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Project-declaredLean 4.32.0 · mathlib@81a5d257c8e4

Exceptional set carleson

exceptional_set_carleson'

Plain-language statement

For a continuous, 2π2\pi-periodic function ff and any δ,ε>0\delta,\varepsilon>0, there is an index N0N_0 such that the set of x(0,2π]x\in(0,2\pi] for which supN>N0f(x)SNf(x)\sup_{N>N_0}\lVert f(x)-S_Nf(x)\rVert exceeds δ\delta has measure at most ε\varepsilon.

Exact Lean statement

theorem exceptional_set_carleson' {f : ℝ → ℂ} (cont_f : Continuous f)
  (periodic_f : f.Periodic (2 * π)) {δ ε : NNReal} (δpos : 0 < δ) (εpos : 0 < ε) :
    ∃ N₀, distribution (fun x ↦ ⨆ N > N₀, ‖f x - S_ N f x‖ₑ) δ (volume.restrict (Set.Ioc 0 (2 * π))) ≤ ε

Formal artifact

Lean source

Canonical source
Full Lean sourceLean 4
theorem exceptional_set_carleson' {f :   ℂ} (cont_f : Continuous f)  (periodic_f : f.Periodic (2 * π)) {δ ε : NNReal} (δpos : 0 < δ) (εpos : 0 < ε) :     N₀, distribution (fun x  ⨆ N > N₀, ‖f x - S_ N f x‖ₑ) δ (volume.restrict (Set.Ioc 0 (2 * π)))  ε := by  have δ2pos : 0 < δ / 2 := by positivity  have δ4pos : 0 < δ / 4 := by positivity  have ε2pos : 0 < ε / 2 := by positivity  have ε4pos : 0 < ε / 4 := by positivity  have unicont_f : UniformContinuous f := periodic_f.uniformContinuous_of_continuous    Real.two_pi_pos cont_f.continuousOn  /- Approximate f by a smooth f₀. -/  obtain f₀, contDiff_f₀, periodic_f₀, hf₀ :=    close_smooth_approx_periodic unicont_f periodic_f      (lt_min δ4pos (C_control_approximation_effect'_pos δ2pos ε2pos))  obtain N₀, hN₀ := fourierConv_ofTwiceDifferentiable periodic_f₀    ((contDiff_infty.mp (contDiff_f₀)) 2) δ4pos  /- This is a classical "epsilon third" argument. -/  use N₀  have : ᶠx in (ae (volume.restrict (Set.Ioc 0 (2 * π)))), ⨆ N > N₀, ‖f x - S_ N f x‖ₑ       ‖f x - f₀ x‖ₑ + (⨆ N > N₀, ‖f₀ x - S_ N f₀ x‖ₑ) + ⨆ N, ‖S_ N (f₀ - f) x‖ₑ := by    rw [ae_restrict_iff' measurableSet_Ioc]    filter_upwards with x hx    apply iSup_le    intro N    apply iSup_le    intro hN    calc ‖f x - S_ N f x‖ₑ      _ = ‖(f x - f₀ x) + (f₀ x - S_ N f₀ x) + (S_ N f₀ x - S_ N f x)‖ₑ := by ring_nf      _  ‖(f x - f₀ x) + (f₀ x - S_ N f₀ x)‖ₑ + ‖S_ N f₀ x - S_ N f x‖ₑ := enorm_add_le ..      _  ‖f x - f₀ x‖ₑ + ‖f₀ x - S_ N f₀ x‖ₑ + ‖S_ N f₀ x - S_ N f x‖ₑ :=        add_le_add_left (enorm_add_le ..) _      _  ‖f x - f₀ x‖ₑ + (⨆ N > N₀, ‖f₀ x - S_ N f₀ x‖ₑ) + ⨆ N, ‖S_ N (f₀ - f) x‖ₑ := by        gcongr        · refine le_iSup₂_of_le N hN ?