Analysis of Boolean Functions in Lean

9.2. Small subsets of the hypercube are noise-sensitive🔗

Lemma9.2.1
Group: Chapter 9: Basics of hypercontractivity (100)
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For every homogeneous degree-k component, \left\|T_{1/\sqrt3}f^{=k}\right\|_4 =(1/\sqrt3)^k\|f^{=k}\|_4 \le\|f^{=k}\|_2. \tag{9.4}

Lean code for Lemma9.2.12 theorems
  • theoremdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    theorem FABL.noiseOperator_degreePart {n : } (rho : ) (k : )
      (f : FABL.SignCube n  ) :
      (FABL.noiseOperator rho) (FABL.degreePart k f) = fun x =>
        rho ^ k * FABL.degreePart k f x
    theorem FABL.noiseOperator_degreePart {n : }
      (rho : ) (k : )
      (f : FABL.SignCube n  ) :
      (FABL.noiseOperator rho)
          (FABL.degreePart k f) =
        fun x =>
        rho ^ k * FABL.degreePart k f x
    Noise acts on the homogeneous degree-`k` part by scalar multiplication by `ρᵏ`. 
  • theoremdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    theorem FABL.homogeneous_twoFour_estimate {n : } (k : )
      (f : FABL.SignCube n  ) :
      FABL.uniformLpNorm 4
            ((FABL.noiseOperator FABL.twoFourNoiseRoot)
              (FABL.degreePart k f)) =
          FABL.twoFourNoiseRoot ^ k *
            FABL.uniformLpNorm 4 (FABL.degreePart k f) 
        FABL.twoFourNoiseRoot ^ k *
            FABL.uniformLpNorm 4 (FABL.degreePart k f) 
          FABL.uniformLpNorm 2 (FABL.degreePart k f)
    theorem FABL.homogeneous_twoFour_estimate {n : }
      (k : ) (f : FABL.SignCube n  ) :
      FABL.uniformLpNorm 4
            ((FABL.noiseOperator
                FABL.twoFourNoiseRoot)
              (FABL.degreePart k f)) =
          FABL.twoFourNoiseRoot ^ k *
            FABL.uniformLpNorm 4
              (FABL.degreePart k f) 
        FABL.twoFourNoiseRoot ^ k *
            FABL.uniformLpNorm 4
              (FABL.degreePart k f) 
          FABL.uniformLpNorm 2
            (FABL.degreePart k f)
    O'Donnell, equation (9.4): the homogeneous Bonami estimate at correlation `1 / √3`. 
Theorem9.2.2
Group: Chapter 9: Basics of hypercontractivity (100)
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L∃∀N

$(2,4)$-Hypercontractivity Theorem. For every f:\{-1,1\}^n\to\mathbb R, \left\|T_{1/\sqrt3}f\right\|_4\le\|f\|_2.

Lean code for Theorem9.2.24 declarations
  • defdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    def FABL.twoFourNoiseRoot : 
    def FABL.twoFourNoiseRoot : 
    The correlation parameter `1 / √3`, represented so its square is definitionally tied to
    the fourth-moment induction. 
  • theoremdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    theorem FABL.twoFourHypercontractive_fourthMoment {n : }
      (f : FABL.SignCube n  ) :
      (Finset.univ.expect fun x =>
          (FABL.noiseOperator FABL.twoFourNoiseRoot) f x ^ 4) 
        (Finset.univ.expect fun x => f x ^ 2) ^ 2
    theorem FABL.twoFourHypercontractive_fourthMoment
      {n : } (f : FABL.SignCube n  ) :
      (Finset.univ.expect fun x =>
          (FABL.noiseOperator
                FABL.twoFourNoiseRoot)
              f x ^
            4) 
        (Finset.univ.expect fun x =>
            f x ^ 2) ^
          2
    The `(2,4)` theorem in fourth-moment form. 
  • theoremdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    theorem FABL.uniformLpNorm_four_pow_eq_expect_fourth.{u_1} {Ω : Type u_1}
      [Fintype Ω] (f : Ω  ) :
      FABL.uniformLpNorm 4 f ^ 4 = Finset.univ.expect fun x => f x ^ 4
    theorem FABL.uniformLpNorm_four_pow_eq_expect_fourth.{u_1}
      {Ω : Type u_1} [Fintype Ω] (f : Ω  ) :
      FABL.uniformLpNorm 4 f ^ 4 =
        Finset.univ.expect fun x => f x ^ 4
    The fourth power of the normalized uniform `L⁴` quantity is the fourth moment. 
  • theoremdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    theorem FABL.twoFourHypercontractivity {n : } (f : FABL.SignCube n  ) :
      FABL.uniformLpNorm 4 ((FABL.noiseOperator FABL.twoFourNoiseRoot) f) 
        FABL.uniformLpNorm 2 f
    theorem FABL.twoFourHypercontractivity {n : }
      (f : FABL.SignCube n  ) :
      FABL.uniformLpNorm 4
          ((FABL.noiseOperator
              FABL.twoFourNoiseRoot)
            f) 
        FABL.uniformLpNorm 2 f
    O'Donnell's `(2,4)`-Hypercontractivity Theorem. 
Theorem9.2.3
Group: Chapter 9: Basics of hypercontractivity (100)
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L∃∀N

