Uniform short Hilbert-transform bounds for Lipschitz directions
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Theorems selected for verification:OAI.LipschitzHilbert.mainOAI.LipschitzHilbert.uniform_truncation
The lines of the Lean statement that state the theorem, then the definitions in the file that it uses.
theoremmain : ∃ a : ℝ, a∈Ioo 0 (1/2) ∧ ∃ C : ℝ≥0, 0<C ∧ ShortHilbertConclusion a C := bysorry⋮theoremuniform_truncation : ∃ C : ℝ, 0<C ∧ ∀ K : ℝ≥0, 0<K → ∀ epsilon R : ℝ,0<epsilon → epsilon≤R → R≤1/(1000000*(K:ℝ)) → ∀ v : Plane → Plane, LipschitzWith K v → (∀ x, ‖v x‖=1) → ∀ f : SchwartzMap Plane ℂ, eLpNorm (shortTransform v epsilon R f) 2 volume≤ENNReal.ofReal (C*‖f.toLp 2 volume‖) := bysorry
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Definitions needed to read it
Local definitions the statement names, followed through the definitions they name in turn. The match is by name in the source text, so a name reached only through notation can be missed; the full file is below.
defshortTransform (v : DirectionPlane → DirectionPlane) (ε a : ℝ) (f : DirectionPlane → ℂ) (x : DirectionPlane) : ℂ := ∫ t in ε..a, t⁻¹ • (f (sample v t x) - f (sample v (-t) x))
deftwoSidedTruncation (v : DirectionPlane → DirectionPlane) (ε a : ℝ) (f : DirectionPlane → ℂ) (x : DirectionPlane) : ℂ := (∫ t in -a..-ε, directionalKernel v f x t) + ∫ t in ε..a, directionalKernel v f x t
defsmoothPrincipalValue (v : DirectionPlane → DirectionPlane) (a : ℝ) (f : DirectionPlane → ℂ) (x : DirectionPlane) : ℂ :=let g := fun t : ℝ => f (sample v t x)-f (sample v (-t) x) ∫ t in (0:ℝ)..a, Function.update (fun t => t⁻¹ • g t) 0 (deriv g 0) t
defShortHilbertConclusion (a : ℝ) (C : ℝ≥0) : Prop :=
Show the remaining 15 lines
∀ v : Plane → Plane, LipschitzWith 1 v → (∀ x, ‖v x‖=1) → (∀ epsilon : ℝ, 0<epsilon → epsilon<a → ∀ f : SchwartzMap Plane ℂ, eLpNorm (twoSidedTruncation v epsilon a f) 2 volume≤C*eLpNorm f 2 volume) ∧ (∀ f : SchwartzMap Plane ℂ, eLpNorm (smoothPrincipalValue v a f) 2 volume≤C*eLpNorm f 2 volume) ∧ (∀ f : SchwartzMap Plane ℂ, ∀ level : ℝ≥0∞, level≠0 → level≠∞ → volume {x | level<‖smoothPrincipalValue v a f x‖ₑ}≤ level⁻¹^2*((C:ℝ≥0∞)*eLpNorm f 2 volume)^2) ∧ (∀ epsilon : ℝ, 0<epsilon → epsilon<a → ∃ T : Lp ℂ 2 (volume : Measure Plane) →L[ℂ] Lp ℂ 2 volume, ‖T‖≤C ∧ ∀ f : SchwartzMap Plane ℂ, (T (f.toLp 2 volume) : Plane → ℂ)=ᵐ[volume] twoSidedTruncation v epsilon a f) ∧ (∃ T : Lp ℂ 2 (volume : Measure Plane) →L[ℂ] Lp ℂ 2 volume, ‖T‖≤C ∧ ∀ f : SchwartzMap Plane ℂ, (T (f.toLp 2 volume) : Plane → ℂ)=ᵐ[volume] smoothPrincipalValue v a f)
Possible paper match, with no recorded review
Atlas selected this possible match by comparing words in the Lean statement with every statement in the family. No review of whether the statements mean the same thing is recorded.
Words of the Lean statement, its names split into words, that also appear in the theorem: principal, value, symmetric, 1/2, field, lipschitz, epsilon and norm. Found in the paper’s title, which its main theorem states: directions, transform, uniform, hilbert and estimate. Shared only with the release’s name for the Lean statement or OpenAI’s note on it: constants.
