The Cohn–Elkies exponent and sign uncertainty

6.2. Existence of extremizers🔗

The existence part of Theorem 1.4 of Cohn–Gonçalves (2019), used in Theorem 6.1.9, following their §3.2 with the modifications described at the beginning of the chapter.

Definition6.2.1
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Definition 6.1.1
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Definition 6.2.2
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(Cohn–Gonçalves 2019, (3.1).) For t > 0 let \varphi_t(x) = \dfrac{e^{-t\pi|x|^2} - e^{-2t\pi|x|^2}}{t^{-d/2} - (2t)^{-d/2}}.

Lean code for Definition6.2.1●1 definition
  • def CohnElkies.gaussianDifference (d : ℕ) (t : ℝ)
      (x : CohnElkies.Euclidean d) : ℝ
    def CohnElkies.gaussianDifference (d : ℕ)
      (t : ℝ) (x : CohnElkies.Euclidean d) : ℝ
    Cohn–Gonçalves (3.1): the Gaussian difference
    `φ_t(x) = (e^{-tπ|x|²} - e^{-2tπ|x|²}) / (t^{-d/2} - (2t)^{-d/2})`. 
Definition6.2.2
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Definition 6.1.1
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Lemma 6.2.4
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✓L∃∀N

With \varphi_t as in Definition 6.2.1, let \psi_t = \varphi_t - \widehat{\varphi_t}.

Lean code for Definition6.2.2●1 definition
  • def CohnElkies.gaussianPerturbation (d : ℕ) (t : ℝ)
      (x : CohnElkies.Euclidean d) : ℝ
    def CohnElkies.gaussianPerturbation (d : ℕ)
      (t : ℝ) (x : CohnElkies.Euclidean d) : ℝ
    `ψ_t = φ_t - 𝓕φ_t` (Cohn–Gonçalves, proof of Lemma 3.1 and §3.3): `𝓕ψ_t = -ψ_t`,
    `ψ_t(0) = -1`, and `ψ_t > 0` outside the ball of radius `√(t d log 2 / π)`. 
Lemma6.2.3
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Definition 6.1.1
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Let d \ge 1 and t > 0, with \varphi_t as in Definition 6.2.1. Then \widehat{\varphi_t}(\xi) = \dfrac{t^{-d/2}e^{-\pi|\xi|^2/t} - (2t)^{-d/2}e^{-\pi|\xi|^2/(2t)}}{t^{-d/2} - (2t)^{-d/2}}, \varphi_t \ge 0, \varphi_t(0) = 0, \widehat{\varphi_t}(0) = 1, \widehat{\widehat{\varphi_t}} = \varphi_t, and \widehat{\varphi_t}(\xi) < 0 whenever |\xi|^2 > t\,d\log 2/\pi (nonpositive when \ge).