$(4/3,2)$-Hypercontractivity Theorem. For every f:\{-1,1\}^n\to\mathbb R, \left\|T_{1/\sqrt3}f\right\|_2\le\|f\|_{4/3}. Equivalently, \operatorname{Stab}_{1/3}[f]\le\|f\|_{4/3}^2.

Lean code for Theorem9.2.33 theorems
  • theoremdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    theorem FABL.uniformInner_le_uniformLpNorm_fourThird_mul_four.{u_1}
      {Ω : Type u_1} [Fintype Ω] [Nonempty Ω] (f g : Ω  ) :
      FABL.uniformInner f g 
        FABL.uniformLpNorm (4 / 3) f * FABL.uniformLpNorm 4 g
    theorem FABL.uniformInner_le_uniformLpNorm_fourThird_mul_four.{u_1}
      {Ω : Type u_1} [Fintype Ω] [Nonempty Ω]
      (f g : Ω  ) :
      FABL.uniformInner f g 
        FABL.uniformLpNorm (4 / 3) f *
          FABL.uniformLpNorm 4 g
    Hölder's inequality for normalized uniform `L^{4/3}` and `L⁴` quantities. 
  • theoremdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    theorem FABL.fourThirdTwoHypercontractivity {n : } (f : FABL.SignCube n  ) :
      FABL.uniformLpNorm 2 ((FABL.noiseOperator FABL.twoFourNoiseRoot) f) 
        FABL.uniformLpNorm (4 / 3) f
    theorem FABL.fourThirdTwoHypercontractivity
      {n : } (f : FABL.SignCube n  ) :
      FABL.uniformLpNorm 2
          ((FABL.noiseOperator
              FABL.twoFourNoiseRoot)
            f) 
        FABL.uniformLpNorm (4 / 3) f
    O'Donnell's `(4/3,2)`-Hypercontractivity Theorem. 
  • theoremdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    theorem FABL.noiseStability_oneThird_le_uniformLpNorm_fourThird_sq {n : }
      (f : FABL.SignCube n  ) :
      FABL.noiseStability (1 / 3)
          FABL.noiseStability_oneThird_le_uniformLpNorm_fourThird_sq._proof_1
          f 
        FABL.uniformLpNorm (4 / 3) f ^ 2
    theorem FABL.noiseStability_oneThird_le_uniformLpNorm_fourThird_sq
      {n : } (f : FABL.SignCube n  ) :
      FABL.noiseStability (1 / 3)
          FABL.noiseStability_oneThird_le_uniformLpNorm_fourThird_sq._proof_1
          f 
        FABL.uniformLpNorm (4 / 3) f ^ 2
    The stability form of `(4/3,2)` hypercontractivity. 
Theorem9.2.4
Group: Chapter 9: Basics of hypercontractivity (100)
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Corollary 9.8. If A\subseteq\{-1,1\}^n has volume \alpha and 1_A is its indicator, then \operatorname{Stab}_{1/3}[1_A] =\Pr[x\in A,\ y\in A] \le\alpha^{3/2}. For \alpha>0, equivalently, \Pr_{x\sim A,\,y\sim N_{1/3}(x)}[y\in A] \le\alpha^{1/2}.

