∀ p : Ω × (ℕ → ℝ), IsProbabilityMeasure ((fun p : Ω × (ℕ → ℝ) => ν p.1) p) :=
    fun p => by change IsProbabilityMeasure (ν p.1); infer_instance
  have hE : Measurable (fun p : (Ω × (ℕ → ℝ)) × X => H p.2 + cylinderField (A p.2) p.1.2) := by
    apply measurable_from_prod_countable_left
    intro x
    have hc : Measurable (fun _ : Ω × (ℕ → ℝ) => H x) := measurable_const
    exact hc.add ((measurable_cylinderField (A x)).comp measurable_snd)
  have hm : Measurable (fun p : Ω × (ℕ → ℝ) => Real.log
      (∫ x, Real.exp (H x + cylinderField (A x) p.2) ∂ν p.1)) :=
    (measurable_random_referencePartition (ν := fun p : Ω × (ℕ → ℝ) => ν p.1)
      (hν.comp measurable_fst) hE).log
  have heq : (fun p : Ω × (ℕ → ℝ) => Real.log
      (∫ x, Real.exp (H x + cylinderField (A x) p.2) ∂ν p.1)) =ᵐ[P.prod gaussianCoordinates]
      (fun p => C + G p) := by
    apply (Measure.ae_prod_iff_ae_ae (measurableSet_eq_fun hm (measurable_const.add hmG))).mpr
    exact ae_of_all _ fun ω => by
      have he := cylinder_log_partition_base (ν ω) H (hH ω) A hA 1
      filter_upwards [he] with g hg
      dsimp only [G, Pi.add_apply]
      simpa only [one_mul, hC ω] using hg
  exact ((integrable_const C).add hiG).congr (Filter.EventuallyEq.symm heq)

/-- Joint integrability over the actual cascade branching and flat
Gaussian coordinates, without a variance or pressure-limit hypothesis. -/
theorem tensorFlatLog_integrable {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) :
    Integrable (tensorFlatLog eig U c I degree amplitude n v)
      ((labeledCascadeLaw n b : Measure (LabeledTree n)).prod gaussianCoordinates) := by
  let ν := fun T : LabeledTree n => labeledSpinReference n (uniformSpinPrior N : Measure (Spin N)) T
  have : ∀ T, IsProbabilityMeasure (ν T) := fun T => by
    change IsProbabilityMeasure (labeledSpinReference n (uniformSpinPrior N : Measure (Spin N)) T)
    infer_instance
  obtain ⟨B, hcap⟩ := tensorLeafCoefficients_finite_bound U I degree amplitude n v
  exact random_cylinder_log_integrable
    (ν := ν) (P := (labeledCascadeLaw n b : Measure (LabeledTree n)))
    (measurable_labeledSpinReference_general n (uniformSpinPrior N : Measure (Spin N)))
    (fun x => rotatedEnergy eig U x.1 + fieldEnergy c x.1)
    (tensorFlat_base_exp_integrable eig U c n)
    (logPartition (fun σ => rotatedEnergy eig U σ + fieldEnergy c σ))
    (tensorFlat_base_log eig U c n)
    (tensorLeafCoefficients U I degree amplitude n (fun i => v i)) hcap

/-- The flat spin/leaf log partition has exactly the same mean as the
root-averaged tensor cascade recursion. -/
theorem tensorFlatLog_mean {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) :
    (∫ p, tensorFlatLog eig U c I degree amplitude n v p
      ∂(labeledCascadeLaw n b : Measure (LabeledTree n)).prod gaussianCoordinates) =
      ∫ z, tensorCascadeValue eig U c I degree amplitude n b (fun i => v (i + 1)) z
        ∂(tensorGaussianLaw I degree (v 0) : Measure (SpinTensorIndex I degree → ℝ)) := by
  let G := fun q : (SpinTensorIndex I degree → ℝ) × TensorLabeledData N n =>
    Real.log (∫ x, Real.exp (tensorLabeledEnergy eig U c I degree amplitude n q.1 q.2 x)
      ∂tensorLabeledReference N n q.2)
  have : ∀ q : (SpinTensorIndex I degree → ℝ) × TensorLabeledData N n,
      IsProbabilityMeasure ((tensorLabeledReference N n ∘ Prod.snd) q) := fun q => by
        change IsProbabilityMeasure (tensorLabeledReference N n q.2)
        infer_instance
  have hmG : Measurable G := (measurable_random_referencePartition
    ((measurable_tensorLabeledReference N n).comp measurable_snd)
    (measurable_tensorLabeledEnergy_root eig U c I degree amplitude n)).log
  have hp := tensorFlatToLabeled_measurePreserving U I degree amplitude n b v
  have he : G ∘ tensorFlatToLabeled U I degree amplitude n v =
      tensorFlatLog eig U c I degree amplitude n v := by
    funext p
    apply congrArg Real.log
    change (∫ x, Real.exp (tensorLabeledEnergy eig U c I degree amplitude n
      (tensorFlatToLabeled U I degree amplitude n v p).1
      (tensorFlatToLabeled U I degree amplitude n v p).2 x)
      ∂labeledSpinReference n (uniformSpinPrior N : Measure (Spin N)) p.1) = _
    apply integral_congr_ae
    refine ae_of_all _ fun x => ?_
    exact congrArg Real.exp (tensorLabeledEnergy_flat_eq eig U c I degree amplitude n v p x)
  have hi : Integrable (G ∘ tensorFlatToLabeled U I degree amplitude n v)
      ((labeledCascadeLaw n b : Measure (LabeledTree n)).prod gaussianCoordinates) := by
    rw [he]
    exact tensorFlatLog_integrable eig U c I degree amplitude n b v
  have hiG : Integrable G
      ((tensorGaussianLaw I degree (v 0) : Measure (SpinTensorIndex I degree → ℝ)).prod
        (tensorLabeledLaw U I degree amplitude n b (fun i => v (i + 1)))) := by
    rw [← hp.map_eq]
    exact (integrable_map_measure hmG.aestronglyMeasurable hp.aemeasurable).mpr hi
  rw [← he]
  change (∫ p, G (tensorFlatToLabeled U I degree amplitude n v p)
    ∂(labeledCascadeLaw n b : Measure (LabeledTree n)).prod gaussianCoordinates) = _
  rw [integral_comp_preserving_ae hp hmG.aestronglyMeasurable, integral_prod _ hiG]
  apply integral_congr_ae
  exact ae_of_all _ fun z =>
    (tensorLabeledLog_mean hN eig U c I degree amplitude n b (fun i => v (i + 1)) hb z).2

theorem tensorEnrichedPressure_eq_flat_mean {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) :
    tensorEnrichedPressure eig U c I degree amplitude n b (fun i => v (i + 1)) (v 0) =
      (N : ℝ)⁻¹ * ∫ T, (∫ g : ℕ → ℝ, tensorFlatLog eig U c I degree amplitude n v (T, g)
        ∂gaussianCoordinates) ∂(labeledCascadeLaw n b : Measure (LabeledTree n)) := by
  rw [tensorEnrichedPressure, ← tensorFlatLog_mean hN eig U c I degree amplitude n b v hb,
    integral_prod _ (tensorFlatLog_integrable eig U c I degree amplitude n b v)]

end InvariantIsing

end

end OAI