Lean code for Lemma6.2.3●6 theorems
  • theorem CohnElkies.fourier_gaussianDifference {d : ℕ} {t : ℝ} (ht : 0 < t)
      (ξ : CohnElkies.Euclidean d) :
      FourierTransform.fourier
          (fun x ↦ ↑(CohnElkies.gaussianDifference d t x)) ξ =
        ↑(CohnElkies.fourierGaussianDifference d t ξ)
    theorem CohnElkies.fourier_gaussianDifference
      {d : ℕ} {t : ℝ} (ht : 0 < t)
      (ξ : CohnElkies.Euclidean d) :
      FourierTransform.fourier
          (fun x ↦
            ↑(CohnElkies.gaussianDifference d
                t x))
          ξ =
        ↑(CohnElkies.fourierGaussianDifference
            d t ξ)
    `𝓕φ_t(ξ) = (t^{-d/2} e^{-π|ξ|²/t} - (2t)^{-d/2} e^{-π|ξ|²/(2t)}) / (t^{-d/2} - (2t)^{-d/2})`. 
  • theorem CohnElkies.gaussianDifference_nonneg {d : ℕ} (hd : 0 < d) {t : ℝ}
      (ht : 0 < t) (x : CohnElkies.Euclidean d) :
      0 ≤ CohnElkies.gaussianDifference d t x
    theorem CohnElkies.gaussianDifference_nonneg
      {d : ℕ} (hd : 0 < d) {t : ℝ}
      (ht : 0 < t)
      (x : CohnElkies.Euclidean d) :
      0 ≤ CohnElkies.gaussianDifference d t x
    `φ_t ≥ 0` for `t > 0`, `d ≥ 1`. 
  • theorem CohnElkies.gaussianDifference_apply_zero {d : ℕ} (t : ℝ) :
      CohnElkies.gaussianDifference d t 0 = 0
    theorem CohnElkies.gaussianDifference_apply_zero
      {d : ℕ} (t : ℝ) :
      CohnElkies.gaussianDifference d t 0 = 0
  • theorem CohnElkies.fourier_gaussianDifference_zero {d : ℕ} (hd : 0 < d) {t : ℝ}
      (ht : 0 < t) :
      FourierTransform.fourier
          (fun x ↦ ↑(CohnElkies.gaussianDifference d t x)) 0 =
        1
    theorem CohnElkies.fourier_gaussianDifference_zero
      {d : ℕ} (hd : 0 < d) {t : ℝ}
      (ht : 0 < t) :
      FourierTransform.fourier
          (fun x ↦
            ↑(CohnElkies.gaussianDifference d
                t x))
          0 =
        1
    `𝓕φ_t(0) = 1`. 
  • theorem CohnElkies.fourier_fourier_gaussianDifference {d : ℕ} {t : ℝ}
      (ht : 0 < t) (ξ : CohnElkies.Euclidean d) :
      FourierTransform.fourier
          (FourierTransform.fourier fun x ↦
            ↑(CohnElkies.gaussianDifference d t x))
          ξ =
        ↑(CohnElkies.gaussianDifference d t ξ)
    theorem CohnElkies.fourier_fourier_gaussianDifference
      {d : ℕ} {t : ℝ} (ht : 0 < t)
      (ξ : CohnElkies.Euclidean d) :
      FourierTransform.fourier
          (FourierTransform.fourier fun x ↦
            ↑(CohnElkies.gaussianDifference d
                t x))
          ξ =
        ↑(CohnElkies.gaussianDifference d t ξ)
    `𝓕 (𝓕 φ_t) = φ_t` (`φ_t` is even). 
  • theorem CohnElkies.fourierGaussianDifference_neg_of_lt {d : ℕ} (hd : 0 < d)
      {t : ℝ} (ht : 0 < t) {ξ : CohnElkies.Euclidean d}
      (h : t * ↑d * Real.log 2 / Real.pi < ‖ξ‖ ^ 2) :
      CohnElkies.fourierGaussianDifference d t ξ < 0
    theorem CohnElkies.fourierGaussianDifference_neg_of_lt
      {d : ℕ} (hd : 0 < d) {t : ℝ}
      (ht : 0 < t)
      {ξ : CohnElkies.Euclidean d}
      (h :
        t * ↑d * Real.log 2 / Real.pi <
          ‖ξ‖ ^ 2) :
      CohnElkies.fourierGaussianDifference d t
          ξ <
        0
    `𝓕φ_t(ξ) < 0` when `|ξ|² > t d log 2 / π` (Cohn–Gonçalves, proof of Lemma 3.1). 
Proof for Lemma 6.2.3
uses 0

The Fourier transform of e^{-b\pi|x|^2} is b^{-d/2}e^{-\pi|\xi|^2/b}, which gives the formula; taking logarithms, t^{-d/2}e^{-\pi|\xi|^2/t} < (2t)^{-d/2}e^{-\pi|\xi|^2/(2t)} if and only if \pi|\xi|^2/(2t) > (d/2)\log 2, i.e. |\xi|^2 > t\,d\log 2/\pi. Applying the transform formula twice gives \widehat{\widehat{\varphi_t}} = \varphi_t.

Lemma6.2.4
Group: Comparison of the constants (20)
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Definition 6.1.1
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Lemma 6.2.5
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✓L∃∀N

Let d \ge 1 and t > 0, with \psi_t as in Definition 6.2.2. Then \widehat{\psi_t} = -\psi_t, \psi_t(0) = -1, and \psi_t > 0 outside the ball of radius \sqrt{t\,d\log 2/\pi}.