Lean code for Theorem9.2.44 theorems
  • theoremdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    theorem FABL.uniformLpNorm_fourThird_sq_of_zeroOne {n : }
      (f : FABL.SignCube n  ) (α : )
      (hvalues :  (x : FABL.SignCube n), f x = 0  f x = 1)
      (hmean : FABL.mean f = α) :
      FABL.uniformLpNorm (4 / 3) f ^ 2 = α ^ (3 / 2)
    theorem FABL.uniformLpNorm_fourThird_sq_of_zeroOne
      {n : } (f : FABL.SignCube n  )
      (α : )
      (hvalues :
         (x : FABL.SignCube n),
          f x = 0  f x = 1)
      (hmean : FABL.mean f = α) :
      FABL.uniformLpNorm (4 / 3) f ^ 2 =
        α ^ (3 / 2)
    For a zero-one-valued function of mean `α`, the square of its uniform `L^{4/3}` quantity
    is `α^{3/2}`. 
  • theoremdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    theorem FABL.smallSetExpansion_oneThird {n : } (f : FABL.SignCube n  )
      (α : ) (hvalues :  (x : FABL.SignCube n), f x = 0  f x = 1)
      (hmean : FABL.mean f = α) :
      FABL.noiseStability (1 / 3)
          FABL.noiseStability_oneThird_le_uniformLpNorm_fourThird_sq._proof_1
          f 
        α ^ (3 / 2)
    theorem FABL.smallSetExpansion_oneThird {n : }
      (f : FABL.SignCube n  ) (α : )
      (hvalues :
         (x : FABL.SignCube n),
          f x = 0  f x = 1)
      (hmean : FABL.mean f = α) :
      FABL.noiseStability (1 / 3)
          FABL.noiseStability_oneThird_le_uniformLpNorm_fourThird_sq._proof_1
          f 
        α ^ (3 / 2)
    O'Donnell, Corollary 9.8 in noise-stability form. 
  • theoremdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    theorem FABL.smallSetExpansion_oneThird_event {n : } (f : FABL.SignCube n  )
      (α : ) (hvalues :  (x : FABL.SignCube n), f x = 0  f x = 1)
      (hmean : FABL.mean f = α) :
      (FABL.pmfEventProbability
          (FABL.correlatedPairPMF (1 / 3)
            FABL.noiseStability_oneThird_le_uniformLpNorm_fourThird_sq._proof_1)
          fun xy => f xy.1 = 1  f xy.2 = 1) 
        α ^ (3 / 2)
    theorem FABL.smallSetExpansion_oneThird_event
      {n : } (f : FABL.SignCube n  )
      (α : )
      (hvalues :
         (x : FABL.SignCube n),
          f x = 0  f x = 1)
      (hmean : FABL.mean f = α) :
      (FABL.pmfEventProbability
          (FABL.correlatedPairPMF (1 / 3)
            FABL.noiseStability_oneThird_le_uniformLpNorm_fourThird_sq._proof_1)
          fun xy => f xy.1 = 1  f xy.2 = 1) 
        α ^ (3 / 2)
    O'Donnell, Corollary 9.8 in joint-event form. 
  • theoremdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    theorem FABL.smallSetExpansion_oneThird_conditional {n : }
      (f : FABL.SignCube n  ) (α : )
      (hvalues :  (x : FABL.SignCube n), f x = 0  f x = 1)
      (hmean : FABL.mean f = α) ( : 0 < α) :
      (FABL.pmfEventProbability
            (FABL.correlatedPairPMF (1 / 3)
              FABL.noiseStability_oneThird_le_uniformLpNorm_fourThird_sq._proof_1)
            fun xy => f xy.1 = 1  f xy.2 = 1) /
          α 
        α
    theorem FABL.smallSetExpansion_oneThird_conditional
      {n : } (f : FABL.SignCube n  )
      (α : )
      (hvalues :
         (x : FABL.SignCube n),
          f x = 0  f x = 1)
      (hmean : FABL.mean f = α) ( : 0 < α) :
      (FABL.pmfEventProbability
            (FABL.correlatedPairPMF (1 / 3)
              FABL.noiseStability_oneThird_le_uniformLpNorm_fourThird_sq._proof_1)
            fun xy =>
            f xy.1 = 1  f xy.2 = 1) /
          α 
        α
    Corollary 9.8's equivalent conditional-probability form, represented as joint mass divided
    by the positive volume `α`. 
Lemma9.2.5
Group: Chapter 9: Basics of hypercontractivity (100)
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Example 9.9. If \alpha=2^{-k} and A is a codimension-k subcube, then one noise step remains in A with probability (2/3)^k =\alpha^{\log(3/2)} \le\alpha^{1/2}.

