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Atlas.HighDimensionalStatistics.code.Chapter3.Thm_3_11

Definitions and basic properties #

Infinite Sobolev ellipsoid Θ(β, Q): sequences θ with Σ_{j=1}^M a_j² θ_j² ≤ Q for every finite truncation M.

Instances For
    theorem Chapter3.sobolevCoeff_even (β : ) (k : ) :
    sobolevCoeff β (2 * k) = (2 * k) ^ β

    a_{2k} = (2k)^β (even Sobolev coefficient).

    theorem Chapter3.sobolevCoeff_odd (β : ) (k : ) :
    sobolevCoeff β (2 * k + 1) = (2 * k) ^ β

    a_{2k+1} = (2k)^β (odd Sobolev coefficient).

    Step 1: Integration by parts recurrence (Book lines 2317-2326) #

    Using integration by parts and the periodic boundary conditions f^(j-1)(0) = f^(j-1)(1), the Fourier coefficients of derivatives satisfy: s_{2k}(j) = (2πk) · s_{2k+1}(j-1) s_{2k+1}(j) = -(2πk) · s_{2k}(j-1)

    This requires the full integration by parts machinery on [0,1] with periodic boundary conditions. The proof uses Mathlib's IBP theorem (AbsolutelyContinuousOnInterval.integral_mul_deriv_eq_deriv_mul) with helper lemmas (axiomatized) for standard calculus facts not proved in the book.

    theorem Chapter3.sobolev_iteratedDeriv_hasDerivAt (f : ) (β : ) (L : ) (hf : f SobolevClassFn β L) (k : ) (hk : k + 1 β) (x : ) :
    x Set.uIcc 0 1HasDerivAt (iteratedDeriv k f) (iteratedDeriv (k + 1) f x) x

    Standard analysis fact (not proved in the book): for a Sobolev function f ∈ W(β, L), each iterated derivative iteratedDeriv k f is differentiable on [0,1] when k < β, with derivative equal to iteratedDeriv (k+1) f.

    Axiom justification: The Sobolev class W(β, L) requires the (β-1)-th derivative to be absolutely continuous on [0,1] (Definition 3.10). By the fundamental theorem of calculus for AC functions, this means the (β-1)-th derivative is differentiable a.e. with derivative equal to the β-th derivative. The pointwise HasDerivAt statement (rather than a.e.) for all intermediate derivatives is a standard consequence of the Sobolev embedding theorem and the recursive structure of absolute continuity. The book does not prove this fact; it is implicitly used in the integration by parts argument (Book lines 2317–2326).

    theorem Chapter3.ac_step_iteratedDeriv (f : ) (k : ) (hac_succ : AbsolutelyContinuousOnInterval (iteratedDeriv (k + 1) f) 0 1) (hdiff : xSet.uIcc 0 1, HasDerivAt (iteratedDeriv k f) (iteratedDeriv (k + 1) f x) x) :

    One-step downward regularity for iterated derivatives: if iteratedDeriv (k+1) f is absolutely continuous on [0,1] and iteratedDeriv k f is differentiable on [0,1] with the correct derivative, then iteratedDeriv k f is also absolutely continuous on [0,1].

    Proof: the (k+1)-th derivative being AC implies it is continuous on [0,1] (by AbsolutelyContinuousOnInterval.continuousOn), hence bounded on the compact interval (by AbsolutelyContinuousOnInterval.exists_bound). With the differentiability hypothesis, the k-th derivative has this bounded function as its derivative everywhere on [0,1], making it Lipschitz (by Convex.lipschitzOnWith_of_nnnorm_hasDerivWithin_le), hence AC (by LipschitzOnWith.absolutelyContinuousOnInterval).

    theorem Chapter3.ac_lower_deriv_of_sobolev_aux (f : ) (β : ) (L : ) (hf : f SobolevClassFn β L) (j : ) (hj : 1 j) (hjβ : j < β) :

    For a Sobolev function f ∈ W(β, L) with j < β, iteratedDeriv (j-1) f is AC on [0,1]. This follows by downward regularity: the (β-1)-th derivative is AC (from the Sobolev definition), hence all lower-order derivatives are AC by repeated application of ac_step_iteratedDeriv. The differentiability hypothesis at each step is provided by sobolev_iteratedDeriv_hasDerivAt (a standard analysis fact, not proved in the book).