Lean code for Lemma6.2.4●3 theorems
  • theorem CohnElkies.fourier_gaussianPerturbation {d : ℕ} {t : ℝ} (ht : 0 < t)
      (ξ : CohnElkies.Euclidean d) :
      FourierTransform.fourier
          (fun x ↦ ↑(CohnElkies.gaussianPerturbation d t x)) ξ =
        -↑(CohnElkies.gaussianPerturbation d t ξ)
    theorem CohnElkies.fourier_gaussianPerturbation
      {d : ℕ} {t : ℝ} (ht : 0 < t)
      (ξ : CohnElkies.Euclidean d) :
      FourierTransform.fourier
          (fun x ↦
            ↑(CohnElkies.gaussianPerturbation
                d t x))
          ξ =
        -↑(CohnElkies.gaussianPerturbation d t
              ξ)
    `𝓕ψ_t = -ψ_t`. 
  • theorem CohnElkies.gaussianPerturbation_apply_zero {d : ℕ} (hd : 0 < d) {t : ℝ}
      (ht : 0 < t) : CohnElkies.gaussianPerturbation d t 0 = -1
    theorem CohnElkies.gaussianPerturbation_apply_zero
      {d : ℕ} (hd : 0 < d) {t : ℝ}
      (ht : 0 < t) :
      CohnElkies.gaussianPerturbation d t 0 =
        -1
  • theorem CohnElkies.gaussianPerturbation_pos {d : ℕ} (hd : 0 < d) {t : ℝ}
      (ht : 0 < t) {x : CohnElkies.Euclidean d}
      (h : t * ↑d * Real.log 2 / Real.pi < ‖x‖ ^ 2) :
      0 < CohnElkies.gaussianPerturbation d t x
    theorem CohnElkies.gaussianPerturbation_pos
      {d : ℕ} (hd : 0 < d) {t : ℝ}
      (ht : 0 < t)
      {x : CohnElkies.Euclidean d}
      (h :
        t * ↑d * Real.log 2 / Real.pi <
          ‖x‖ ^ 2) :
      0 <
        CohnElkies.gaussianPerturbation d t x
    `ψ_t > 0` when `|ξ|² > t d log 2 / π`. 
Proof for Lemma 6.2.4

Immediate from Lemma 6.2.3: \widehat{\psi_t} = \widehat{\varphi_t} - \varphi_t = -\psi_t, \psi_t(0) = 0 - 1, and \psi_t = \varphi_t - \widehat{\varphi_t} > 0 where \widehat{\varphi_t} < 0.

Lemma6.2.5
Group: Comparison of the constants (20)
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Definition 6.1.1
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Definition 1.2.1
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(Cohn–Gonçalves 2019, Lemma 3.1, last paragraph.) Let d \ge 1, R > 0, and let g \in L^1(\mathbb{R}^d;\mathbb{R}) satisfy \widehat g = -g pointwise, g \ne 0, g \ge 0 on \{|x| \ge R\} and g(0) \ge 0. With t = \pi R^2/(d\log 2) and \psi_t as in Definition 6.2.2, the function h = g + g(0)\psi_t belongs to \mathcal{E}_-(d) (Definition 1.2.1) and satisfies h \ge 0 on \{|x| \ge R\}, so r(h) \le R; moreover h = g if g(0) = 0.

