OAI/Probability/DilutedSpin/PatternComparison.lean
45 declarations, 0 contain sorry, 0 declared as axioms
- def
OAI.DilutedSpinGlass.BooleanPolynomial.truthline 11 - def
OAI.DilutedSpinGlass.BooleanPolynomial.monomialline 12 - def
OAI.DilutedSpinGlass.BooleanPolynomial.coefficientline 13 - lemma
OAI.DilutedSpinGlass.BooleanPolynomial.interpolationline 17 - lemma
OAI.DilutedSpinGlass.BooleanPolynomial.product_expansionline 36 - theorem
OAI.DilutedSpinGlass.BooleanPolynomial.expansionline 53Source documentation
Every predicate of a finite sharing profile is a finite real linear combination of positive sharing requirements. No endpoint mark is needed.
theorem expansion (F : (R → Bool) → ℝ) (y : R → Bool) : F y = ∑ s : Finset R, coefficient F s * monomial s y := by …Mentions: OAI.DilutedSpinGlass.BooleanPolynomial.coefficient, OAI.DilutedSpinGlass.BooleanPolynomial.monomial
- def
OAI.DilutedSpinGlass.extractionProbeline 78Source documentation
The exact probe sequence of pert:parameters, indexed from zero.
noncomputable def extractionProbe (j : ℕ) : ℝ := 1 / ((j:ℝ)+4)
- theorem
OAI.DilutedSpinGlass.extractionProbe_posline 80 - theorem
OAI.DilutedSpinGlass.extractionProbe_le_halfline 84 - theorem
OAI.DilutedSpinGlass.extractionProbe_tendstoline 90 - theorem
OAI.DilutedSpinGlass.coefficients_tendsto_zero_of_uniform_remaindersline 100Source documentation
Real finite-remainder extraction. This avoids both a complex normal-family argument and a subsequence of limiting coefficients: all coefficients tend to zero directly. The same base function is tested at every probe, as required by the Poisson add-one identity.
theorem coefficients_tendsto_zero_of_uniform_remainders (H : ℕ → ℝ → ℝ) (a : ℕ → ℕ → ℝ) (B : ℕ → ℝ) (C : ℝ) (_hB : ∀ k, 0 ≤ B k) (hC : 0 ≤ C) (hR : ∀ N k t, t ∈ Icc (0:ℝ) (1/2) → |H N t - ∑ i ∈ Finset.range (k+1), a N i * t^i| ≤ B k * t^(k+1)) (err : ℕ → ℕ → ℝ) (herr : ∀ j, Tendsto (err j) atTop (𝓝 0)) (hsmall : ∀ j N, |H N (extractionProbe j)| ≤ C * extractionProbe j ^ (j+4) + err j N) : ∀ k, Tendsto (fun N => a N k) atTop (𝓝 0) := by …Mentions: OAI.DilutedSpinGlass.extractionProbe
- theorem
OAI.DilutedSpinGlass.integral_polynomial_remainderline 175Source documentation
Uniform finite Taylor remainders survive an arbitrary probability-space average. This is a plain Bochner integral statement, not an analyticity axiom.
theorem integral_polynomial_remainder {Z : Type*} [MeasurableSpace Z] (μ : Measure Z) [IsProbabilityMeasure μ] (F : Z → ℝ) (a : ℕ → Z → ℝ) (hF : Integrable F μ) (ha : ∀ j, Integrable (a j) μ) (k : ℕ) (t R : ℝ) (hR : ∀ z, |F z - ∑ j ∈ Finset.range (k+1), a j z*t^j| ≤ R) : |(∫ z, F z ∂μ) - ∑ j ∈ Finset.range (k+1), (∫ z, a j z ∂μ)*t^j| ≤ R := by … - theorem
OAI.DilutedSpinGlass.integral_difference_boundline 191 - lemma
OAI.DilutedSpinGlass.limsup_sqrt_error_boundline 210 - lemma
OAI.DilutedSpinGlass.limsup_finite_linear_boundline 241 - lemma
OAI.DilutedSpinGlass.squeeze_triangle_grid_zeroline 270Source documentation
First take each fixed-grid limsup, then the grid limit, and only then let the arbitrary regularity cutoff tend to zero.
lemma squeeze_triangle_grid_zero (a : ℕ → ℝ) (C : ℝ) (ha : ∀ n, 0 ≤ a n) (hC : 0 ≤ C) (b : ℝ → ℕ → ℝ) (hb : ∀ η, 0<η → Tendsto (b η) atTop (𝓝 (C*η))) (hbound : ∀ η, 0<η → ∀ n, a n ≤ b η n) : Tendsto a atTop (𝓝 0) := by … - def
OAI.DilutedSpinGlass.Pattern.signline 301Source documentation
The manuscript's ±1 spin, represented by Bool.
