Download lean/OAI/Probability/SKBarriers/Calculus/ParameterSpace.lean from roseking/openAI-math-dataset: direct link, hf CLI and curl.
- Browser
- Download file 2.73 kB
-
https://huggingface.co/datasets/roseking/openAI-math-dataset/resolve/main/lean/OAI/Probability/SKBarriers/Calculus/ParameterSpace.lean
- Command line
-
hf download hf://datasets/roseking/openAI-math-dataset/lean/OAI/Probability/SKBarriers/Calculus/ParameterSpace.lean
-
curl -L -o ParameterSpace.lean https://huggingface.co/datasets/roseking/openAI-math-dataset/resolve/main/lean/OAI/Probability/SKBarriers/Calculus/ParameterSpace.lean
2.73 kB
| import Mathlib | |
| import OAI.Probability.SKBarriers.Calculus.MarginalPotential | |
| namespace OAI | |
| section | |
| section | |
| noncomputable section | |
| open scoped BigOperators Topology | |
| open MeasureTheory ProbabilityTheory Filter | |
| noncomputable section | |
| open MeasureTheory Set Filter | |
| open scoped Topology Interval | |
| noncomputable section | |
| open MeasureTheory Set | |
| open scoped Interval | |
| namespace SK.Analytic | |
| @[reducible] def ParameterSpace : ℕ → Type | |
| | 0 => ℝ | |
| | n+1 => ParameterSpace n × ℝ | |
| instance parameterNormedGroup : (n : ℕ) → NormedAddCommGroup (ParameterSpace n) | |
| | 0 => inferInstanceAs (NormedAddCommGroup ℝ) | |
| | n+1 => letI := parameterNormedGroup n; inferInstanceAs (NormedAddCommGroup (ParameterSpace n × ℝ)) | |
| instance parameterNormedSpace : (n : ℕ) → NormedSpace ℝ (ParameterSpace n) | |
| | 0 => inferInstanceAs (NormedSpace ℝ ℝ) | |
| | n+1 => letI := parameterNormedSpace n; inferInstanceAs (NormedSpace ℝ (ParameterSpace n × ℝ)) | |
| instance parameterFiniteDimensional : (n : ℕ) → FiniteDimensional ℝ (ParameterSpace n) | |
| | 0 => inferInstanceAs (FiniteDimensional ℝ ℝ) | |
| | n+1 => letI := parameterFiniteDimensional n; inferInstanceAs (FiniteDimensional ℝ (ParameterSpace n × ℝ)) | |
| def coordinateSquare : (n : ℕ) → ParameterSpace n → ℝ | |
| | 0, _ => 0 | |
| | n+1, z => coordinateSquare n z.1 + z.2^2 | |
| @[simp] theorem coordinateSquare_zero (n : ℕ) : coordinateSquare n 0 = 0 := by | |
| induction n with | |
| | zero => rfl | |
| | succ n ih => | |
| change coordinateSquare n (0 : ParameterSpace n) + (0 : ℝ)^2 = 0 | |
| rw [ih] | |
| norm_num | |
| theorem coordinateSquare_nonneg (n : ℕ) (z : ParameterSpace n) : | |
| 0 ≤ coordinateSquare n z := by | |
| induction n with | |
| | zero => exact le_refl _ | |
| | succ n ih => exact add_nonneg (ih z.1) (sq_nonneg z.2) | |
| def cubePotential : (n : ℕ) → (ParameterSpace n → ℝ) → ℝ → ℝ → ℝ → ℝ | |
| | 0, V, _, _ => V | |
| | n+1, V, a, b => cubePotential n (marginalPotential V a b) a b | |
| theorem cubePotential_hessian_lower (n : ℕ) (V : ParameterSpace n → ℝ) | |
| (hV : ContDiff ℝ 2 V) {c : ℝ} (hc : 0 < c) | |
| (hH : ∀ z u, c * coordinateSquare n u ≤ Hessian V z u u) | |
| {a b : ℝ} (hab : a < b) : | |
| ContDiff ℝ 2 (cubePotential n V a b) ∧ | |
| ∀ x u, 0 ≤ Hessian (cubePotential n V a b) x u u := by | |
| induction n with | |
| | zero => | |
| refine ⟨hV, ?_⟩ | |
| intro x u | |
| change 0 ≤ Hessian V x u u | |
| simpa only [coordinateSquare, mul_zero] using hH x u | |
| | succ n ih => | |
| apply ih (marginalPotential V a b) (contDiff_marginalPotential V 2 hV hab) | |
| intro z u | |
| apply marginal_hessian_lower V hV (coordinateSquare n) (coordinateSquare_zero n) hc | |
| (fun z u s => hH z (u,s)) hab | |
| end SK.Analytic | |
| end | |
| end | |
| end | |
| end | |
| end | |
| end OAI | |