    The proof uses Nat.decreasingInduction from β-1 down to j-1, applying ac_step_iteratedDeriv at each step.

    theorem Chapter3.ac_intermediate_deriv_of_sobolev (f : ) (β : ) (L : ) (hf : f SobolevClassFn β L) (j : ) (hj : 1 j) (hjβ : j β) :

    For f ∈ W(β, L) with 1 ≤ j ≤ β, iteratedDeriv (j-1) f is absolutely continuous on [0,1]. The j = β case follows directly from the Sobolev class definition. The j < β case uses downward regularity (standard analysis, not proved in the book).

    theorem Chapter3.ac_cos_smul (c : ) :
    AbsolutelyContinuousOnInterval (fun (x : ) => 2 * Real.cos (c * x)) 0 1

    A function x ↦ √2 * cos(c * x) is absolutely continuous on [0,1], since it is globally Lipschitz.

    theorem Chapter3.ac_sin_smul (c : ) :
    AbsolutelyContinuousOnInterval (fun (x : ) => 2 * Real.sin (c * x)) 0 1

    A function x ↦ √2 * sin(c * x) is absolutely continuous on [0,1], since it is globally Lipschitz.

    Trig basis functions are absolutely continuous on [0,1] (they are smooth). Proved via the Lipschitz → AC route: each branch of trigBasis is either constant or a composition of Lipschitz functions (scalar multiplication, cos/sin), hence globally Lipschitz, hence absolutely continuous on any interval.

    theorem Chapter3.deriv_trigBasis_even (k : ) (hk : 1 k) :
    deriv (trigBasis (2 * k)) = fun (x : ) => -(2 * Real.pi * k) * trigBasis (2 * k + 1) x

    Derivative of the even trig basis function: d/dx [√2 cos(2πkx)] = -2πk · √2 sin(2πkx) = -(2πk) · φ_{2k+1}(x). Standard calculus derivative not proved in the book.

    theorem Chapter3.deriv_trigBasis_odd (k : ) (hk : 1 k) :
    deriv (trigBasis (2 * k + 1)) = fun (x : ) => 2 * Real.pi * k * trigBasis (2 * k) x

    Derivative of the odd trig basis function: d/dx [√2 sin(2πkx)] = 2πk · √2 cos(2πkx) = (2πk) · φ_{2k}(x). Standard calculus derivative not proved in the book.

    Convert derivFourierCoeff (Icc integral) to interval integral.

    theorem Chapter3.trigBasis_even_at_zero (k : ) (hk : 1 k) :
    trigBasis (2 * k) 0 = 2

    φ_{2k}(0) = √2 · cos(0) = √2.

    theorem Chapter3.trigBasis_even_at_one (k : ) (hk : 1 k) :
    trigBasis (2 * k) 1 = 2

    φ_{2k}(1) = √2 · cos(2πk) = √2.

    theorem Chapter3.trigBasis_odd_at_zero (k : ) (hk : 1 k) :
    trigBasis (2 * k + 1) 0 = 0

    φ_{2k+1}(0) = √2 · sin(0) = 0.

    theorem Chapter3.trigBasis_odd_at_one (k : ) (hk : 1 k) :
    trigBasis (2 * k + 1) 1 = 0

    φ_{2k+1}(1) = √2 · sin(2πk) = 0.

    theorem Chapter3.ibp_cos_step (f : ) (β : ) (L : ) (hf : f SobolevClassFn β L) (j : ) (hj : 1 j) (hjβ : j β) (k : ) (hk : 1 k) :
    derivFourierCoeff f j (2 * k) = 2 * Real.pi * k * derivFourierCoeff f (j - 1) (2 * k + 1)