Theorem 1.1 of A uniform Hilbert transform estimate for Lipschitz directions
Theorem
There are absolute constants a_*\in(0,1/2) and C_*<\infty such that every Lipschitz field v:\R^2\to S^1 with \Lip(v)\le1 satisfies
There are absolute constants \(a_*\in(0,1/2)\) and \(C_*<\infty\)
such that every Lipschitz field \(v:\R^2\to S^1\) with
\(\Lip(v)\le1\) satisfies
\[
\sup_{0<\epsilon<a_*}
\norm{H_{v,a_*}^{\epsilon}f}_{L^2(\R^2)}
\le C_*\norm{f}_{L^2(\R^2)}
\qquad(f\in\mathcal S(\R^2)).
\]
Its symmetric principal value therefore satisfies
\[
\norm{H_{v,a_*}f}_2\le C_*\norm f_2,
\qquad
\big|\{x:|H_{v,a_*}f(x)|>\lambda\}\big|
\le C_*^2\lambda^{-2}\norm f_2^2
\quad(\lambda>0).
\]
Other possible paper matches, closest wording first
Proposition 1.9 of A uniform Hilbert transform estimate for Lipschitz directions. Words of the Lean statement, its names split into words, that also appear in the theorem: uniform and estimate. Found in the paper’s title, which its main theorem states: directions, transform, lipschitz and hilbert.
Proposition 1.15 of A uniform Hilbert transform estimate for Lipschitz directions. Words of the Lean statement, its names split into words, that also appear in the theorem: input, bounded, field, scales, form, epsilon and four more. Shared only with the release’s name for the Lean statement or OpenAI’s note on it: constants and one.
Proposition 2.1 of A uniform Hilbert transform estimate for Lipschitz directions. Words of the Lean statement, its names split into words, that also appear in the theorem: conclusions, 1/2, space, hilbert, estimates and norm. Shared only with the release’s name for the Lean statement or OpenAI’s note on it: one.
Theorem 7.5 of A uniform Hilbert transform estimate for Lipschitz directions. Words of the Lean statement, its names split into words, that also appear in the theorem: real, bounded, forms, interval, measurable and estimates. Shared only with the release’s name for the Lean statement or OpenAI’s note on it: one.
Proposition 4.1 of A uniform Hilbert transform estimate for Lipschitz directions. Words of the Lean statement, its names split into words, that also appear in the theorem: complex, space, epsilon, hilbert, estimates, measure and one more. Shared only with the release’s name for the Lean statement or OpenAI’s note on it: one and constant.
Theorem 1.4 of A uniform Hilbert transform estimate for Lipschitz directions. Words of the Lean statement, its names split into words, that also appear in the theorem: field, cutoff, epsilon, estimate and measure. Shared only with the release’s name for the Lean statement or OpenAI’s note on it: constants and one.
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Finds the whole advertised result stated or impliedTheir term: “full”.
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Their note: None; statement is exactly the short-scale uniform bound plus principal-value/weak-type consequences (not the full-scale Stein conjecture).
Definitions the group asks readers to compare with the paper: smoothPrincipalValue extends the symmetric quotient at 0 by Function.update ... 0 (deriv g 0) (custom, correct for Schwartz f); file temporarily removes/re-adds the instance instCommCStarAlgebraComplex to fix scalar-multiplication elaboration (harmless hack)
OpenAI’s own note on what this Lean statement covers
“The formalization proves uniform $L^2$ bounds for short Hilbert transforms along Lipschitz unit vector fields in the plane, including fields depending on both coordinates. For Lipschitz constant $K>0$, every hard truncation with $0<\varepsilon\le R\le1/(10^6K)$ has one universal $L^2$ bound on Schwartz functions, independent of the inner cutoff.”
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Supporting material
The complete Lean statement file
80 lines, copied from release version fd4aeeb. A name defined in this file links to its line; pointing at the name shows its definition.
Declared in this fileOpenAI’s library at fd4aeebOther linked names open the current documentation for Mathlib, Lean’s mathematical library.