def sign (s : Bool) : ℝ := if s then 1 else -1
- theorem
OAI.DilutedSpinGlass.Pattern.abs_signline 303 - theorem
OAI.DilutedSpinGlass.Pattern.sign_sqline 304 - theorem
OAI.DilutedSpinGlass.Pattern.sign_indicatorline 306 - def
OAI.DilutedSpinGlass.Pattern.characterline 309 - theorem
OAI.DilutedSpinGlass.Pattern.abs_characterline 311 - theorem
OAI.DilutedSpinGlass.Pattern.character_emptyline 314 - theorem
OAI.DilutedSpinGlass.Pattern.character_kernelline 318Source documentation
Fourier inversion kernel on replica-spin patterns.
theorem character_kernel {ι : Type*} [Fintype ι] [DecidableEq ι] (e f : ι → Bool) : (∑ S : Finset ι, character S e * character S f) = if e=f then (2 : ℝ) ^ Fintype.card ι else 0 := by …Mentions: OAI.DilutedSpinGlass.Pattern.character
- def
OAI.DilutedSpinGlass.Pattern.momentline 341Source documentation
Moments include all replica subsets, not only pair overlaps.
noncomputable def moment {ι : Type*} [Fintype ι] [DecidableEq ι] (P : (ι → Bool) → ℝ) (S : Finset ι) : ℝ := … - theorem
OAI.DilutedSpinGlass.Pattern.inversionline 345Source documentation
Exact Walsh inversion for an arbitrary signed pattern mass.
theorem inversion {ι : Type*} [Fintype ι] [DecidableEq ι] (P : (ι → Bool) → ℝ) (e : ι → Bool) : P e = (∑ S : Finset ι, moment P S * character S e) / (2 : ℝ)^Fintype.card ι := by …Mentions: OAI.DilutedSpinGlass.Pattern.moment, OAI.DilutedSpinGlass.Pattern.character
- theorem
OAI.DilutedSpinGlass.Pattern.variation_le_momentsline 360Source documentation
The total variation discrepancy costs one per nonempty multioverlap. Both masses have the same total, so the empty Fourier coefficient cancels.
theorem variation_le_moments {ι : Type*} [Fintype ι] [DecidableEq ι] (P Q : (ι → Bool) → ℝ) (htotal : ∑ e, P e = ∑ e, Q e) : (∑ e, |P e-Q e|) ≤ ∑ S ∈ (Finset.univ : Finset (Finset ι)).erase ∅, |moment P S-moment Q S| := by …Mentions: OAI.DilutedSpinGlass.Pattern.moment
- theorem
OAI.DilutedSpinGlass.Pattern.product_variation_stepline 390Source documentation
Exact coordinatewise product telescoping, in a form usable for different probability laws at different message labels.
theorem product_variation_step {α β : Type*} [Fintype α] [Fintype β] (P Q : α → ℝ) (U V : β → ℝ) (hP : ∀ x, 0 ≤ P x) (hV : ∀ y, 0 ≤ V y) (hPt : ∑ x, P x = 1) (hVt : ∑ y, V y = 1) : (∑ x, ∑ y, |P x*U y-Q x*V y|) ≤ (∑ x, |P x-Q x|) + ∑ y, |U y-V y| := by … - theorem
OAI.DilutedSpinGlass.Pattern.observable_variationline 411Source documentation
Testing a spin pattern by a bounded observable costs twice the total variation.
theorem observable_variation {α : Type*} [Fintype α] (P Q f : α → ℝ) (hf : ∀ x, |f x| ≤ 1) : |(∑ x, P x*f x)-(∑ x, Q x*f x)| ≤ ∑ x, |P x-Q x| := by … - theorem
OAI.DilutedSpinGlass.Pattern.product_variationline 425Source documentation
Tensorization with the sharp linear number of independent labels.
theorem product_variation {α : Type*} [Fintype α] (P Q : α → ℝ) (hP : ∀ x, 0 ≤ P x) (hQ : ∀ x, 0 ≤ Q x) (hPt : ∑ x, P x = 1) (hQt : ∑ x, Q x = 1) (a : ℕ) : (∑ x : Fin a → α, |(∏ i, P (x i))-(∏ i, Q (x i))|) ≤ (a : ℝ) * ∑ x, |P x-Q x| := by … - theorem
OAI.DilutedSpinGlass.Pattern.pattern_replacementline 451Source documentation
The deterministic empirical-pattern comparison in comp:patterns. The hypotheses are probability masses, and the conclusion involves ALL nonempty replica-subset moments, with no assumption of decorrelation.