    Integration by parts for Fourier coefficients: the cos case. ∫₀¹ f^(j)(t) · √2 cos(2πkt) dt = [f^(j-1)(t) · √2 cos(2πkt)]₀¹ + (2πk) ∫₀¹ f^(j-1)(t) · √2 sin(2πkt) dt = 0 + (2πk) · s_{2k+1}(j-1) The boundary term vanishes by cos(2πk) = 1 and periodic BC. This is an application of integration by parts (a standard tool not proved in the book) to the specific integrals defining Fourier coefficients.

    theorem Chapter3.ibp_sin_step (f : ) (β : ) (L : ) (hf : f SobolevClassFn β L) (j : ) (hj : 1 j) (hjβ : j β) (k : ) (hk : 1 k) :
    derivFourierCoeff f j (2 * k + 1) = -(2 * Real.pi * k) * derivFourierCoeff f (j - 1) (2 * k)

    Integration by parts for Fourier coefficients: the sin case. ∫₀¹ f^(j)(t) · √2 sin(2πkt) dt = [f^(j-1)(t) · √2 sin(2πkt)]₀¹ - (2πk) ∫₀¹ f^(j-1)(t) · √2 cos(2πkt) dt = 0 - (2πk) · s_{2k}(j-1) The boundary term vanishes by sin(2πk) = sin(0) = 0. This is an application of integration by parts (a standard tool not proved in the book) to the specific integrals defining Fourier coefficients.

    theorem Chapter3.ibp_recurrence (f : ) (β : ) (L : ) (hf : f SobolevClassFn β L) (j : ) (hj : 1 j) (hjβ : j β) (k : ) (hk : 1 k) :
    derivFourierCoeff f j (2 * k) = 2 * Real.pi * k * derivFourierCoeff f (j - 1) (2 * k + 1) derivFourierCoeff f j (2 * k + 1) = -(2 * Real.pi * k) * derivFourierCoeff f (j - 1) (2 * k)

    Integration by parts recurrence for Fourier coefficients of derivatives (Book lines 2319–2326). For f ∈ W(β, L) and 1 ≤ j ≤ β, k ≥ 1: s_{2k}(j) = (2πk) s_{2k+1}(j-1) and s_{2k+1}(j) = -(2πk) s_{2k}(j-1). Proof: integration by parts using periodic boundary conditions. Proof: integration by parts using periodic boundary conditions (ibp_cos_step and ibp_sin_step).

    Step 2: Induction result (Book line 2334) #

    From the IBP recurrence, by induction on β: s_{2k}(β)² + s_{2k+1}(β)² = (2πk)^{2β} · (θ_{2k}² + θ_{2k+1}²) where θ_j = s_j(0) are the Fourier coefficients of f.

    theorem Chapter3.ibp_sq_step (f : ) (β : ) (L : ) (hf : f SobolevClassFn β L) (j : ) (hj : 1 j) (hjβ : j β) (k : ) (hk : 1 k) :
    derivFourierCoeff f j (2 * k) ^ 2 + derivFourierCoeff f j (2 * k + 1) ^ 2 = (2 * Real.pi * k) ^ 2 * (derivFourierCoeff f (j - 1) (2 * k) ^ 2 + derivFourierCoeff f (j - 1) (2 * k + 1) ^ 2)

    Induction on the IBP recurrence (Book line 2330): s_{2k}(j)² + s_{2k+1}(j)² = (2πk)² · [s_{2k}(j-1)² + s_{2k+1}(j-1)²]. Follows directly from the IBP recurrence by squaring and adding.