Links in the file: 48 to its own declarations, 30 to Mathlib’s documentation. 10 declared names also link to the same declaration in OpenAI’s library. 2 identifiers stay plain because they resolve to no single declaration: variables Lean binds automatically, notation, or names the scan of the pinned sources did not find. OpenAI uses Mathlib version d13f23b. The linked documentation describes the current version, so names that have since changed may be missing there.
There are absolute constants \(a_*\in(0,1/2)\) and \(C_*<\infty\)
such that every Lipschitz field \(v:\R^2\to S^1\) with
\(\Lip(v)\le1\) satisfies
\[
\sup_{0<\epsilon<a_*}
\norm{H_{v,a_*}^{\epsilon}f}_{L^2(\R^2)}
\le C_*\norm{f}_{L^2(\R^2)}
\qquad(f\in\mathcal S(\R^2)).
\]
Its symmetric principal value therefore satisfies
\[
\norm{H_{v,a_*}f}_2\le C_*\norm f_2,
\qquad
\big|\{x:|H_{v,a_*}f(x)|>\lambda\}\big|
\le C_*^2\lambda^{-2}\norm f_2^2
\quad(\lambda>0).
\]
Theorem(Lacey–Li)
Let v:\R^2\to S^1 be Lipschitz and 0<\delta<1. Restrict to rectangles satisfying
Let \(v:\R^2\to S^1\) be Lipschitz and \(0<\delta<1\). Restrict to
rectangles satisfying
\[
L(R)\le \frac1{100\Lip(v)},\qquad
\abs{R\cap v^{-1}(\operatorname{EX}(R))}\ge\delta\abs R,
\]
where the first restriction is void when \(\Lip(v)=0\). Then
\[
\mathcal M_{v,\delta}h(z)
=\sup_R\frac{\one_R(z)}{\abs R}\int_R\abs h
\quad\text{satisfies}\quad
\norm{\mathcal M_{v,\delta}h}_{L^{2,\infty}}
\le C\delta^{-1/2}\norm h_2.
\]
Here the supremum is tested at every point of \(R\), and the constant
is independent of \(v\) and \(\delta\).
Theorem(Restricted estimate on a vertical band)
For the fixed absolute constants in (red:local-operator), there is an absolute C such that, for every field u with \abs u\le1 and \Lip(u)\le C_{\rm Lip}, every 0<\epsilon<a, every dyadic w, and every vertical band cutoff P_w,
For the fixed absolute constants in \eqref{red:local-operator}, there
is an absolute \(C\) such that, for every field \(u\) with
\(\abs u\le1\) and \(\Lip(u)\le C_{\rm Lip}\), every
\(0<\epsilon<a\), every dyadic \(w\), and every vertical band
cutoff \(P_w\),
\begin{equation}
\abs{\langle H_{u,a}^{\epsilon}P_w f,g\rangle}
\le C\bigl(1+\abs{\log(|F|/|E|)}\bigr)^{-3}
\sqrt{|F||E|}
\end{equation}
whenever \(F,E\subset I\times\R\) have positive finite measure,
\(\abs f\le\one_F\), \(\abs g\le\one_E\), and
\(\abs I\le b_0\).
Corollary
For \abs t\le b_0 and T as in red:commutator,
\norm{TC_t h-C_tTh}_2
\le C A(\mathfrak m)\abs t\,\norm h_2.
The constant is uniform over \abs u\le1, \Lip(u)\le C_{\rm Lip}.
For \(\abs t\le b_0\) and \(T\) as in \Cref{red:commutator},
\begin{equation}
\norm{TC_t h-C_tTh}_2
\le C A(\mathfrak m)\abs t\,\norm h_2.
\end{equation}
The constant is uniform over \(\abs u\le1\),
\(\Lip(u)\le C_{\rm Lip}\).
Proposition
The uniform restricted estimate in thm:band-restricted implies thm:main.
is a sum, with absolutely summable scalar coefficients, of averages of forms (eq:src-3). Each form satisfies red:packets, uniformly in w,m,\mathcal L, and has one common angular grid and common spatial lattices across components. The same assertion holds for m=1 with the original positive-frequency band cutoff in place of \widetilde Q_1. The sums can be obtained as limits of finite packet collections.
The diagonal form
\[
\sum_j\langle\mathcal A_{u,\mathcal L}
\widetilde Q_j f_j,g_j\rangle
\]
is a sum, with absolutely summable scalar coefficients, of averages
of forms \eqref{eq:src-3}. Each form satisfies
\Cref{red:packets}, uniformly in \(w,m,\mathcal L\), and has one
common angular grid and common spatial lattices across components.