theorem pattern_replacement {ι : Type*} [Fintype ι] [DecidableEq ι] (P Q : (ι → Bool) → ℝ) (hP : ∀ x, 0 ≤ P x) (hQ : ∀ x, 0 ≤ Q x) (hPt : ∑ x, P x = 1) (hQt : ∑ x, Q x = 1) (a : ℕ) (f : (Fin a → (ι → Bool)) → ℝ) (hf : ∀ x, |f x| ≤ 1) : |(∑ x, (∏ i, P (x i))*f x)-(∑ x, (∏ i, Q (x i))*f x)| ≤ (a : ℝ) * ∑ S ∈ (Finset.univ : Finset (Finset ι)).erase ∅, |moment P S-moment Q S| := by …Mentions: OAI.DilutedSpinGlass.Pattern.moment
- def
OAI.DilutedSpinGlass.Pattern.empiricalline 462Source documentation
Empirical law of the replica pattern at a uniformly sampled site.
noncomputable def empirical {ι : Type*} [Fintype ι] {N : ℕ} (σ : Fin N → ι → Bool) (e : ι → Bool) : ℝ := by … - theorem
OAI.DilutedSpinGlass.Pattern.empirical_nonnegline 467 - theorem
OAI.DilutedSpinGlass.Pattern.empirical_totalline 471Source documentation
The normalization uses N>=1, as required for reservoir sizes.
theorem empirical_total {ι : Type*} [Fintype ι] [DecidableEq ι] {N : ℕ} (hN : 0 < N) (σ : Fin N → ι → Bool) : (∑ e, empirical σ e) = 1 := by …Mentions: OAI.DilutedSpinGlass.Pattern.empirical
- theorem
OAI.DilutedSpinGlass.Pattern.empirical_momentline 482 - theorem
OAI.DilutedSpinGlass.Pattern.mass_le_oneline 503 - theorem
OAI.DilutedSpinGlass.Pattern.mass_abs_averageline 509 - theorem
OAI.DilutedSpinGlass.Pattern.bounded_integrableline 518 - def
OAI.DilutedSpinGlass.Pattern.meanMassline 524Source documentation
The unconditional spin-pattern distribution, not a conditional law.
noncomputable def meanMass (P : Ω → α → ℝ) (x : α) : ℝ := ∫ ω, P ω x ∂μ …
- theorem
OAI.DilutedSpinGlass.Pattern.meanMass_nonnegline 527 - theorem
OAI.DilutedSpinGlass.Pattern.meanMass_totalline 530 - theorem
OAI.DilutedSpinGlass.Pattern.meanMass_momentline 543Source documentation
Averaging the empirical law reproduces the expected multioverlaps.
theorem meanMass_moment {ι : Type*} [Fintype ι] [DecidableEq ι] (P : Ω → (ι → Bool) → ℝ) (hm : ∀ x, Measurable (fun ω => P ω x)) (hP : ∀ ω x, 0 ≤ P ω x) (hPt : ∀ ω, ∑ x, P ω x = 1) (S : Finset ι) : moment (meanMass (μ := μ) P) S = ∫ ω, moment (P ω) S ∂μ := by …Mentions: OAI.DilutedSpinGlass.Pattern.moment, OAI.DilutedSpinGlass.Pattern.meanMass
- theorem
OAI.DilutedSpinGlass.Pattern.expected_pattern_replacementline 557Source documentation
The integrated empirical-pattern comparison, valid for arbitrary reservoir root laws. This is comp:pattern-error; conditioning on independent new insertion disorder can subsequently be performed without changing the bound.
theorem expected_pattern_replacement {ι : Type*} [Fintype ι] [DecidableEq ι] (P : Ω → (ι → Bool) → ℝ) (hm : ∀ x, Measurable (fun ω => P ω x)) (hP : ∀ ω x, 0 ≤ P ω x) (hPt : ∀ ω, ∑ x, P ω x = 1) (a : ℕ) (f : (Fin a → (ι → Bool)) → ℝ) (hf : ∀ x, |f x| ≤ 1) : |(∫ ω, ∑ x, (∏ i, P ω (x i))*f x ∂μ) - (∑ x, (∏ i, meanMass (μ := μ) P (x i))*f x)| ≤ …Mentions: OAI.DilutedSpinGlass.Pattern.meanMass
- lemma
OAI.DilutedSpinGlass.limsup_finite_boundline 612 - lemma
OAI.DilutedSpinGlass.series_double_limitline 638Source documentation
Uniform summable remainders commute with the ordered limsup/grid limits. No diagonal exchange of the two limits is used.
lemma series_double_limit (a : ℕ → ℕ → ℝ) (f : ℕ → ℕ → ℕ → ℝ) (c tail : ℕ → ℝ) (ha : ∀ L n, 0≤a L n) (hab : ∀ L, IsBoundedUnder (·≤·) atTop (a L)) (hc : ∀ k, 0≤c k) (hf : ∀ k L, IsBoundedUnder (·≤·) atTop (f k L)) (hflim : ∀ k, Tendsto (fun L => limsup (f k L) atTop) atTop (𝓝 0)) (htail : Tendsto tail atTop (𝓝 0)) (h : ∀ K L n, a L n≤tail K+∑ k∈Finset.range K, c k*f k L n) : Tendsto (fun L => limsup (a L) atTop) atTop (𝓝 0) := by …