    theorem Chapter3.ibp_induction_sq (f : ) (β : ) ( : 1 β) (L : ) (hf : f SobolevClassFn β L) (k : ) (hk : 1 k) :
    derivFourierCoeff f β (2 * k) ^ 2 + derivFourierCoeff f β (2 * k + 1) ^ 2 = (2 * Real.pi * k) ^ (2 * β) * (derivFourierCoeff f 0 (2 * k) ^ 2 + derivFourierCoeff f 0 (2 * k + 1) ^ 2)

    By induction on β (Book line 2334): s_{2k}(β)² + s_{2k+1}(β)² = (2πk)^{2β} · (θ_{2k}² + θ_{2k+1}²) where θ_j = s_j(0) = derivFourierCoeff f 0 j.

    theorem Chapter3.fourier_deriv_identity (β : ) (k : ) (_hk : 1 k) (s_even s_odd θ_even θ_odd : ) (hIBP : s_even ^ 2 + s_odd ^ 2 = (2 * Real.pi * k) ^ (2 * β) * (θ_even ^ 2 + θ_odd ^ 2)) :
    s_even ^ 2 + s_odd ^ 2 = Real.pi ^ (2 * β) * (sobolevCoeff β (2 * k) ^ 2 * θ_even ^ 2 + sobolevCoeff β (2 * k + 1) ^ 2 * θ_odd ^ 2)

    Key identity (Theorem 3.11 proof, by IBP induction): s_{2k}(β)² + s_{2k+1}(β)² = (2πk)^{2β}(θ_{2k}² + θ_{2k+1}²) implies the Sobolev coefficient form = π^{2β}(a_{2k}² θ_{2k}² + a_{2k+1}² θ_{2k+1}²).

    Step 3: Parseval's identity for derivatives (Book line 2343) #

    Parseval's identity applied to f^(β) ∈ L₂([0,1]): ∫₀¹ (f^(β)(t))² dt = Σ_{k=1}^∞ s_k(β)² This is a standard result for orthonormal bases in L₂.

    theorem Chapter3.trigBasis_orthonormal (i j : ) (hi : 1 i) (hj : 1 j) :
    (x : ) in Set.Icc 0 1, trigBasis i x * trigBasis j x = if i = j then 1 else 0

    Orthonormality of the trigonometric basis (standard integral computation, not proved in the book). For i, j ≥ 1: ∫₀¹ φ_i(x) φ_j(x) dx = δ_{ij} This is a direct computation using the integrals of products of sin/cos functions on [0,1]. The book assumes this as a known property of the trigonometric system.

    trigBasis is continuous for each j.

    theorem Chapter3.partialFourierSum_continuous (c : ) (N : ) :
    Continuous fun (x : ) => kFinset.range N, c k * trigBasis (k + 1) x

    The partial Fourier sum is continuous.

    Continuous functions are integrable on Icc 0 1.

    If g² is integrable and g is AEStronglyMeasurable on Icc 0 1, then g is integrable on Icc 0 1 (L² ⊂ L¹ on finite measure spaces).

    theorem Chapter3.trigBasis_L2_error_eq (g : ) (hg : MeasureTheory.IntegrableOn (fun (x : ) => g x ^ 2) (Set.Icc 0 1) MeasureTheory.volume) (hg_int : MeasureTheory.IntegrableOn g (Set.Icc 0 1) MeasureTheory.volume) (N : ) :
    (x : ) in Set.Icc 0 1, (g x - kFinset.range N, ( (t : ) in Set.Icc 0 1, g t * trigBasis (k + 1) t) * trigBasis (k + 1) x) ^ 2 = ( (x : ) in Set.Icc 0 1, g x ^ 2) - kFinset.range N, ( (x : ) in Set.Icc 0 1, g x * trigBasis (k + 1) x) ^ 2