_          rfl        · apply le_iSup_of_le N          rw [partialFourierSum_sub (contDiff_f₀.continuous.intervalIntegrable 0 (2 * π))            (cont_f.intervalIntegrable 0 (2 * π))]          · rfl  calc _    _  distribution        (fun x  ‖f x - f₀ x‖ₑ + (⨆ N > N₀, ‖f₀ x - S_ N f₀ x‖ₑ) + ⨆ N, ‖S_ N (f₀ - f) x‖ₑ)        ((δ / 4) +/ 4) +/ 2)) (volume.restrict (Set.Ioc 0 (2 * π))) := by      apply distribution_mono      · filter_upwards [this] with x hx        simp only [gt_iff_lt, enorm_eq_self, hx]      · norm_cast        ring_nf        rfl    _  distribution (fun x  ‖f x - f₀ x‖ₑ) (δ / 4) (volume.restrict (Set.Ioc 0 (2 * π)))        + distribution (fun x  ⨆ N > N₀, ‖f₀ x - S_ N f₀ x‖ₑ) (δ / 4) (volume.restrict (Set.Ioc 0 (2 * π)))        + distribution (fun x  ⨆ N, ‖S_ N (f₀ - f) x‖ₑ) (δ / 2) (volume.restrict (Set.Ioc 0 (2 * π))) := by      apply distribution_add_le.trans      gcongr      exact distribution_add_le    _  ε / 2 + 0 + ε / 2 := by      gcongr      · norm_cast        convert! zero_le (α := 0∞)        rw [distribution_eq_zero_iff]        apply eLpNormEssSup_le_of_ae_enorm_bound        filter_upwards with x        simp only [enorm_eq_self, ne_eq, OfNat.ofNat_ne_zero, not_false_eq_true, coe_div, coe_ofNat]        have : ENNReal.ofNNReal δ / 4 = ↑(δ / 4) := by norm_num        rw [this, enorm_le_coe]        rw [ nnnorm_norm]        calc _          _  ‖((δ / 4) : )‖₊ := nnnorm_le_nnnorm (by simp) ((hf₀ x).trans (min_le_left _ _))          _ = δ / 4 := by simp      · simp only [gt_iff_lt, nonpos_iff_eq_zero]        rw [distribution_eq_zero_iff]        apply essSup_le_of_ae_le _        rw [EventuallyLE, ae_restrict_iff' measurableSet_Ioc]        filter_upwards with x hx        simp only [enorm_eq_self, iSup_le_iff]        intro N hN        rw [enorm_eq_nnnorm,  nnnorm_norm]        norm_cast        calc _          _  ‖((δ / 4) : )‖₊ :=            nnnorm_le_nnnorm (by simp) (hN₀ N hN x (Set.Ioc_subset_Icc_self hx))          _ = δ / 4 := by simp      · norm_cast        apply control_approximation_effect' (ε := ε / 2) δ2pos ε2pos          (contDiff_f₀.continuous.sub cont_f).measurable            (periodic_f₀.sub periodic_f)        intro x        rw [Pi.sub_apply, norm_sub_rev]        apply (hf₀ x).trans (min_le_right _ _)    _ = ε := by simp
Project
Carleson formalization
License
Apache-2.0
Commit
74ef907d6bdb
Source
Carleson/Classical/ClassicalCarleson.lean:28-116

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Ae tendsto zero of distribution le

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Plain-language statement

Suppose that, for every error threshold δ>0\delta>0 and every measure tolerance ε>0\varepsilon>0, one can choose N0N_0 so that the set where supN>N0f(x)FN(x)\sup_{N>N_0}\lVert f(x)-F_N(x)\rVert exceeds δ\delta has measure at most ε\varepsilon. Then FN(x)F_N(x) converges to f(x)f(x) for almost every xx.

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Project-declaredLean 4.32.0

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Plain-language statement

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harmonic analysisFourier analysismeasure theory

Source project: Carleson formalization

Person-level attribution pending.

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