Lean code for Lemma9.2.53 declarations
  • defdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    def FABL.pointSubcubeIndicator (k : ) : FABL.SignCube k  
    def FABL.pointSubcubeIndicator (k : ) :
      FABL.SignCube k  
    The indicator of the one-point coordinate subcube in dimension `k`; this is a
    codimension-`k` subcube, and adding free coordinates gives the book's general example. 
  • theoremdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    theorem FABL.mean_pointSubcubeIndicator (k : ) :
      FABL.mean (FABL.pointSubcubeIndicator k) = (2 ^ k)⁻¹
    theorem FABL.mean_pointSubcubeIndicator (k : ) :
      FABL.mean
          (FABL.pointSubcubeIndicator k) =
        (2 ^ k)⁻¹
    O'Donnell, Example 9.9: the point subcube has volume `2⁻ᵏ`. 
  • theoremdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    theorem FABL.pointSubcube_oneThird_stayProbability (k : ) :
      have x₀ := fun x => 1;
      FABL.pmfExpectation
          (FABL.noiseKernel (1 / 3)
            FABL.noiseStability_oneThird_le_uniformLpNorm_fourThird_sq._proof_1
            x₀)
          (FABL.pointSubcubeIndicator k) =
        (2 / 3) ^ k
    theorem FABL.pointSubcube_oneThird_stayProbability
      (k : ) :
      have x₀ := fun x => 1;
      FABL.pmfExpectation
          (FABL.noiseKernel (1 / 3)
            FABL.noiseStability_oneThird_le_uniformLpNorm_fourThird_sq._proof_1
            x₀)
          (FABL.pointSubcubeIndicator k) =
        (2 / 3) ^ k
    O'Donnell, Example 9.9: from a point in the codimension-`k` subcube, one step of
    one-third noise stays in the subcube with probability `(2/3)ᵏ`. 
Definition9.2.6
Group: Chapter 9: Basics of hypercontractivity (100)
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Definition 9.10. The n-dimensional \rho-stable hypercube graph has vertex set \{-1,1\}^n and directed edge weight on (x,y) equal to the probability of that \rho-correlated pair. When \rho=1-2\delta, it is also called the \delta-noisy hypercube.

Lean code for Definition9.2.62 definitions
  • defdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    def FABL.stableHypercubeEdgeWeight {n : } (ρ : ) ( : ρ  Set.Icc (-1) 1)
      (x y : FABL.SignCube n) : 
    def FABL.stableHypercubeEdgeWeight {n : }
      (ρ : ) ( : ρ  Set.Icc (-1) 1)
      (x y : FABL.SignCube n) : 
    O'Donnell, Definition 9.10: the directed edge weight of the `ρ`-stable hypercube graph. 
  • defdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    def FABL.noisyHypercubeEdgeWeight {n : } (δ : ) ( : δ  Set.Icc 0 1)
      (x y : FABL.SignCube n) : 
    def FABL.noisyHypercubeEdgeWeight {n : }
      (δ : ) ( : δ  Set.Icc 0 1)
      (x y : FABL.SignCube n) : 
    O'Donnell, Definition 9.10: the `δ`-noisy graph is the stable graph at `ρ = 1 - 2δ`. 
Lemma9.2.7
Group: Chapter 9: Basics of hypercontractivity (100)
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Remark 9.11. The edge weights are nonnegative and sum to 1; every vertex has incoming and outgoing weight 2^{-n}. The corresponding undirected edge has weight 2^{1-n}\delta^{\Delta(x,y)}(1-\delta)^{n-\Delta(x,y)}. Thus uniform measure is stationary and the chain is reversible. Its continuous-time parameter is t=\ln(1/\rho).

