A positive tilt matches the Poisson denominator
Mathematical statement
The selected positive tilt puts the Gaussian denominator into the source Poisson-kernel form.
Lean statement · selected_tilt
Only the standing n and kappa assumptions; all positivity and matching are conclusions.
Braces mark parameters Lean can infer; square brackets request structures such as a measurable space or probability measure. Named hypotheses are mathematical premises, not facts established by this declaration. Section parameters are described in the mathematical hypotheses above; the module link retains their exact source context.
theorem selected_tilt {n : ℕ} (hn : 3 ≤ n) {κ : ℝ} (hκ : 4 ≤ κ) :
let r : ℝ := (1 - 1 / (n : ℝ)) * ((Real.sqrt κ - 1) / (Real.sqrt κ + 1))
let ℓ : ℝ := (4 * (n : ℝ) * Real.sqrt κ + (Real.sqrt κ - 1) ^ 2) /
(8 * (n : ℝ) * ((n : ℝ) - 1))
0 < r ∧ r < 1 ∧ 0 < ℓ ∧
ℓ = (κ - 1) / (8 * r) * (1 + r ^ 2) - (κ + 1) / 4 ∧
(κ - 1) / (2 * r) = (n : ℝ) * (Real.sqrt κ + 1) ^ 2 /
(2 * ((n : ℝ) - 1)) ∧
(∀ u : ℝ,
κ + 1 + 4 * ℓ - (κ - 1) * u =
(κ - 1) / (2 * r) * (1 + r ^ 2 - 2 * r * u) ∧
(κ - 1) / (2 * r) * (1 + r ^ 2 - 2 * r * u) =
((n : ℝ) * (Real.sqrt κ + 1) ^ 2 / (2 * ((n : ℝ) - 1))) *
(1 + r ^ 2 - 2 * r * u))This supplies the positive tilt and scalar matching for Eq23; the actual sphere/Poisson integral remains open.
Full assumptions and notation
All objects and hypotheses
- Natural \(n\ge3\) and real \(\kappa\ge4\), including \(\kappa=4\).
- Every subtraction and division involving \(n\) is real arithmetic after coercion. The matching variable \(u\) is any real number. No domain estimate is supplied as a premise.
Notation and interpretation
- \(s,r,\ell\)
Literal source parameter choices; s is shorthand for the real square root.
\[s=\sqrt\kappa,\quad r=\left(1-\frac1n\right)\frac{s-1}{s+1},\quad\ell=\frac{4ns+(s-1)^2}{8n(n-1)}.\]- \(D_\ell(u)\)
Affine denominator from the already formalized Gaussian transform.
\[D_\ell(u)=\kappa+1+4\ell-(\kappa-1)u.\]
Mathematical proof
1. Establish the parameter domains
The standing source assumptions keep every denominator away from zero. These are conclusions derived internally, not extra caller premises.
Corresponding Lean step
hs, hs2, hn3, hn0 and hn1 use the canonical Real.le_sqrt_of_sq_le and Real.sq_sqrt declarations and real arithmetic.
2. Shrink the spectral ratio
Both factors defining r lie strictly between zero and one. Rewrite r into a single rational expression for later normalization.
Corresponding Lean step
hfactor, hfactor1, hratio and hratio1 use positive division; hr, hr1 and hreq establish the exact source radius and its domain.
3. Choose a strictly positive tilt
The closed-form numerator is positive and its denominator is positive. Clearing these established nonzero denominators recovers the other presentation of the same source tilt.
Corresponding Lean step
hℓ proves positivity from the literal formula. hell rewrites kappa=s² and the exact hreq radius; field arithmetic checks the equality.
4. Normalize the positive coefficient
Factor the spectral difference and cancel only factors already proved nonzero. This makes explicit the scalar coefficient equality underlying the second source line of Eq23.
Corresponding Lean step
hcoeff uses hs2 and hreq followed by canonical field normalization. This is supplied scalar bookkeeping, not an additional displayed source theorem or a sphere-law assertion.
5. Match the entire affine denominator
Substitute the recovered tilt formula, collect the affine terms, and replace the coefficient. The calculation is valid for any real u. Positivity for arbitrary real u is not claimed; the source later uses its bounded actual coordinate U.
Corresponding Lean step
The final forall-u block expands hell and then rewrites hcoeff. The separate actual_gaussian_transform consumer can use the proved ell>0; Poisson evaluation and Eq24 are not inferred.
Lean verification
Lean proof · selected_tilt
Positive rational factors and canonical square-root/field arithmetic.
