Download lean/OAI/Probability/InvariantIsing/Arrays/NSpinCascade.lean from roseking/openAI-math-dataset: direct link, hf CLI and curl.
- Browser
- Download file 7.56 kB
-
https://huggingface.co/datasets/roseking/openAI-math-dataset/resolve/main/lean/OAI/Probability/InvariantIsing/Arrays/NSpinCascade.lean
- Command line
-
hf download hf://datasets/roseking/openAI-math-dataset/lean/OAI/Probability/InvariantIsing/Arrays/NSpinCascade.lean
-
curl -L -o NSpinCascade.lean https://huggingface.co/datasets/roseking/openAI-math-dataset/resolve/main/lean/OAI/Probability/InvariantIsing/Arrays/NSpinCascade.lean
7.56 kB
| import OAI.Probability.InvariantIsing.Fields.CascadeMarking | |
| import OAI.Probability.InvariantIsing.Haar.Rotation | |
| import OAI.Probability.IsingPerceptron.EnrichedFieldCap | |
| namespace OAI | |
| /-! | |
| Gaussian cascade marking for the actual finite Ising partition function at | |
| a fixed orthogonal rotation. The Haar variable is fixed in this result. | |
| -/ | |
| noncomputable section | |
| open MeasureTheory ProbabilityTheory | |
| open scoped BigOperators NNReal | |
| namespace InvariantIsing | |
| def rotatedFieldTerminal {N : ℕ} (eig : Fin N → ℝ) (U : Rotation N) | |
| (c z : Fin N → ℝ) : ℝ := | |
| logPartition (fun σ => rotatedEnergy eig U σ + fieldEnergy (c + z) σ) | |
| lemma measurable_rotatedFieldTerminal {N : ℕ} (eig : Fin N → ℝ) (U : Rotation N) | |
| (c : Fin N → ℝ) : Measurable (rotatedFieldTerminal eig U c) := by | |
| unfold rotatedFieldTerminal logPartition fieldEnergy | |
| fun_prop | |
| lemma abs_rotatedFieldTerminal_sub_le {N : ℕ} (eig : Fin N → ℝ) (U : Rotation N) | |
| (c z w : Fin N → ℝ) : | |
| |rotatedFieldTerminal eig U c z - rotatedFieldTerminal eig U c w| ≤ | |
| (N : ℝ) * ‖z - w‖ := by | |
| have he (σ : Spin N) : | |
| |(rotatedEnergy eig U σ + fieldEnergy (c + z) σ) - | |
| (rotatedEnergy eig U σ + fieldEnergy (c + w) σ)| ≤ (N : ℝ) * ‖z - w‖ := by | |
| rw [add_sub_add_left_eq_sub] | |
| calc | |
| _ ≤ ∑ i, |(c + z) i - (c + w) i| := abs_fieldEnergy_sub_le _ _ σ | |
| _ = ∑ i, |z i - w i| := by simp only [Pi.add_apply, add_sub_add_left_eq_sub] | |
| _ ≤ ∑ _ : Fin N, ‖z - w‖ := Finset.sum_le_sum fun i _ => by | |
| simpa only [Pi.sub_apply, Real.norm_eq_abs] using norm_le_pi_norm (z - w) i | |
| _ = (N : ℝ) * ‖z - w‖ := by simp | |
| exact abs_logPartition_sub_le _ _ _ he | |
| lemma rotatedFieldTerminal_linearGrowth {N : ℕ} (eig : Fin N → ℝ) (U : Rotation N) | |
| (c : Fin N → ℝ) : IsingPerceptron.HasLinearGrowth (rotatedFieldTerminal eig U c) := by | |
| refine ⟨|rotatedFieldTerminal eig U c 0|, N, abs_nonneg _, Nat.cast_nonneg _, fun z => ?_⟩ | |
| have hl := abs_rotatedFieldTerminal_sub_le eig U c z 0 | |
| rw [sub_zero] at hl | |