Lean code for Lemma6.2.5●3 declarations
  • def CohnElkies.originCorrection {d : ℕ} (hd : 0 < d)
      (g : CohnElkies.Euclidean d → ℝ)
      (hint : MeasureTheory.Integrable g MeasureTheory.volume)
      (hfour :
        ∀ (ξ : CohnElkies.Euclidean d),
          FourierTransform.fourier (fun x ↦ ↑(g x)) ξ = -↑(g ξ))
      (hne : g ≠ 0) {R : ℝ} (hR : 0 < R)
      (hpos : ∀ (x : CohnElkies.Euclidean d), R ≤ ‖x‖ → 0 ≤ g x)
      (h0 : 0 ≤ g 0) : CohnElkies.SignEigenfunction d (-1)
    def CohnElkies.originCorrection {d : ℕ}
      (hd : 0 < d)
      (g : CohnElkies.Euclidean d → ℝ)
      (hint :
        MeasureTheory.Integrable g
          MeasureTheory.volume)
      (hfour :
        ∀ (ξ : CohnElkies.Euclidean d),
          FourierTransform.fourier
              (fun x ↦ ↑(g x)) ξ =
            -↑(g ξ))
      (hne : g ≠ 0) {R : ℝ} (hR : 0 < R)
      (hpos :
        ∀ (x : CohnElkies.Euclidean d),
          R ≤ ‖x‖ → 0 ≤ g x)
      (h0 : 0 ≤ g 0) :
      CohnElkies.SignEigenfunction d (-1)
    Cohn–Gonçalves, proof of Lemma 3.1 (last paragraph): the corrected function
    `h = g + g(0) (φ_t - 𝓕φ_t)`, `t d log 2 / π = R²`, is a sign eigenfunction of eigenvalue `-1`:
    `𝓕 h = -h` (since `𝓕 g = -g`, `𝓕𝓕φ_t = φ_t`), `h(0) = g(0) + g(0)(0 - 1) = 0`, and `h ≠ 0`
    (`h = g` if `g(0) = 0`; `h(x) > g(x) ≥ 0` for `|x| > R` if `g(0) > 0`). 
  • theorem CohnElkies.originCorrection_nonneg_outside {d : ℕ} (hd : 0 < d)
      (g : CohnElkies.Euclidean d → ℝ)
      (hint : MeasureTheory.Integrable g MeasureTheory.volume)
      (hfour :
        ∀ (ξ : CohnElkies.Euclidean d),
          FourierTransform.fourier (fun x ↦ ↑(g x)) ξ = -↑(g ξ))
      (hne : g ≠ 0) {R : ℝ} (hR : 0 < R)
      (hpos : ∀ (x : CohnElkies.Euclidean d), R ≤ ‖x‖ → 0 ≤ g x)
      (h0 : 0 ≤ g 0) (x : CohnElkies.Euclidean d) (hx : R ≤ ‖x‖) :
      0 ≤
        (CohnElkies.originCorrection hd g hint hfour hne hR hpos h0).toFun x
    theorem CohnElkies.originCorrection_nonneg_outside
      {d : ℕ} (hd : 0 < d)
      (g : CohnElkies.Euclidean d → ℝ)
      (hint :
        MeasureTheory.Integrable g
          MeasureTheory.volume)
      (hfour :
        ∀ (ξ : CohnElkies.Euclidean d),
          FourierTransform.fourier
              (fun x ↦ ↑(g x)) ξ =
            -↑(g ξ))
      (hne : g ≠ 0) {R : ℝ} (hR : 0 < R)
      (hpos :
        ∀ (x : CohnElkies.Euclidean d),
          R ≤ ‖x‖ → 0 ≤ g x)
      (h0 : 0 ≤ g 0)
      (x : CohnElkies.Euclidean d)
      (hx : R ≤ ‖x‖) :
      0 ≤
        (CohnElkies.originCorrection hd g hint
              hfour hne hR hpos h0).toFun
          x
    `h ≥ 0` outside the ball of radius `R`. 
  • theorem CohnElkies.originCorrection_eq_of_zero {d : ℕ} (hd : 0 < d)
      (g : CohnElkies.Euclidean d → ℝ)
      (hint : MeasureTheory.Integrable g MeasureTheory.volume)
      (hfour :
        ∀ (ξ : CohnElkies.Euclidean d),
          FourierTransform.fourier (fun x ↦ ↑(g x)) ξ = -↑(g ξ))
      (hne : g ≠ 0) {R : ℝ} (hR : 0 < R)
      (hpos : ∀ (x : CohnElkies.Euclidean d), R ≤ ‖x‖ → 0 ≤ g x)
      (h0 : 0 ≤ g 0) (h0' : g 0 = 0) :
      (CohnElkies.originCorrection hd g hint hfour hne hR hpos h0).toFun = g
    theorem CohnElkies.originCorrection_eq_of_zero
      {d : ℕ} (hd : 0 < d)
      (g : CohnElkies.Euclidean d → ℝ)
      (hint :
        MeasureTheory.Integrable g
          MeasureTheory.volume)
      (hfour :
        ∀ (ξ : CohnElkies.Euclidean d),
          FourierTransform.fourier
              (fun x ↦ ↑(g x)) ξ =
            -↑(g ξ))
      (hne : g ≠ 0) {R : ℝ} (hR : 0 < R)
      (hpos :
        ∀ (x : CohnElkies.Euclidean d),
          R ≤ ‖x‖ → 0 ≤ g x)
      (h0 : 0 ≤ g 0) (h0' : g 0 = 0) :
      (CohnElkies.originCorrection hd g hint
            hfour hne hR hpos h0).toFun =
        g
    `h = g` when `g(0) = 0`. 
Proof for Lemma 6.2.5