Braces mark parameters Lean can infer; square brackets request structures such as a measurable space or probability measure. Named hypotheses are mathematical premises, not facts established by this declaration. Section parameters are described in the mathematical hypotheses above; the module link retains their exact source context.
theorem selected_tilt {n : ℕ} (hn : 3 ≤ n) {κ : ℝ} (hκ : 4 ≤ κ) :
let r : ℝ := (1 - 1 / (n : ℝ)) * ((Real.sqrt κ - 1) / (Real.sqrt κ + 1))
let ℓ : ℝ := (4 * (n : ℝ) * Real.sqrt κ + (Real.sqrt κ - 1) ^ 2) /
(8 * (n : ℝ) * ((n : ℝ) - 1))
0 < r ∧ r < 1 ∧ 0 < ℓ ∧
ℓ = (κ - 1) / (8 * r) * (1 + r ^ 2) - (κ + 1) / 4 ∧
(κ - 1) / (2 * r) = (n : ℝ) * (Real.sqrt κ + 1) ^ 2 /
(2 * ((n : ℝ) - 1)) ∧
(∀ u : ℝ,
κ + 1 + 4 * ℓ - (κ - 1) * u =
(κ - 1) / (2 * r) * (1 + r ^ 2 - 2 * r * u) ∧
(κ - 1) / (2 * r) * (1 + r ^ 2 - 2 * r * u) =
((n : ℝ) * (Real.sqrt κ + 1) ^ 2 / (2 * ((n : ℝ) - 1))) *
(1 + r ^ 2 - 2 * r * u)) := by
let s := Real.sqrt κ
have hs : (2 : ℝ) ≤ s := Real.le_sqrt_of_sq_le (by nlinarith)
have hs0 : 0 < s := by linarith
have hm : 0 < s - 1 := by linarith
have hp : 0 < s + 1 := by linarith
have hs2 : s ^ 2 = κ := Real.sq_sqrt (by linarith)
have hn3 : (3 : ℝ) ≤ n := by exact_mod_cast hn
have hn0 : (0 : ℝ) < n := by linarith
have hn1 : (0 : ℝ) < (n : ℝ) - 1 := by linarith
let r : ℝ := (1 - 1 / (n : ℝ)) * ((s - 1) / (s + 1))
let ℓ : ℝ := (4 * (n : ℝ) * s + (s - 1) ^ 2) /
(8 * (n : ℝ) * ((n : ℝ) - 1))
change 0 < r ∧ r < 1 ∧ 0 < ℓ ∧ _
have hfactor : 0 < (1 : ℝ) - 1 / (n : ℝ) := by
have hdiv : (1 : ℝ) / n < 1 := (div_lt_one hn0).2 (by linarith)
linarith
have hfactor1 : (1 : ℝ) - 1 / (n : ℝ) < 1 := by
have : (0 : ℝ) < 1 / (n : ℝ) := one_div_pos.mpr hn0
linarith
have hratio : 0 < (s - 1) / (s + 1) := div_pos hm hp
have hratio1 : (s - 1) / (s + 1) < 1 := (div_lt_one hp).2 (by linarith)
have hr : 0 < r := mul_pos hfactor hratio
have hr1 : r < 1 := by
dsimp [r]
nlinarith
have hℓ : 0 < ℓ := by dsimp [ℓ]; positivity
have hreq : r = ((n : ℝ) - 1) * (s - 1) / ((n : ℝ) * (s + 1)) := by
dsimp [r]
field_simp
have hcoeff : (κ - 1) / (2 * r) =
(n : ℝ) * (s + 1) ^ 2 / (2 * ((n : ℝ) - 1)) := by
rw [← hs2, hreq]
field_simp
ring
have hell : ℓ = (κ - 1) / (8 * r) * (1 + r ^ 2) - (κ + 1) / 4 := by
rw [← hs2, hreq]
dsimp [ℓ]
field_simp
ring
refine ⟨hr, hr1, hℓ, hell, hcoeff, ?_⟩
intro u
change κ + 1 + 4 * ℓ - (κ - 1) * u =
(κ - 1) / (2 * r) * (1 + r ^ 2 - 2 * r * u) ∧
(κ - 1) / (2 * r) * (1 + r ^ 2 - 2 * r * u) =
((n : ℝ) * (s + 1) ^ 2 / (2 * ((n : ℝ) - 1))) *
(1 + r ^ 2 - 2 * r * u)
constructor
· rw [hell]
field_simp
ring
· rw [hcoeff]
end AutoSamplingTheory.ExampleCases.GaussianComplexity.SelectedTiltScope and omitted-condition boundaries
- Selected numerical tilt and all Eq22–23 scalar matching only. No sphere law/Poisson integral, Eq24 H evaluation, actual TV first ratio, amplification, transcript/query/cost, hidden-eigenbasis or main lower bound. Source zero-tilt remark is context, not an extra conclusion.
Sources, dependencies, and reuse
Source and reuse
Samplinglib parents called
Mathlib API called (external library)
- Real.le_sqrt_of_sq_le
- Real.sq_sqrt
- div_lt_one
- one_div_pos
- div_pos
- mul_pos
Mathematical sources
- Zhou-Suzuki, Eq. (22)-(23) — Only literal r/ell positivity and Eq22–23 denominator matching, including the coefficient equality; scalar identities hold for every real u, with no claim of positivity for every real u.
Samplinglib prose is not a quotation or a source-equivalence certificate. Definitions and aliases are explained as constructions, not counted as new mathematical proofs.