The same assertion holds for \(m=1\) with the original
positive-frequency band cutoff in place of \(\widetilde Q_1\).
The sums can be obtained as limits of finite packet collections.
Proposition
Suppose that the following bounds hold, uniformly for every admissible finite form \Lambda_{\mathcal S} in red:packets, with the fixed packet constants there. The field u:\R^2\to\R is bounded and measurable, the sets F,E\subset\R^2 are measurable with positive finite measure, and the input and test satisfy \norm{f(z)}_{\mathcal H}\le\one_F(z), \norm{g(z)}_{\mathcal H}\le\one_E(z).
(i)
For m\ge1, there is a fixed exponent C_1 such that
For L\ge L_0, with \tau,m,W as in (red:small-time-parameters), assume in addition that \abs u\le1, \Lip(u)\le C_{\rm Lip}, and F,E\subset I\times\R for an interval I with \abs I\le b_0. Whenever L/2\le\log\sqrt{|E|/|F|}\le2L,
|\Lambda_{\mathcal S}(f,g)|
\le C L^{-20}\sqrt{|F||E|}.
(iii)
For m=1, one scalar component, and |E|\le|F|, there is a fixed c>0 such that
Suppose that the following bounds hold, uniformly for every admissible
finite form \(\Lambda_{\mathcal S}\) in
\Cref{red:packets}, with the fixed packet constants there.
The field \(u:\R^2\to\R\) is bounded and measurable, the sets
\(F,E\subset\R^2\) are measurable with positive finite measure,
and the input and test satisfy
\(\norm{f(z)}_{\mathcal H}\le\one_F(z)\),
\(\norm{g(z)}_{\mathcal H}\le\one_E(z)\).
\begin{enumerate}[label=\textup{(\roman*)}]
\item For \(m\ge1\), there is a fixed exponent \(C_1\) such that
\begin{equation}
|\Lambda_{\mathcal S}(f,g)|
\le C(1+\log(2m))^{C_1}\sqrt{|F||E|}.
\end{equation}
\item For \(L\ge L_0\), with \(\tau,m,W\) as in
\eqref{red:small-time-parameters}, assume in addition that
\(\abs u\le1\), \(\Lip(u)\le C_{\rm Lip}\), and
\(F,E\subset I\times\R\) for an interval \(I\) with
\(\abs I\le b_0\). Whenever
\(L/2\le\log\sqrt{|E|/|F|}\le2L\),
\begin{equation}
|\Lambda_{\mathcal S}(f,g)|
\le C L^{-20}\sqrt{|F||E|}.
\end{equation}
\item For \(m=1\), one scalar component, and \(|E|\le|F|\),
there is a fixed \(c>0\) such that
\begin{equation}
|\Lambda_{\mathcal S}(f,g)|
\le C\sqrt{|F||E|}(|E|/|F|)^c.
\end{equation}
\end{enumerate}
Then \Cref{thm:band-restricted} holds. The constants remain uniform
in \(w\), \(\epsilon\), and the number of retained scales.
A uniform Hilbert transform estimate for Lipschitz directions
TeX label thm:main, build/sections/01-introduction.tex, line 17
The Lean statement says
theoremmain : ∃ a : ℝ, a∈Ioo 0 (1/2) ∧ ∃ C : ℝ≥0, 0<C ∧ ShortHilbertConclusion a C := bysorry⋮theoremuniform_truncation : ∃ C : ℝ, 0<C ∧ ∀ K : ℝ≥0, 0<K → ∀ epsilon R : ℝ,0<epsilon → epsilon≤R → R≤1/(1000000*(K:ℝ)) → ∀ v : Plane → Plane, LipschitzWith K v → (∀ x, ‖v x‖=1) → ∀ f : SchwartzMap Plane ℂ, eLpNorm (shortTransform v epsilon R f) 2 volume≤ENNReal.ofReal (C*‖f.toLp 2 volume‖) := bysorry
A Lean statement states the theorem and leaves its proof as sorry on purpose. OpenAI’s proof is in a separate solution module, and a program called Comparator checks that proof against this statement.
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