Lean code for Lemma9.2.713 declarations
  • theoremdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    theorem FABL.stableHypercubeEdgeWeight_nonneg {n : } (ρ : )
      ( : ρ  Set.Icc (-1) 1) (x y : FABL.SignCube n) :
      0  FABL.stableHypercubeEdgeWeight ρ  x y
    theorem FABL.stableHypercubeEdgeWeight_nonneg
      {n : } (ρ : )
      ( : ρ  Set.Icc (-1) 1)
      (x y : FABL.SignCube n) :
      0 
        FABL.stableHypercubeEdgeWeight ρ  x
          y
    Stable-hypercube edge weights are nonnegative. 
  • theoremdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    theorem FABL.stableHypercubeEdgeWeight_eq_uniform_mul_transition {n : } (ρ : )
      ( : ρ  Set.Icc (-1) 1) (x y : FABL.SignCube n) :
      FABL.stableHypercubeEdgeWeight ρ  x y =
        ((FABL.uniformPMF (FABL.SignCube n)) x).toReal *
          ((FABL.noiseKernel ρ  x) y).toReal
    theorem FABL.stableHypercubeEdgeWeight_eq_uniform_mul_transition
      {n : } (ρ : )
      ( : ρ  Set.Icc (-1) 1)
      (x y : FABL.SignCube n) :
      FABL.stableHypercubeEdgeWeight ρ  x
          y =
        ((FABL.uniformPMF (FABL.SignCube n))
              x).toReal *
          ((FABL.noiseKernel ρ  x) y).toReal
    The stable graph is the uniform stationary mass times its noise-kernel transition mass. 
  • theoremdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    theorem FABL.sum_stableHypercubeEdgeWeight {n : } (ρ : )
      ( : ρ  Set.Icc (-1) 1) :
       xy, FABL.stableHypercubeEdgeWeight ρ  xy.1 xy.2 = 1
    theorem FABL.sum_stableHypercubeEdgeWeight {n : }
      (ρ : ) ( : ρ  Set.Icc (-1) 1) :
       xy,
          FABL.stableHypercubeEdgeWeight ρ 
            xy.1 xy.2 =
        1
    O'Donnell, Remark 9.11: all directed edge weights sum to one. 
  • theoremdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    theorem FABL.stableHypercubeEdgeWeight_comm {n : } (ρ : )
      ( : ρ  Set.Icc (-1) 1) (x y : FABL.SignCube n) :
      FABL.stableHypercubeEdgeWeight ρ  x y =
        FABL.stableHypercubeEdgeWeight ρ  y x
    theorem FABL.stableHypercubeEdgeWeight_comm
      {n : } (ρ : )
      ( : ρ  Set.Icc (-1) 1)
      (x y : FABL.SignCube n) :
      FABL.stableHypercubeEdgeWeight ρ  x
          y =
        FABL.stableHypercubeEdgeWeight ρ  y
          x
    O'Donnell, Remark 9.11: the graph is reversible; exchanging an edge's endpoints preserves
    its weight. 
  • defdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    def FABL.stableHypercubeUndirectedEdgeWeight {n : } (ρ : )
      ( : ρ  Set.Icc (-1) 1) (x y : FABL.SignCube n) : 
    def FABL.stableHypercubeUndirectedEdgeWeight
      {n : } (ρ : )
      ( : ρ  Set.Icc (-1) 1)
      (x y : FABL.SignCube n) : 
    The undirected edge weight is the sum of the two directed orientations. 
  • theoremdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    theorem FABL.stableHypercubeUndirectedEdgeWeight_eq_two_mul {n : } (ρ : )
      ( : ρ  Set.Icc (-1) 1) (x y : FABL.SignCube n) :
      FABL.stableHypercubeUndirectedEdgeWeight ρ  x y =
        2 * FABL.stableHypercubeEdgeWeight ρ  x y
    theorem FABL.stableHypercubeUndirectedEdgeWeight_eq_two_mul
      {n : } (ρ : )
      ( : ρ  Set.Icc (-1) 1)
      (x y : FABL.SignCube n) :
      FABL.stableHypercubeUndirectedEdgeWeight
          ρ  x y =
        2 *
          FABL.stableHypercubeEdgeWeight ρ 
            x y
    By reversibility, an undirected edge has twice either directed weight. 
  • theoremdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    theorem FABL.sum_stableHypercubeEdgeWeight_outgoing {n : } (ρ : )
      ( : ρ  Set.Icc (-1) 1) (x : FABL.SignCube n) :
       y, FABL.stableHypercubeEdgeWeight ρ  x y = (2 ^ n)⁻¹
