Download lean/OAI/Analysis/HyperbolicCones/KernelLimit.lean from roseking/openAI-math-dataset: direct link, hf CLI and curl.
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2.09 kB
| import OAI.Analysis.HyperbolicCones.SpectralContinuity | |
| import OAI.Analysis.HyperbolicCones.InverseOrder | |
| namespace OAI | |
| /-! The inverse-square-root kernel limit for every finite positive semidefinite matrix. -/ | |
| noncomputable section | |
| open scoped Matrix.Norms.L2Operator MatrixOrder | |
| open Matrix Filter Topology | |
| namespace Paper256 | |
| theorem inverseSquareRoot_affine_eq_cfc {n : ℕ} (H : Sym n) (t : ℝ) : | |
| inverseSquareRoot (1 + (t - 1) • H) = | |
| cfc (fun x : ℝ => (Real.sqrt (1 + (t - 1) * x))⁻¹) (H : Mat n ℝ) := by | |
| have haff : cfc (fun x : ℝ => 1 + (t - 1) * x) (H : Mat n ℝ) = | |
| ((1 + (t - 1) • H : Sym n) : Mat n ℝ) := by | |
| simpa using matrix_cfc_affine H 1 (t - 1) | |
| have hcomp := cfc_comp (fun x : ℝ => (Real.sqrt x)⁻¹) | |
| (fun x : ℝ => 1 + (t - 1) * x) (H : Mat n ℝ) H.property | |
| ((H.val.finite_real_spectrum.image _).continuousOn _) | |
| (H.val.finite_real_spectrum.continuousOn _) | |
| rw [haff] at hcomp | |
| exact (inverseSquareRoot_eq_cfc _).trans hcomp.symm | |
| theorem inverseSquareRoot_affine_tendsto {n : ℕ} (H : Sym n) | |
| (hH : (H : Mat n ℝ).PosSemidef) : | |
| Tendsto (fun t : ℝ => inverseSquareRoot (1 + (t - 1) • H)) atTop | |
| (𝓝 (kernelProjection (H : Mat n ℝ))) := by | |
| have hc := matrix_cfc_tendsto (H : Mat n ℝ) H.property | |
| (fun t x : ℝ => (Real.sqrt (1 + (t - 1) * x))⁻¹) | |
| (fun x : ℝ => if x = 0 then 1 else 0) | |
| (fun i => inverse_sqrt_affine_scalar_tendsto _ (hH.eigenvalues_nonneg i)) | |
| simpa only [← inverseSquareRoot_affine_eq_cfc, ← kernelProjection_eq_cfc] using hc | |
| theorem inverseSquareRoot_kernel_limit (n : ℕ) (H : Sym n) | |
| (hH : (H : Mat n ℝ).PosSemidef) : | |
| Tendsto (fun t : ℝ => operatorNorm | |
| (inverseSquareRoot (1 + (t - 1) • H) - kernelProjection (H : Mat n ℝ))) | |
| atTop (𝓝 0) := by | |
| have h := ((inverseSquareRoot_affine_tendsto H hH).sub_const | |
| (kernelProjection (H : Mat n ℝ))).norm | |
| have hop (A : Mat n ℝ) : operatorNorm A = ‖A‖ := (Matrix.l2_opNorm_def A).symm | |
| simpa only [hop, sub_self, norm_zero] using h | |
| end Paper256 | |
| end | |
| end OAI | |