    L² error formula via orthonormality (not proved in the book). For g ∈ L²([0,1]), the L² error of the N-th partial Fourier sum equals the L² norm minus the sum of squared Fourier coefficients: ∫₀¹ (g - Σ_{k=1}^N c_k φ_k)² dx = ∫₀¹ g² dx - Σ_{k=1}^N c_k² where c_k = ∫₀¹ g φ_k dx. This follows by expanding the square and using orthonormality of {φ_k}. Proof by induction on N: the base case is trivial, and the induction step uses the algebraic identity (a - b - c)² = (a-b)² - 2c(a-b) + c² together with orthonormality to evaluate the cross terms.

    theorem Chapter3.trigBasis_L2_convergence_axiom (g : ) (hg : MeasureTheory.IntegrableOn (fun (x : ) => g x ^ 2) (Set.Icc 0 1) MeasureTheory.volume) (hmean : (x : ) in Set.Icc 0 1, g x = 0) :
    Filter.Tendsto (fun (N : ) => (x : ) in Set.Icc 0 1, (g x - jFinset.range N, ( (t : ) in Set.Icc 0 1, g t * trigBasis (j + 1) t) * trigBasis (j + 1) x) ^ 2) Filter.atTop (nhds 0)

    L² convergence of the trigonometric Fourier series (axiom). For a mean-zero square-integrable function g on [0,1], the partial Fourier sums (over the non-constant trig basis elements φ₁, φ₂, ...) converge to g in L² norm. The mean-zero hypothesis is essential: the sum excludes the constant basis element trigBasis 0 = 1, so the limit captures all of ‖g‖² only when ⟨g, 1⟩ = ∫g = 0.

    The book states L² completeness of the full trig system at lines 2297–2299 without proof. Mathlib proves the analogous result for complex Fourier series on AddCircle T (hasSum_fourier_series_L2), but bridging from that to this real formulation requires substantial infrastructure.

    theorem Chapter3.trigBasis_L2_approx (g : ) (hg : MeasureTheory.IntegrableOn (fun (x : ) => g x ^ 2) (Set.Icc 0 1) MeasureTheory.volume) (hmean : (x : ) in Set.Icc 0 1, g x = 0) (ε : ) ( : 0 < ε) :
    ∃ (M : ), ∀ (N : ), M N (x : ) in Set.Icc 0 1, (g x - jFinset.range N, ( (t : ) in Set.Icc 0 1, g t * trigBasis (j + 1) t) * trigBasis (j + 1) x) ^ 2 < ε

    L₂ completeness of the trigonometric system (ε-δ form) (not proved in the book). For any mean-zero square-integrable function g on [0,1] and any ε > 0, the Fourier partial sum approximation error eventually stays below ε. The mean-zero hypothesis is needed because the sum excludes trigBasis 0. Proved from trigBasis_L2_convergence_axiom via Metric.tendsto_atTop.

    theorem Chapter3.trigBasis_L2_completeness (g : ) (hg : MeasureTheory.IntegrableOn (fun (x : ) => g x ^ 2) (Set.Icc 0 1) MeasureTheory.volume) (hmean : (x : ) in Set.Icc 0 1, g x = 0) :
    Filter.Tendsto (fun (N : ) => (x : ) in Set.Icc 0 1, (g x - jFinset.range N, ( (t : ) in Set.Icc 0 1, g t * trigBasis (j + 1) t) * trigBasis (j + 1) x) ^ 2) Filter.atTop (nhds 0)

    L₂ completeness of the trigonometric system (not proved in the book). For any mean-zero square-integrable function g on [0,1], the partial Fourier sums (excluding the constant term) converge to g in L₂ norm. The mean-zero hypothesis is needed because the sum excludes trigBasis 0. Follows from trigBasis_L2_approx via Metric.tendsto_atTop.

    theorem Chapter3.parseval_L2_trigBasis (g : ) (hg : MeasureTheory.IntegrableOn (fun (x : ) => g x ^ 2) (Set.Icc 0 1) MeasureTheory.volume) (hg_int : MeasureTheory.IntegrableOn g (Set.Icc 0 1) MeasureTheory.volume) (hmean : (x : ) in Set.Icc 0 1, g x = 0) :
    (x : ) in Set.Icc 0 1, g x ^ 2 = ∑' (k : ), ( (x : ) in Set.Icc 0 1, g x * trigBasis (k + 1) x) ^ 2

    Parseval's identity for L₂([0,1]) with the trigonometric ONB. For any square-integrable function g on [0,1]: ∫₀¹ g(x)² dx = ∑_{k≥1} (∫₀¹ g(x) φ_k(x) dx)² The book invokes this identity at line 2343 ("Together with the Parseval identity") without proof.