    theorem FABL.sum_stableHypercubeEdgeWeight_outgoing
      {n : } (ρ : )
      ( : ρ  Set.Icc (-1) 1)
      (x : FABL.SignCube n) :
       y,
          FABL.stableHypercubeEdgeWeight ρ 
            x y =
        (2 ^ n)⁻¹
    O'Donnell, Remark 9.11: the total outgoing weight at every vertex is `2⁻ⁿ`. 
  • theoremdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    theorem FABL.sum_stableHypercubeEdgeWeight_incoming {n : } (ρ : )
      ( : ρ  Set.Icc (-1) 1) (y : FABL.SignCube n) :
       x, FABL.stableHypercubeEdgeWeight ρ  x y = (2 ^ n)⁻¹
    theorem FABL.sum_stableHypercubeEdgeWeight_incoming
      {n : } (ρ : )
      ( : ρ  Set.Icc (-1) 1)
      (y : FABL.SignCube n) :
       x,
          FABL.stableHypercubeEdgeWeight ρ 
            x y =
        (2 ^ n)⁻¹
    O'Donnell, Remark 9.11: the total incoming weight at every vertex is also `2⁻ⁿ`. 
  • theoremdefined in FABL/Chapter09/StableHypercubeExplicit.lean
    complete
    theorem FABL.coordinateNoisePMF_noisy_apply_toReal (δ : )
      ( : δ  Set.Icc 0 1) (x y : FABL.Sign) :
      ((FABL.coordinateNoisePMF (1 - 2 * δ)  x) y).toReal =
        if x = y then 1 - δ else δ
    theorem FABL.coordinateNoisePMF_noisy_apply_toReal
      (δ : ) ( : δ  Set.Icc 0 1)
      (x y : FABL.Sign) :
      ((FABL.coordinateNoisePMF (1 - 2 * δ) 
              x)
            y).toReal =
        if x = y then 1 - δ else δ
    At noise rate `delta`, a coordinate is unchanged with mass `1-delta` and flipped with mass
    `delta`. 
  • theoremdefined in FABL/Chapter09/StableHypercubeExplicit.lean
    complete
    theorem FABL.noiseKernel_noisy_apply_toReal {n : } (δ : )
      ( : δ  Set.Icc 0 1) (x y : FABL.SignCube n) :
      ((FABL.noiseKernel (1 - 2 * δ)  x) y).toReal =
        δ ^ hammingDist x y * (1 - δ) ^ (n - hammingDist x y)
    theorem FABL.noiseKernel_noisy_apply_toReal
      {n : } (δ : ) ( : δ  Set.Icc 0 1)
      (x y : FABL.SignCube n) :
      ((FABL.noiseKernel (1 - 2 * δ)  x)
            y).toReal =
        δ ^ hammingDist x y *
          (1 - δ) ^ (n - hammingDist x y)
    The explicit Hamming-distance mass formula for the `delta`-noisy transition kernel. 
  • theoremdefined in FABL/Chapter09/StableHypercubeExplicit.lean
    complete
    theorem FABL.noisyHypercubeUndirectedEdgeWeight_eq_hamming {n : } (δ : )
      ( : δ  Set.Icc 0 1) (x y : FABL.SignCube n) :
      FABL.stableHypercubeUndirectedEdgeWeight (1 - 2 * δ)  x y =
        2 ^ (1 - n) * δ ^ hammingDist x y * (1 - δ) ^ (n - hammingDist x y)
    theorem FABL.noisyHypercubeUndirectedEdgeWeight_eq_hamming
      {n : } (δ : ) ( : δ  Set.Icc 0 1)
      (x y : FABL.SignCube n) :
      FABL.stableHypercubeUndirectedEdgeWeight
          (1 - 2 * δ)  x y =
        2 ^ (1 - n) * δ ^ hammingDist x y *
          (1 - δ) ^ (n - hammingDist x y)
    Remark 9.11's explicit undirected edge weight. 
  • defdefined in FABL/Chapter09/StableHypercubeExplicit.lean
    complete
    def FABL.stableHypercubeContinuousTime (rho : ) : 
    def FABL.stableHypercubeContinuousTime
      (rho : ) : 
    The continuous-time parameter associated to a positive stable correlation. 
  • theoremdefined in FABL/Chapter09/StableHypercubeExplicit.lean
    complete
    theorem FABL.exp_neg_stableHypercubeContinuousTime (rho : ) (hrho : 0 < rho) :
      Real.exp (-FABL.stableHypercubeContinuousTime rho) = rho
    theorem FABL.exp_neg_stableHypercubeContinuousTime
      (rho : ) (hrho : 0 < rho) :
      Real.exp
          (-FABL.stableHypercubeContinuousTime
              rho) =
        rho
    The parameterization `t = log (1/rho)` is equivalent to `rho = exp (-t)`. 
Theorem9.2.8
Group: Chapter 9: Basics of hypercontractivity (100)
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L∃∀N