By Lemma 6.2.4, \widehat h = -g + g(0)(-\psi_t) = -h, h(0) = g(0) + g(0)\psi_t(0) = 0, and for |x| \ge R one has |x|^2 \ge t\,d\log 2/\pi, so \psi_t(x) \ge 0 and h(x) \ge g(x) \ge 0. If g(0) > 0 then h(x) > g(x) \ge 0 for |x| > R, so h \ne 0; if g(0) = 0 then h = g \ne 0.

Lemma6.2.6
Group: Comparison of the constants (20)
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Theorem 6.1.10
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✓L∃∀N

For every d \ge 1 and \varsigma = \pm 1, \mathsf{A}_\varsigma(d) > 0 (Definition 1.2.3).

Lean code for Lemma6.2.6●1 theorem
  • complete
    theorem CohnElkies.signUncertaintyConstant_pos {d : ℕ} (hd : 0 < d) (ς : ℤˣ) :
      0 < CohnElkies.signUncertaintyConstant ς d
    theorem CohnElkies.signUncertaintyConstant_pos
      {d : ℕ} (hd : 0 < d) (ς : ℤˣ) :
      0 <
        CohnElkies.signUncertaintyConstant ς d
    `A_ς(d) > 0` for `d ≥ 1` and both signs (Cohn–Gonçalves §3.1): no sign eigenfunction is
    nonnegative outside a ball of volume `< ½`. 
Proof for Lemma 6.2.6
uses 0

(Cohn–Gonçalves 2019, §3.1.) If g \in \mathcal{E}_\varsigma(d) with \|g\|_1 = 1 is nonnegative outside B_\rho, then \int g = \widehat g(0) = \varsigma g(0) = 0 gives \int g_- = \tfrac12, while g_- \le |g| \le \|\widehat g\|_1 = 1 vanishes outside B_\rho, so \tfrac12 \le \operatorname{vol}(B_\rho); choosing \rho with \operatorname{vol}(B_\rho) < \tfrac12 shows \mathsf{A}_\varsigma(d) \ge \rho > 0.

Lemma6.2.7
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For every d \ge 1, with \psi_t as in Definition 6.2.2, G = \psi_{1/4} - \psi_{1/2} belongs to \mathcal{E}_-(d) and is positive outside a ball, so r(G) < \infty.

Lean code for Lemma6.2.7●3 declarations
  • def CohnElkies.explicitSignEigenfunction {d : ℕ} (hd : 0 < d) :
      CohnElkies.SignEigenfunction d (-1)
    def CohnElkies.explicitSignEigenfunction
      {d : ℕ} (hd : 0 < d) :
      CohnElkies.SignEigenfunction d (-1)
    Cohn–Gonçalves, §3.3: `G = ψ_{1/4} - ψ_{1/2} ∈ 𝓔₋(d)`: `𝓕 G = -G` (as `𝓕ψ_t = -ψ_t`),
    `G(0) = -1 - (-1) = 0`, `G` is integrable, and `G ≠ 0` since `G > 0` outside the ball of radius
    `R(d)`. 
  • complete
    theorem CohnElkies.explicitEigenfunction_pos_of_le {d : ℕ} (hd : 0 < d)
      {x : CohnElkies.Euclidean d}
      (hx : CohnElkies.explicitEigenfunctionRadius d ≤ ‖x‖) :
      0 < CohnElkies.explicitEigenfunction d x
    theorem CohnElkies.explicitEigenfunction_pos_of_le
      {d : ℕ} (hd : 0 < d)
      {x : CohnElkies.Euclidean d}
      (hx :
        CohnElkies.explicitEigenfunctionRadius
            d ≤
          ‖x‖) :
      0 < CohnElkies.explicitEigenfunction d x
    `G(x) > 0` for `|x| ≥ R(d)`: then `|x|² ≥ (√L + 1)² > L = (4/π) log (1 + D/D' + 2^d)`. 
  • complete
    theorem CohnElkies.signRadius_explicitSignEigenfunction_lt_top {d : ℕ}
      (hd : 0 < d) :
      CohnElkies.signRadius
          (CohnElkies.explicitSignEigenfunction hd).toFun <
        ⊤
    theorem CohnElkies.signRadius_explicitSignEigenfunction_lt_top
      {d : ℕ} (hd : 0 < d) :
      CohnElkies.signRadius
          (CohnElkies.explicitSignEigenfunction
              hd).toFun <
        ⊤
    `r(G) < ∞`. 
Proof for Lemma 6.2.7