    Proof structure: From orthonormality of {φ_k} (trigBasis_orthonormal), the L² error satisfies ∫(g - S_N)² = ∫g² - Σ_{k≤N} c_k² (trigBasis_L2_error_eq). By completeness (trigBasis_L2_completeness), ∫(g - S_N)² → 0. Therefore Σ c_k² → ∫g², giving the Parseval identity.

    theorem Chapter3.parseval_derivative (f : ) (β : ) (_hβ : 1 β) (L : ) (hf : f SobolevClassFn β L) :
    (x : ) in Set.Icc 0 1, iteratedDeriv β f x ^ 2 = ∑' (k : ), derivFourierCoeff f β (k + 1) ^ 2

    Parseval's identity for f^(β): the L₂ norm of the β-th derivative equals the sum of squares of its Fourier coefficients (Book line 2343). This is a standard Hilbert space result for the trigonometric ONB.

    Step 4: Combining Parseval + IBP + coefficient identity (Book line 2343) #

    The key formula: ∫₀¹ (f^(β))² dt = π^{2β} · Σ_{j≥1} a_j² θ_j²

    This combines:

    theorem Chapter3.parity_regroup_sum' (f g : ) (h0 : f 0 = g 0) (hpair : ∀ (k : ), f (2 * k + 1) + f (2 * (k + 1)) = g (2 * k + 1) + g (2 * (k + 1))) (hfs : Summable f) (hgs : Summable g) :
    ∑' (k : ), f k = ∑' (k : ), g k

    Parity regrouping: if two summable sequences agree on pair sums (f(2k+1) + f(2k+2) = g(2k+1) + g(2k+2)) and have the same first term, then their total sums agree. This is used to match the IBP-derived pairs.

    Companion function for parity regrouping: swaps adjacent odd/even indices. companion(0) = 0, companion(2k+1) = 2(k+1), companion(2(k+1)) = 2k+1.

    Instances For
      theorem Chapter3.summable_of_pair_eq (f g : ) (hf_nn : ∀ (k : ), 0 f k) (hg_nn : ∀ (k : ), 0 g k) (hf_sum : Summable f) (h0 : f 0 = g 0) (hpair : ∀ (k : ), f (2 * k + 1) + f (2 * (k + 1)) = g (2 * k + 1) + g (2 * (k + 1))) :

      Summability from pair identity: if two nonneg sequences agree on pair sums and at index 0, and one is summable, then so is the other.

      theorem Chapter3.parseval_summable (g : ) (hg : MeasureTheory.IntegrableOn (fun (x : ) => g x ^ 2) (Set.Icc 0 1) MeasureTheory.volume) (hg_int : MeasureTheory.IntegrableOn g (Set.Icc 0 1) MeasureTheory.volume) (hmean : (x : ) in Set.Icc 0 1, g x = 0) :
      Summable fun (k : ) => ( (x : ) in Set.Icc 0 1, g x * trigBasis (k + 1) x) ^ 2

      Summability of Fourier coefficients squared, extracted from Bessel's inequality. For a square-integrable function g on [0,1], the sequence (∫ g · φ_{k+1})² is summable, bounded by ∫ g².

      theorem Chapter3.series_parity_regroup (f : ) (β : ) ( : 1 β) (L : ) (hf : f SobolevClassFn β L) (θ : ) ( : ∀ (j : ), θ j = derivFourierCoeff f 0 j) :
      ∑' (k : ), derivFourierCoeff f β (k + 1) ^ 2 = Real.pi ^ (2 * β) * ∑' (j : ), sobolevCoeff (↑β) (j + 1) ^ 2 * θ (j + 1) ^ 2

