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The difference-quotient characterisation of for
Statement
Assume Countable Choice. Let be open, , and ; write and for the difference-quotient and gradient vectors, with (1) If and , then for every and every coordinate direction , At the vector estimate has constant one. The coordinate bound also holds on any open for a fixed for which every segment , , stays in ; compact containment is unnecessary. In particular, for tangential directions on a half-space . (2) Conversely, if , and there is with for every coordinate and all , then with , , and weakly in as . For , tangential quotients on also converge strongly: in as . Both parts are identities of classes and hold without any regularity of . At the converse in (2) is deliberately not asserted; the companion remark records why only a measure derivative survives there.
Facts & Assumptions
Given: Countable Choice; an open set with ; an open ; a scalar field ; the exponent range for part (1) and for part (2); a class in part (1) or a class with uniform difference-quotient bound in part (2); and a coordinate direction .
Difference quotients: on ; for one has , and for the class lies in with ; the definition depends only on the class of . (Difference quotients on a shrunken domain, The space as the quotient by null functions)
Sobolev classes: consists of the classes whose first weak derivatives lie in , and ; convergence in means convergence in of and of every . (Integer-order Sobolev spaces and their norms, The notation and the reserved zero-boundary symbol, Weak derivative of a locally integrable function)
Smooth approximation: is dense in for . (Meyers–Serrin density on an arbitrary open set)
Fundamental theorem of calculus and chain rule: for smooth and , the map is differentiable with derivative , so . (The second fundamental theorem: if is differentiable on with and is integrable, then , The chain rule for total derivatives: )
Jensen's inequality: on a probability space and for a convex , ; the normalized restriction of Lebesgue measure to , , is a probability measure, and is convex on . (Jensen's integral inequality for a probability measure)
Fubini for nonnegative integrands and translation invariance of Lebesgue measure: for measurable one has , and for one has and . (Tonelli's theorem for nonnegative measurable functions on a sigma-finite product, Fubini's theorem for L^1 functions on a sigma-finite product, Lebesgue outer measure, Lebesgue measurability and Lebesgue measure are unchanged by translation, A C^1 diffeomorphism satisfies the change-of-variables formula for L^1 functions)
Hölder's inequality with conjugate exponents on , and the triangle inequality in for . (Conjugate exponents, including the endpoint conventions, Holder's inequality for integrals, including the endpoint cases, Minkowski's inequality for integrals, including )
The weak-limit lemma: a uniform bound for and , , , gives , and for every . (Uniformly bounded difference quotients represent a weak derivative)
Translations are strongly continuous on for under Countable Choice. ( in as , for )
Proof
Let and . Take first and fix ; by [F4] and the convexity of , Jensen's inequality [F5] for the probability measure gives For the same computation applies with the segment from to and the average taken over .
For part (2), choose a finite with ; when and the distance is infinite, take ; the hypothesis is exactly the uniform bound required by the weak-limit lemma [F8], which gives with and the convergence for every ; by [F7] the latter is precisely weak convergence in .
Integrating the estimate of step 1.1 over and applying Fubini and the translation invariance of [F6] (every point with , between and , satisfies because ) gives, for either sign of , so .
Let now and and choose with , as [F3] permits. For fixed with , [F1] applied to gives , and by [F2]; step 2.1 applied to each and passage to the limit (norms are continuous) yield .
The coordinate argument in steps 1.1--3.1 works on any open with the segment condition: each translated set lies in , so Tonelli and change of variables bound its integral by the gradient norm on . For , fix a compact . The union of its segments is compact in , so choose a bounded open tube containing that union. For each finite , the same coordinate argument applied to gives . If the quotient exceeded this essential bound by on a positive-measure subset of , its norm would exceed , a contradiction as . Exhausting by compact sets proves the coordinate bound.
Tangential strong convergence. For a tangential direction on , smooth approximation [F3] and the fixed- translation bounds pass the segment formula to : as classes. Indeed Jensen and tangential change of variables bound the error between the averages of two gradient approximations by their distance. Extend by zero as an class on ; tangential shifts preserve , so [F9] gives uniformly for as . Jensen and Tonelli applied to the segment formula therefore give .
Vector estimate. Put and . Step 3.1 gives for each coordinate. If , the finite-dimensional inequalities yield . If , the triangle inequality in gives . For , step 4.1 gives a.e., hence . These finite-dimensional comparisons follow from Hölder applied to the finite sum. Thus the stated vector constant is valid, and equals one at . Each component uses its own coordinate segment; no common translated gradient vector is asserted.
Steps 3.1--4.1 prove (1) for every , and step 1.2 proves (2) for ; no step used any regularity of , only the containedness and the shrunken-domain definition of the quotients, so both assertions are identities of classes on arbitrary open sets.
Source notes
Hunter's Theorem 4.53 (printed pp. 125-126) states (1) with the mean value formula and (2) by weak compactness; Laugesen's Proposition 5.7 (printed pp. 110-111) and Simon's Lemma 7 record the same two directions. The companion remark on this page records the failure of (2) at . The scaffold dependency on def-sobolev-conjugate-exponent was replaced by Conjugate exponents, including the endpoint conventions: the exponents in Hölder's inequality are conjugate exponents, while the Sobolev conjugate is a different object.
Depends on
- Difference quotients on a shrunken domain
- Difference-quotient calculus: integration by parts, product rule, commutation
- Uniformly bounded difference quotients represent a weak derivative
- Integer-order Sobolev spaces and their norms
- Conjugate exponents, including the endpoint conventions
- Dominated convergence
- The Axiom of Countable Choice ($\mathrm{AC}_\omega$)
- Meyers–Serrin density on an arbitrary open set
- Jensen's integral inequality for a probability measure
- Fubini's theorem for L^1 functions on a sigma-finite product
- Lebesgue outer measure, Lebesgue measurability and Lebesgue measure are unchanged by translation
- A C^1 diffeomorphism satisfies the change-of-variables formula for L^1 functions
- The second fundamental theorem: if $G$ is differentiable on $[a,b]$ with $G' = f$ and $f$ is integrable, then $\int_a^b f = G(b)-G(a)$
- The chain rule for total derivatives: $D(g\circ f)(a)=Dg(f(a))\circ Df(a)$
- Weak derivative of a locally integrable function
- The notation $H^k$ and the reserved zero-boundary symbol
- The space $L^p(\mu)$ as the quotient by null functions
- Holder's inequality for integrals, including the endpoint cases
- Minkowski's inequality for integrals, including $p = \infty$
- Tonelli's theorem for nonnegative measurable functions on a sigma-finite product
- $\|\tau_h f - f\|_p \to 0$ in $L^p(\mathbb{R}^n)$ as $h \to 0$, for $1 \le p < \infty$
Used by
- Tangential H² estimate near a flat Dirichlet boundary Lemma
- The difference-quotient test function and its commutators Lemma
- At p=1 bounded difference quotients need not give an L¹ weak derivative Remark
- Higher-order boundary regularity for Dirichlet problems Theorem
- Interior H² estimate for constant-coefficient elliptic equations Theorem
- Interior H² regularity for divergence-form equations Theorem
Dependency tree · two levels
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Sources
- John K. Hunter, Notes on Partial Differential Equations (UC Davis, revised 18 June 2014, complete 242-page two-quarter graduate notes) (standard reference, not scraped)
- Richard S. Laugesen, Linear Analysis and Partial Differential Equations (University of Illinois, 2020, complete 158-page graduate notes) (standard reference, not scraped)
- Leon Simon, Lectures on Partial Differential Equations (Stanford, complete 223-page author scan) (standard reference, not scraped)