Corollary 9.12. For every Boolean-valued f and coordinate i, \operatorname{Inf}_i^{(1/3)}[f] \le\operatorname{Inf}_i[f]^{3/2}.

Lean code for Theorem9.2.82 theorems
  • theoremdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    theorem FABL.stableInfluence_oneThird_le_booleanInfluence_mul_sqrt {n : }
      (f : FABL.BooleanFunction n) (i : Fin n) :
      FABL.stableInfluence (1 / 3) f.toReal i 
        FABL.booleanInfluence f i * (FABL.booleanInfluence f i)
    theorem FABL.stableInfluence_oneThird_le_booleanInfluence_mul_sqrt
      {n : } (f : FABL.BooleanFunction n)
      (i : Fin n) :
      FABL.stableInfluence (1 / 3) f.toReal
          i 
        FABL.booleanInfluence f i *
          (FABL.booleanInfluence f i)
    O'Donnell, Corollary 9.12, written as `a * √a = a^{3/2}` to avoid introducing a
    separate real-exponent convention for influence. 
  • theoremdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    theorem FABL.stableInfluence_oneThird_le_booleanInfluence_rpow {n : }
      (f : FABL.BooleanFunction n) (i : Fin n) :
      FABL.stableInfluence (1 / 3) f.toReal i 
        FABL.booleanInfluence f i ^ (3 / 2)
    theorem FABL.stableInfluence_oneThird_le_booleanInfluence_rpow
      {n : } (f : FABL.BooleanFunction n)
      (i : Fin n) :
      FABL.stableInfluence (1 / 3) f.toReal
          i 
        FABL.booleanInfluence f i ^ (3 / 2)
    Corollary 9.12 in the book's literal exponent notation. 
Lemma9.2.9
Group: Chapter 9: Basics of hypercontractivity (100)
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uses 1used by 0L∃∀N

If f:\{-1,1\}^n\to\{0,1\} has mean \alpha, then for every k\ge0, W^{\le k}[f]\le3^k\alpha^{3/2}. \tag{9.7}

Lean code for Lemma9.2.92 theorems
  • theoremdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    theorem FABL.oneThird_pow_mul_fourierWeightAtMost_le_noiseStability {n : }
      (k : ) (f : FABL.SignCube n  ) :
      (1 / 3) ^ k * FABL.fourierWeightAtMost k f 
        FABL.noiseStability (1 / 3)
          FABL.noiseStability_oneThird_le_uniformLpNorm_fourThird_sq._proof_1
          f
    theorem FABL.oneThird_pow_mul_fourierWeightAtMost_le_noiseStability
      {n : } (k : )
      (f : FABL.SignCube n  ) :
      (1 / 3) ^ k *
          FABL.fourierWeightAtMost k f 
        FABL.noiseStability (1 / 3)
          FABL.noiseStability_oneThird_le_uniformLpNorm_fourThird_sq._proof_1
          f
    The low-degree Fourier mass of a zero-one function is controlled by its one-third
    noise stability. 
  • theoremdefined in FABL/Chapter09/SmallSetExpansion.lean
    complete
    theorem FABL.fourierWeightAtMost_le_three_pow_mul_rpow {n : } (k : )
      (f : FABL.SignCube n  ) (α : )
      (hvalues :  (x : FABL.SignCube n), f x = 0  f x = 1)
      (hmean : FABL.mean f = α) :
      FABL.fourierWeightAtMost k f  3 ^ k * α ^ (3 / 2)
    theorem FABL.fourierWeightAtMost_le_three_pow_mul_rpow
      {n : } (k : )
      (f : FABL.SignCube n  ) (α : )
      (hvalues :
         (x : FABL.SignCube n),
          f x = 0  f x = 1)
      (hmean : FABL.mean f = α) :
      FABL.fourierWeightAtMost k f 
        3 ^ k * α ^ (3 / 2)
    O'Donnell, equation (9.7): `W^{≤k}[f] ≤ 3^k α^{3/2}`.