| have ht := abs_add_le (rotatedFieldTerminal eig U c z - rotatedFieldTerminal eig U c 0) | |
| (rotatedFieldTerminal eig U c 0) | |
| rw [sub_add_cancel] at ht | |
| linarith | |
| def vectorGaussianLaw (N : ℕ) (v : ℝ≥0) : ProbabilityMeasure (Fin N → ℝ) := | |
| ⟨Measure.pi (fun _ : Fin N => gaussianReal 0 v), inferInstance⟩ | |
| lemma vectorGaussianLaw_moments {N : ℕ} (hN : 0 < N) (v : ℝ≥0) : | |
| IsingPerceptron.ExponentialNormMoments (vectorGaussianLaw N v : Measure (Fin N → ℝ)) := by | |
| let : Nonempty (Fin N) := ⟨⟨0, hN⟩⟩ | |
| have hm := IsingPerceptron.finite_gaussian_exponentialNormMoments | |
| (P := Measure.pi (fun _ : Fin N => gaussianReal 0 v)) | |
| (X := fun z : Fin N → ℝ => z) measurable_id (fun _ => 0) (fun _ => v) | |
| (fun i => (measurePreserving_eval (fun _ : Fin N => gaussianReal 0 v) i).map_eq) | |
| change IsingPerceptron.ExponentialNormMoments | |
| ((Measure.pi (fun _ : Fin N => gaussianReal 0 v)).map id) at hm | |
| rw [Measure.map_id] at hm | |
| exact hm | |
| def rotatedCascadeLaw (N n : ℕ) (b : ℕ → ℝ) (v : ℕ → ℝ≥0) : | |
| Measure (IsingPerceptron.NoiseTree (Fin N → ℝ) n) := | |
| IsingPerceptron.noiseCascadeLaw (Fin N → ℝ) n b (fun i => vectorGaussianLaw N (v i)) | |
| def rotatedCascadeLog {N : ℕ} (n : ℕ) (eig : Fin N → ℝ) (U : Rotation N) | |
| (c z : Fin N → ℝ) (T : IsingPerceptron.NoiseTree (Fin N → ℝ) n) : ℝ := | |
| Real.log (∫ leaf, Real.exp (IsingPerceptron.noiseLeafTerminal n | |
| (fun _ => rotatedFieldTerminal eig U c) (fun _ p => p.1 + p.2) z leaf) | |
| ∂IsingPerceptron.noiseLeafKernel (Fin N → ℝ) n T) | |
| def rotatedCascadeValue {N : ℕ} (n : ℕ) (b : ℕ → ℝ) (v : ℕ → ℝ≥0) | |
| (eig : Fin N → ℝ) (U : Rotation N) (c z : Fin N → ℝ) : ℝ := | |
| IsingPerceptron.cascadeRecursion n b (fun i => vectorGaussianLaw N (v i)) | |
| (fun _ p => p.1 + p.2) (rotatedFieldTerminal eig U c) z | |
| /-- The published Gaussian marking recursion specialized to the actual | |
| finite rotated Ising terminal, with the Haar rotation held fixed. -/ | |
| theorem rotatedCascadeLog_recursion {N : ℕ} (hN : 0 < N) (n : ℕ) (b : ℕ → ℝ) | |
| (v : ℕ → ℝ≥0) (hb : IsingPerceptron.CascadeExponents n b) | |
| (eig : Fin N → ℝ) (U : Rotation N) (c z : Fin N → ℝ) : | |
| Integrable (rotatedCascadeLog n eig U c z) (rotatedCascadeLaw N n b v) ∧ | |
| (∫ T, rotatedCascadeLog n eig U c z T ∂rotatedCascadeLaw N n b v) = | |
| rotatedCascadeValue n b v eig U c z := by | |
| have h := IsingPerceptron.linearGrowth_noiseCascade_recursion n b hb | |
| (fun i => vectorGaussianLaw N (v i)) (fun i _ => vectorGaussianLaw_moments hN (v i)) | |
| (measurable_rotatedFieldTerminal eig U c) (rotatedFieldTerminal_linearGrowth eig U c) z | |
| have he := IsingPerceptron.noise_leaf_log_eq_ratio n b hb | |
