OAI/Probability/InvariantIsing/Arrays/TensorDiagonalWardCorrectionBound.lean

GitHub source file

4 declarations, 0 contain sorry, 0 declared as axioms

The normalized one-replica Gaussian Ward correction is quadratic in the perturbation scale, uniformly in the finite leaf restriction.

  1. def OAI.InvariantIsing.tensorRestrictionDiagonalWardContraction line 18
  2. lemma OAI.InvariantIsing.tensorRestrictionDiagonalWardContraction_eq line 23
  3. lemma OAI.InvariantIsing.tensorRestrictionDiagonalWardCorrection_eq line 35
  4. theorem OAI.InvariantIsing.tensorRestriction_actualDiagonalWardCorrection_abs_le line 58

    Source documentation

    The exact one-replica Gaussian correction, with its single covariance kernel rather than a doubled Hamiltonian coefficient.

    theorem tensorRestriction_actualDiagonalWardCorrection_abs_le [Fintype S] {N m n : ℕ}
        (hN : 0 < N) (U : SpecialOrthogonal N) {w : S → ℝ} (hw : GibbsReference w) (H : S → ℝ)
        (I : Fin m → Finset (Fin N)) (degree : Fin N → Fin m → ℕ) (treeDegree : Fin N → ℕ)
        (u : Fin N → ℝ) (hu : ∀ r, |u r| ≤ 2) (D : ℝ) (hD : 0 ≤ D)
        (hdegree : ∀ r, (∑ a, (degree r a : ℝ)) ≤ D * ((r : ℝ) + 1))
        (h : ℕ → ℝ) (hh : Monotone h) (h0 : 0 ≤ h 0)
        (J K : Finset (Fin N)) (x : S → Spin N × LabeledLeaf n) :
        |(N : ℝ)⁻¹ ^ 2 * ∑ i ∈ J, ∑ j ∈ K,
          gaussianWardCorrection w H (tensorRestrictionDiagonalObservable i j x U)
            (tensorRestrictionCovarianceDerivative I degree (tensorPerturbationAmplitude N u)
              (fun a => tensorPathProfile I degree n treeDegree h a) x i j U)| ≤
          48 * D * perturbationScale N ^ 2 := by
    …

    Mentions: OAI.InvariantIsing.SpecialOrthogonal, OAI.InvariantIsing.Spin, OAI.InvariantIsing.gaussianWardCorrection, OAI.InvariantIsing.tensorRestrictionDiagonalObservable, OAI.InvariantIsing.tensorRestrictionCovarianceDerivative, OAI.InvariantIsing.tensorPerturbationAmplitude, OAI.InvariantIsing.tensorPathProfile