      Series regrouping: the sum of squares of derivative Fourier coefficients ∑{k≥1} s_k(β)² equals π^{2β} ∑{j≥1} a_j² θ_j². This combines:

      • s₁(β) = 0 (by periodic BC: ∫₀¹ f^(β)(t) dt = f^(β-1)(1) - f^(β-1)(0) = 0)
      • IBP induction: s_{2k}(β)² + s_{2k+1}(β)² = (2πk)^{2β}(θ_{2k}² + θ_{2k+1}²)
      • Coefficient identity: (2πk)^{2β} = π^{2β} · a_{2k}² (resp. a_{2k+1}²)
      • Regrouping: ∑{j≥1} = a₁²θ₁² + ∑{k≥1}(a_{2k}²θ_{2k}² + a_{2k+1}²θ_{2k+1}²), with a₁=0. The regrouping of an absolutely convergent series by parity is a standard analysis fact not proved in the book.
      theorem Chapter3.parseval_sobolev_coeff_identity (f : ) (β : ) ( : 1 β) (L : ) (hf : f SobolevClassFn β L) (θ : ) ( : ∀ (j : ), θ j = derivFourierCoeff f 0 j) :
      (x : ) in Set.Icc 0 1, iteratedDeriv β f x ^ 2 = Real.pi ^ (2 * β) * ∑' (j : ), sobolevCoeff (↑β) (j + 1) ^ 2 * θ (j + 1) ^ 2

      The combined Parseval–IBP–coefficient identity (Book line 2343): ∫₀¹ (f^(β)(t))² dt = π^{2β} · Σ_{j≥1} a_j² θ_j² where θ_j = s_j(0) are the Fourier coefficients of f.

      This is the analytical core of Theorem 3.11, combining:

      • Parseval's identity for f^(β),
      • the IBP induction s_{2k}(β)² + s_{2k+1}(β)² = (2πk)^{2β}(θ_{2k}² + θ_{2k+1}²),
      • the rewriting (2πk)^{2β} = π^{2β} · a_{2k}² (and a_{2k+1}²).

      The series regrouping (parity decomposition) is captured in series_parity_regroup.

      Part A: Fourier series representation (Book lines 2297-2299) #

      f ∈ W(β, L) can be represented as f = Σ θ_j* φ_j (convergence in L₂). This is a consequence of the completeness of the trigonometric system.

      theorem Chapter3.trigBasis_L2_full_convergence_axiom (g : ) (hg : MeasureTheory.IntegrableOn (fun (x : ) => g x ^ 2) (Set.Icc 0 1) MeasureTheory.volume) :
      Filter.Tendsto (fun (N : ) => (x : ) in Set.Icc 0 1, (g x - jFinset.range N, ( (t : ) in Set.Icc 0 1, g t * trigBasis j t) * trigBasis j x) ^ 2) Filter.atTop (nhds 0)

      L² convergence of the full trigonometric Fourier series (axiom). For any square-integrable function g on [0,1], the partial sums over the full trigonometric basis {φ₀, φ₁, φ₂, ...} = {1, √2cos(2πx), √2sin(2πx), ...} converge to g in L² norm. Unlike trigBasis_L2_convergence_axiom, this includes the constant basis element trigBasis 0 = 1, so no mean-zero hypothesis is needed.

