Download lean/OAI/Geometry/NodalSets/Spectral/CompactPositiveMaxEigenvector.lean from roseking/openAI-math-dataset: direct link, hf CLI and curl.
- Browser
- Download file 2.43 kB
-
https://huggingface.co/datasets/roseking/openAI-math-dataset/resolve/main/lean/OAI/Geometry/NodalSets/Spectral/CompactPositiveMaxEigenvector.lean
- Command line
-
hf download hf://datasets/roseking/openAI-math-dataset/lean/OAI/Geometry/NodalSets/Spectral/CompactPositiveMaxEigenvector.lean
-
curl -L -o CompactPositiveMaxEigenvector.lean https://huggingface.co/datasets/roseking/openAI-math-dataset/resolve/main/lean/OAI/Geometry/NodalSets/Spectral/CompactPositiveMaxEigenvector.lean
2.43 kB
| import Mathlib.Analysis.InnerProductSpace.Spectrum | |
| namespace OAI | |
| namespace Yau.Analysis | |
| open Filter Set Module.End | |
| noncomputable section | |
| theorem compact_positive_max_eigenvector {E : Type*} [NormedAddCommGroup E] | |
| [InnerProductSpace ℝ E] [CompleteSpace E] [Nontrivial E] | |
| (T : E →L[ℝ] E) (hc : IsCompactOperator T) (hs : T.IsSymmetric) | |
| (hp : ∀ x, 0 ≤ inner ℝ (T x) x) (hT : T ≠ 0) : | |
| ∃ v : E, ‖v‖=1 ∧ T v=‖T‖ • v ∧ | |
| inner ℝ (T v) v=‖T‖ ∧ ∀ x : E, inner ℝ (T x) x ≤ ‖T‖*‖x‖^2 := by | |
| have hn : 0 < ‖T‖ := norm_pos_iff.mpr hT | |
| have hspec : ‖T‖ ∈ spectrum ℝ T ∨ -‖T‖ ∈ spectrum ℝ T := by | |
| by_contra! h | |
| have h1 : ‖T‖ ∈ resolventSet ℝ T := by simpa only [spectrum,mem_compl_iff,not_not] using h.1 | |
| have h2 : -‖T‖ ∈ resolventSet ℝ T := by simpa only [spectrum,mem_compl_iff,not_not] using h.2 | |
| obtain ⟨c,hc0,hc⟩ := T.abs_rayleighQuotient_le_of_norm_mem_resolventSet h1 h2 | |
| have hb : (⨆ x, |T.rayleighQuotient x|) ≤ ‖T‖-c := ciSup_le hc | |
| rw [← T.norm_eq_iSup_rayleighQuotient hs] at hb | |
| linarith | |
| have he : HasEigenvalue T.toLinearMap ‖T‖ := by | |
| rcases hspec with h | h | |
| · exact (hc.hasEigenvalue_iff_mem_spectrum hn.ne').mpr h | |
| · obtain ⟨v,hv⟩ := ((hc.hasEigenvalue_iff_mem_spectrum (neg_ne_zero.mpr hn.ne')).mpr h).exists_hasEigenvector | |
| have heq : T v = -‖T‖ • v := hv.apply_eq_smul | |
| have hh := hp v | |
| rw [heq,inner_smul_left_eq_smul,smul_eq_mul,real_inner_self_eq_norm_sq] at hh | |
| have hvpos : 0 < ‖v‖^2 := sq_pos_of_pos (norm_pos_iff.mpr hv.2) | |
| nlinarith | |
| obtain ⟨v,hv⟩ := he.exists_hasEigenvector | |
| have hvnorm : ‖v‖ ≠ 0 := norm_ne_zero_iff.mpr hv.2 | |
| let u := ‖v‖⁻¹ • v | |
| have hun : ‖u‖=1 := by | |
| simp only [u,norm_smul,Real.norm_eq_abs,abs_inv,abs_norm,inv_mul_cancel₀ hvnorm] | |
| have heq : T v=‖T‖ • v := hv.apply_eq_smul | |
| have hue : T u=‖T‖ • u := by | |
| dsimp [u] | |
| rw [map_smul,heq,smul_comm] | |
| refine ⟨u,hun,hue,?_,?_⟩ | |
| · rw [hue,inner_smul_left_eq_smul,smul_eq_mul,real_inner_self_eq_norm_sq,hun] | |
| ring | |
| · intro x | |
| calc | |
| inner ℝ (T x) x ≤ ‖T x‖*‖x‖ := real_inner_le_norm _ _ | |
| _ ≤ (‖T‖*‖x‖)*‖x‖ := mul_le_mul_of_nonneg_right (T.le_opNorm x) (norm_nonneg x) | |
| _ = ‖T‖*‖x‖^2 := by ring | |
| end | |
| end Yau.Analysis | |
| end OAI | |