G satisfies \widehat G = -G and G(0) = -1 - (-1) = 0 (Lemma 6.2.4). Writing E_b(x) = e^{-\pi b|x|^2}, D = 2^d - 2^{d/2}, D' = 2^{d/2} - 1, \psi_{1/4} = (E_{1/4} - E_{1/2} - 2^dE_4 + 2^{d/2}E_2)/D and \psi_{1/2} = (E_{1/2} - 2^{d/2}E_2)/D', so that G \ge E_{1/4}\bigl(1 - e^{-\pi|x|^2/4}(1 + D/D' + 2^d)\bigr)/D > 0 once |x|^2 > (4/\pi)\log(1 + D/D' + 2^d); hence G \ne 0 and G \in \mathcal{E}_-(d).

Lemma6.2.8
Group: Comparison of the constants (20)
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Theorem 6.1.9
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✓L∃∀N

For every d \ge 1, \mathsf{A}_-(d) < \infty (Definition 1.2.3).

Lean code for Lemma6.2.8●1 theorem
  • complete
    theorem CohnElkies.signUncertaintyConstant_neg_one_lt_top {d : ℕ} (hd : 0 < d) :
      CohnElkies.signUncertaintyConstant (-1) d < ⊤
    theorem CohnElkies.signUncertaintyConstant_neg_one_lt_top
      {d : ℕ} (hd : 0 < d) :
      CohnElkies.signUncertaintyConstant (-1)
          d <
        ⊤
    `A₋(d) < ∞` for `d ≥ 1`: `A₋(d) ≤ r(G) < ∞` for the explicit `G ∈ 𝓔₋(d)`. 
Proof for Lemma 6.2.8

\mathsf{A}_-(d) \le r(G) < \infty for the explicit G of Lemma 6.2.7.

Lemma6.2.9
Group: Comparison of the constants (20)
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Lemma 6.2.10
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✓L∃∀N

Every bounded sequence (x_n) in a separable Hilbert space E has a weakly convergent subsequence: there are \varphi strictly increasing and y \in E with \|y\| \le \sup_n\|x_n\| and \langle x_{\varphi(n)}, z\rangle \to \langle y, z\rangle for every z \in E.

Lean code for Lemma6.2.9●1 theorem
  • theorem InnerProductSpace.tendsto_subseq_inner_left_of_norm_le.{u_2, u_3}
      (𝕜 : Type u_2) {E : Type u_3} [RCLike 𝕜] [NormedAddCommGroup E]
      [InnerProductSpace 𝕜 E] [CompleteSpace E]
      [TopologicalSpace.SeparableSpace E] {x : ℕ → E} {C : ℝ}
      (hx : ∀ (n : ℕ), ‖x n‖ ≤ C) :
      ∃ φ y,
        StrictMono φ ∧
          ‖y‖ ≤ C ∧
            ∀ (z : E),
              Filter.Tendsto (fun n ↦ inner 𝕜 (x (φ n)) z) Filter.atTop
                (nhds (inner 𝕜 y z))
    theorem InnerProductSpace.tendsto_subseq_inner_left_of_norm_le.{u_2,
        u_3}
      (𝕜 : Type u_2) {E : Type u_3} [RCLike 𝕜]
      [NormedAddCommGroup E]
      [InnerProductSpace 𝕜 E]
      [CompleteSpace E]
      [TopologicalSpace.SeparableSpace E]
      {x : ℕ → E} {C : ℝ}
      (hx : ∀ (n : ℕ), ‖x n‖ ≤ C) :
      ∃ φ y,
        StrictMono φ ∧
          ‖y‖ ≤ C ∧
            ∀ (z : E),
              Filter.Tendsto
                (fun n ↦ inner 𝕜 (x (φ n)) z)
                Filter.atTop
                (nhds (inner 𝕜 y z))
    Every bounded sequence in a separable Hilbert space has a weakly convergent subsequence: if
    `‖x n‖ ≤ C` for all `n`, there are a strictly increasing `φ` and `y` with `‖y‖ ≤ C` such that
    `⟪x (φ n), z⟫` converges to `⟪y, z⟫` for every `z`. 
Proof for Lemma 6.2.9
uses 0