| (fun i => vectorGaussianLaw N (v i)) | |
| (fun _ => measurable_fst.add measurable_snd) (measurable_rotatedFieldTerminal eig U c) z | |
| refine ⟨h.2.1.congr (Filter.EventuallyEq.symm he), ?_⟩ | |
| exact (integral_congr_ae he).trans h.2.2.1 | |
| lemma integrable_rotatedCascadeValue {N : ℕ} (hN : 0 < N) (n : ℕ) (b : ℕ → ℝ) | |
| (v : ℕ → ℝ≥0) (hb : IsingPerceptron.CascadeExponents n b) | |
| (eig : Fin N → ℝ) (U : Rotation N) (c : Fin N → ℝ) (root : ℝ≥0) : | |
| Integrable (rotatedCascadeValue n b v eig U c) | |
| (vectorGaussianLaw N root : Measure (Fin N → ℝ)) := by | |
| have hm := IsingPerceptron.measurable_cascadeRecursion n b | |
| (fun i => vectorGaussianLaw N (v i)) | |
| (fun _ => measurable_fst.add measurable_snd) (measurable_rotatedFieldTerminal eig U c) | |
| change Measurable (rotatedCascadeValue n b v eig U c) at hm | |
| have hg := IsingPerceptron.cascadeRecursion_linearGrowth n b | |
| (fun i => vectorGaussianLaw N (v i)) (fun i _ => vectorGaussianLaw_moments hN (v i)) | |
| (measurable_rotatedFieldTerminal eig U c) (rotatedFieldTerminal_linearGrowth eig U c) | |
| (fun i hi => (hb.1 i hi).1) | |
| obtain ⟨C, L, _, hL, hbound⟩ := hg | |
| have hi := (integrable_const C).add ((vectorGaussianLaw_moments hN root 1).const_mul L) | |
| apply hi.mono' hm.aestronglyMeasurable | |
| exact ae_of_all _ fun z => by | |
| change |rotatedCascadeValue n b v eig U c z| ≤ C + L * Real.exp (1 * ‖z‖) | |
| rw [one_mul] | |
| exact (hbound z).trans (add_le_add le_rfl | |
| (mul_le_mul_of_nonneg_left | |
| ((le_add_of_nonneg_right zero_le_one).trans (Real.add_one_le_exp ‖z‖)) hL)) | |
| def rotatedEnrichedPressure {N : ℕ} (n : ℕ) (b : ℕ → ℝ) (v : ℕ → ℝ≥0) | |
| (root : ℝ≥0) (eig : Fin N → ℝ) (U : Rotation N) (c : Fin N → ℝ) : ℝ := | |
| (N : ℝ)⁻¹ * ∫ z, rotatedCascadeValue n b v eig U c z | |
| ∂(vectorGaussianLaw N root : Measure (Fin N → ℝ)) | |
| /-- The fixed-rotation enriched pressure is the actual iterated Gaussian | |
| root and cascade expectation of the finite Ising log partition. -/ | |
| theorem rotatedEnrichedPressure_eq_cascade_expectation {N : ℕ} (hN : 0 < N) | |
| (n : ℕ) (b : ℕ → ℝ) (v : ℕ → ℝ≥0) (root : ℝ≥0) | |
| (hb : IsingPerceptron.CascadeExponents n b) | |
| (eig : Fin N → ℝ) (U : Rotation N) (c : Fin N → ℝ) : | |
| rotatedEnrichedPressure n b v root eig U c = | |
| (N : ℝ)⁻¹ * ∫ z, (∫ T, rotatedCascadeLog n eig U c z T | |
| ∂rotatedCascadeLaw N n b v) ∂(vectorGaussianLaw N root : Measure (Fin N → ℝ)) := by | |
| unfold rotatedEnrichedPressure | |
| congr 1 | |
| apply integral_congr_ae | |
| exact ae_of_all _ fun z => (rotatedCascadeLog_recursion hN n b v hb eig U c z).2.symm | |
| end InvariantIsing | |
| end | |
| end OAI | |