      The book states this at lines 2297–2299 without proof.

      theorem Chapter3.sobolev_fourier_representation (β : ) (_hβ : 1 β) (L : ) (_hL : 0 < L) (f : ) (hf : f SobolevClassFn β L) :
      Filter.Tendsto (fun (N : ) => (x : ) in Set.Icc 0 1, (f x - jFinset.range N, derivFourierCoeff f 0 j * trigBasis j x) ^ 2) Filter.atTop (nhds 0)

      Theorem 3.11, Part A (Fourier series representation). For f ∈ W(β, L), there exists a sequence θ of Fourier coefficients θ_j = ∫₀¹ f(t)φ_j(t)dt such that f = Σ θ_j φ_j in L₂([0,1]), i.e., ∫₀¹ |f(t) - Σ_{j=0}^{N-1} θ_j φ_j(t)|² dt → 0 as N → ∞. Here the sum includes the constant basis element φ₀ = 1.

      This is a standard consequence of {φ_j} being an orthonormal basis of L₂([0,1]): every L₂ function can be expanded in the basis. Proof: Follows from the L₂ completeness of the full trigonometric system (trigBasis_L2_full_convergence_axiom), which is not proved in the book.

      Part B: Main theorem — ellipsoid bound (Book lines 2345-2349) #

      theorem Chapter3.sobolev_fourier_ellipsoid (β : ) ( : 1 β) (L : ) (_hL : 0 < L) (f : ) (hf : f SobolevClassFn β L) (θ : ) ( : ∀ (j : ), θ j = derivFourierCoeff f 0 j) :
      ∑' (j : ), sobolevCoeff (↑β) (j + 1) ^ 2 * θ (j + 1) ^ 2 L ^ 2 / Real.pi ^ (2 * β)

      Theorem 3.11, Part B (Sobolev class ⊂ Fourier ellipsoid). If f ∈ W(β, L), then its Fourier coefficients θ_j = ⟨f, φ_j⟩ satisfy Σ_{j≥1} a_j² θ_j² ≤ L²/π^{2β}, i.e., θ ∈ Θ(β, L²/π^{2β}).

      Proof: By the Parseval–IBP identity (parseval_sobolev_coeff_identity), ∫₀¹ (f^(β))² = π^{2β} Σ a_j² θ_j². Since f ∈ W(β,L), ∫₀¹ (f^(β))² ≤ L², giving Σ a_j² θ_j² ≤ L²/π^{2β}.

      theorem Chapter3.sobolev_fourier_ellipsoid_fin (β : ) (_hβ : 1 β) (L : ) (_hL : 0 < L) (M : ) (θ : Fin M) (hParseval : Real.pi ^ (2 * β) * j : Fin M, sobolevCoeff (↑β) (j + 1) ^ 2 * θ j ^ 2 L ^ 2) :
      θ SobolevEllipsoid (↑β) (L ^ 2 / Real.pi ^ (2 * β)) M

      Finite-dimensional corollary: the truncated coefficients lie in the finite Sobolev ellipsoid.

      theorem Chapter3.thm_3_11 (β : ) ( : 1 β) (L : ) (hL : 0 < L) (f : ) (hf : f SobolevClassFn β L) :
      Filter.Tendsto (fun (N : ) => (x : ) in Set.Icc 0 1, (f x - jFinset.range N, derivFourierCoeff f 0 j * trigBasis j x) ^ 2) Filter.atTop (nhds 0) ∀ (θ : ), (∀ (j : ), θ j = derivFourierCoeff f 0 j)∑' (j : ), sobolevCoeff (↑β) (j + 1) ^ 2 * θ (j + 1) ^ 2 L ^ 2 / Real.pi ^ (2 * β)

      Theorem 3.11 (Sobolev Fourier representation and ellipsoid membership). For f ∈ W(β, L): (A) f can be represented as f = Σ θ_j φ_j (convergence in L²), where θ_j = ∫₀¹ f(t)φ_j(t) dt are the Fourier coefficients; and (B) the sequence θ belongs to the Sobolev ellipsoid Θ(β, L²/π^{2β}), i.e., Σ_{j≥1} a_j² θ_j² ≤ L²/π^{2β}.

      This bundles sobolev_fourier_representation (Part A) and sobolev_fourier_ellipsoid (Part B) into a single combined statement.