By the Fréchet–Riesz theorem the functionals \langle x_n, \cdot\rangle lie in a closed ball of the dual E^*, which is weak-star sequentially compact for separable E (sequential Banach–Alaoglu, Mathlib's WeakDual.isSeqCompact_closedBall); transporting the limit functional back along the Riesz isometry gives y.

Lemma6.2.10
Group: Comparison of the constants (20)
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Definition 6.1.1
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Let V be a nontrivial finite-dimensional real inner product space, c \in \mathbb{C}\setminus\{0\} and R \ge 0. There is \kappa > 0 such that every integrable f : V \to \mathbb{C} with \widehat f = cf pointwise and \|f\|_1 = 1 satisfies \int_{|x| > R}|f| \ge \kappa.

Lean code for Lemma6.2.10●1 theorem
  • theorem Real.exists_pos_le_setIntegral_norm_compl_closedBall_of_fourier_eq_mul.{u_1}
      {V : Type u_1} [NormedAddCommGroup V] [InnerProductSpace ℝ V]
      [FiniteDimensional ℝ V] [MeasurableSpace V] [BorelSpace V]
      [Nontrivial V] {c : ℂ} (hc : c ≠ 0) (R : ℝ) :
      ∃ κ,
        0 < κ ∧
          ∀ (f : V → ℂ),
            MeasureTheory.Integrable f MeasureTheory.volume →
              (∀ (ξ : V), FourierTransform.fourier f ξ = c * f ξ) →
                ∫ (x : V), ‖f x‖ = 1 →
                  κ ≤ ∫ (x : V) in (Metric.closedBall 0 R)ᶜ, ‖f x‖
    theorem Real.exists_pos_le_setIntegral_norm_compl_closedBall_of_fourier_eq_mul.{u_1}
      {V : Type u_1} [NormedAddCommGroup V]
      [InnerProductSpace ℝ V]
      [FiniteDimensional ℝ V]
      [MeasurableSpace V] [BorelSpace V]
      [Nontrivial V] {c : ℂ} (hc : c ≠ 0)
      (R : ℝ) :
      ∃ κ,
        0 < κ ∧
          ∀ (f : V → ℂ),
            MeasureTheory.Integrable f
                MeasureTheory.volume →
              (∀ (ξ : V),
                  FourierTransform.fourier f
                      ξ =
                    c * f ξ) →
                ∫ (x : V), ‖f x‖ = 1 →
                  κ ≤
                    ∫ (x : V) in
                      (Metric.closedBall 0
                          R)ᶜ,
                      ‖f x‖
    **Eigenfunctions of the Fourier transform do not concentrate on a ball**: for `c ≠ 0` and
    `R : ℝ` there is `κ > 0` such that every integrable `f : V → ℂ` with `𝓕 f ξ = c * f ξ` for all
    `ξ` and `∫ ‖f‖ = 1` has `L¹` mass at least `κ` outside the closed ball of radius `R`. 
Proof for Lemma 6.2.10
Proof uses 2
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Lemma 3.2.12
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Suppose not: there are such f_n with \delta_n = \int_{B^c}|f_n| \to 0, B the closed ball of radius R. Each f_n = c^{-1}\widehat{f_n} is continuous with |f_n| \le |c|^{-1}. The truncations 1_Bf_n are bounded in L^2, so by Lemma 6.2.9 a subsequence converges weakly to some g \in L^2; testing against the kernels 1_B(x)e^{2\pi i\langle x,\xi\rangle} shows \widehat{1_Bf_n}(\xi) \to \widehat{1_Bg}(\xi) for every \xi, and |\widehat{f_n} - \widehat{1_Bf_n}| \le \delta_n, so f_n \to G := c^{-1}\widehat{1_Bg} pointwise, with G continuous. Bounded convergence on B gives \int_B|G| = \lim(1 - \delta_n) = 1; Fatou on B^c gives G = 0 a.e., hence everywhere, off B; and bounded convergence on B again gives \widehat G(\xi) = \lim\int_B e^{-2\pi i\langle x,\xi\rangle}f_n = \lim(\widehat{f_n}(\xi) + O(\delta_n)) = cG(\xi). Thus G and \widehat G are compactly supported and G \ne 0, contradicting Lemma 3.2.12.

Theorem6.2.11
Group: Comparison of the constants (20)
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Definition 6.1.1
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(Cohn–Gonçalves 2019, Theorem 1.4, existence part.) For every d \ge 1 there exists g \in \mathcal{E}_-(d) with r(g) = \mathsf{A}_-(d) (Definition 1.2.3).

Lean code for Theorem6.2.11●1 theorem
  • complete
    theorem CohnElkies.exists_signRadius_eq_signUncertaintyConstant_neg_one {d : ℕ}
      (hd : 0 < d) :
      ∃ g,
        CohnElkies.signRadius g.toFun =
          CohnElkies.signUncertaintyConstant (-1) d
    theorem CohnElkies.exists_signRadius_eq_signUncertaintyConstant_neg_one
      {d : ℕ} (hd : 0 < d) :
      ∃ g,
        CohnElkies.signRadius g.toFun =
          CohnElkies.signUncertaintyConstant
            (-1) d
    Cohn–Gonçalves 2019, Theorem 1.4 (existence): `A₋(d)` is attained by some `g ∈ 𝓔₋(d)`. 
Proof for Theorem 6.2.11
Proof uses 5
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Lemma 6.2.5
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By Lemma 6.2.6 and Lemma 6.2.8, 0 < a := \mathsf{A}_-(d) < \infty. Pick f_n \in \mathcal{E}_-(d) with r(f_n) \le a + 1/(n+1), normalized so that \|f_n\|_1 = 1; then |f_n| = |\widehat{f_n}| \le 1, \int f_n = 0, and f_n \ge 0 on \{|x| \ge a + 1/(n+1)\}. By Lemma 6.2.10 with R = a + 1 there is \kappa > 0 with \int_{|x| \le a+1} f_n = -\int_{|x| > a+1} f_n \le -\kappa for all n. Since \|f_n\|_2^2 \le \|f_n\|_\infty\|f_n\|_1 \le 1, Lemma 6.2.9 gives a subsequence converging weakly in L^2 to some g. Testing the weak convergence against bounded compactly supported functions shows: g \in L^1 with \int_K|g| \le 1 for every compact K (test with 1_K\operatorname{sign} g); \int_{|x| \le a+1} g \le -\kappa, so g \ne 0; \int_K g \le 0 for all balls K \supseteq B_{a+1}, hence \int g \le 0; and g \ge 0 a.e. on \{|x| > a\} (test with indicators of \{a + 1/(m+1) \le |x| \le m+1\} \cap \{g < 0\}). Testing against Schwartz functions \Phi and using \int\widehat u\,\Phi = \int u\,\widehat\Phi for u \in L^1 yields \int(\widehat g + g)\Phi = 0 for all smooth compactly supported \Phi, so \widehat g = -g a.e. The continuous function G = -\widehat g therefore satisfies G = g a.e., \widehat G = -G pointwise, G \ne 0, G(0) = -\int g \ge 0, and G \ge 0 on \{|x| \ge a\} (a.e. on the open exterior, hence everywhere by continuity). Finally Lemma 6.2.5 with R = a produces h \in \mathcal{E}_-(d) with r(h) \le a, and r(h) \ge \mathsf{A}_-(d) = a by definition of the infimum.

This differs from the proof of Cohn–Gonçalves in three places: their uniform negative-mass bound \int_{B} f_n \le K < 0 is deduced from Nazarov's uncertainty principle in Jaming's form (or from the Amrein–Berthier inequality), here from the compactness lemma Lemma 6.2.10; they pass from weak to almost-everywhere and L^2 convergence by Mazur's lemma before applying Fatou's lemma, whereas here the weak limit is only tested against explicit L^2 and smooth compactly supported functions; and they normalize the minimizing sequence by their Lemma 3.1 and infer f(0) = 0 for the limit from minimality, whereas here every element of \mathcal{E}_-(d) already has \widehat g = -g and g(0) = 0, and the origin correction is applied once, to the limit.