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Rademacher's theorem

Rademacher's theorem is a mathematics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Rademacher's theorem rather than just read about it. In short: In mathematical analysis, Rademacher's theorem, named after Hans Rademacher, states the following: If U is an open subset of Rn and f: U → Rm is Lipschitz continuous, then f is differentiable almost everywhere in U; that is, the points in U at which f is not differentiable form a set of Lebesgue measure zero. Differentiability here refers to infinitesimal approximability by a linear map, which in particular asserts…

Key takeaways

  • Rademacher's theorem belongs to mathematics; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Rademacher's theorem to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Rademacher's theorem from memory before moving on to harder problems.

Reference excerpt

In mathematical analysis, Rademacher's theorem, named after Hans Rademacher, states the following: If U is an open subset of Rn and f: U → Rm is Lipschitz continuous, then f is differentiable almost everywhere in U; that is, the points in U at which f is not differentiable form a set of Lebesgue measure zero. Differentiability here refers to infinitesimal approximability by a linear map, which in particular asserts the existence of the coordinate-wise partial derivatives.

Sketch of proof The one-dimensional case of Rademacher's theorem is a standard result in introductory texts on measure-theoretic analysis. In this context, it is natural to prove the more general statement that any single-variable function of bounded variation is differentiable almost everywhere. (This one-dimensional generalization of Rademacher's theorem fails to extend to higher dimensions.) One of the standard proofs of the general Rademacher theorem was found by Charles Morrey. In the following, let u denote a Lipschitz-continuous function on Rn. The first step of the proof is to show that, for any fixed unit vector v, the v-directional derivative of u exists almost everywhere. This is a consequence of a special case of the Fubini theorem: a measurable set in Rn has Lebesgue measure zero if its restriction to every line parallel to v has (one-dimensional) Lebesgue measure zero. Considering in particular the set in Rn where the v-directional derivative of u fails to exist (which must be proved to be measurable), the latter condition is met due to the one-dimensional case of Rademacher's theorem. The second step of Morrey's proof establishes the linear dependence of the v-directional derivative of u upon v. This is based upon the following identity:

∫ R n u ( x + h ν ) − u ( x ) h ζ ( x ) d L n ( x ) = − ∫ R n ζ ( x ) − ζ ( x − h ν ) h u ( x ) d L n ( x ) . {\displaystyle \int _{\mathbf {R} ^{n}}{\frac {u(x+h\nu )-u(x)}{h}}\zeta (x)\,d{\mathcal {L}}^{n}(x)=-\int _{\mathbf {R} ^{n}}{\frac {\zeta (x)-\zeta (x-h\nu )}{h}}u(x)\,d{\mathcal {L}}^{n}(x).}

Using the Lipschitz assumption on u, the dominated convergence theorem can be applied to replace the two difference quotients in the above expression by the corresponding v-directional derivatives. Then, based upon the known linear dependence of the v-directional derivative of ζ upon v, the same can be proved of u via the fundamental lemma of calculus of variations. At this point in the proof, the gradient (defined as the n-tuple of partial derivatives) is guaranteed to exist almost everywhere; for each v, the dot product with v equals the v-directional derivative almost everywhere (although perhaps on a smaller set). Hence, for any countable collection of unit vectors v1, v2, ..., there is a single set E of measure zero such that the gradient and each vi-directional derivative exist everywhere on the complement of E, and are linked by the dot product. By selecting v1, v2, ... to be dense in the unit sphere, it is possible to use the Lipschitz condition to prove the existence of every directional derivative everywhere on the complement of E, together with its representation as the dot product of the gradient with the direction. Morrey's proof can also be put into the context of generalized derivatives. Another proof, also via a reduction to the one-dimensional case, uses the technology of approximate limits.

Applications Rademacher's theorem can be used to prove that, for any p ≥ 1, the Sobolev space W1,p(Ω) is preserved under a bi-Lipschitz transformation of the domain, with the chain rule holding in its standard form. With appropriate modification, this also extends to the more general Sobolev spaces Wk,p(Ω). Rademacher's theorem is also significant in the study of geometric measure theory and rectifiable sets, as it allows the analysis of first-order differential geometry, specifically tangent planes and normal vectors. Higher-order concepts such as curvature remain more subtle, since their usual definitions require more differentiability than is achieved by the Rademacher theorem. In the presence of convexity, second-order differentiability is achieved by the Alexandrov theorem, the proof of which can be modeled on that of the Rademacher theorem. In some special cases, the Rademacher theorem is even used as part of the proof.

Generalizations Alberto Calderón proved the more general fact that if Ω is an open bounded set in Rn then every function in the Sobolev space W1,p(Ω) is differentiable almost everywhere, provided that p > n. Calderón's theorem is a relatively direct corollary of the Lebesgue differentiation theorem and Sobolev embedding theorem. Rademacher's theorem is a special case, due to the fact that any Lipschitz function on Ω is an element of the space W1,∞(Ω). There is a version of Rademacher's theorem that holds for Lipschitz functions from a Euclidean space into an arbitrary metric space in terms of metric differentials instead of the usual derivative.

See also Pansu derivative

References

Sources

External links Heinonen, Juha (2004). "Lectures on Lipschitz Analysis" (PDF). Lectures at the 14th Jyväskylä Summer School in August 2004. (Rademacher's theorem with a proof is on page 18 and further.)

Worked examples

Example 1 — a first encounter with Rademacher's theorem

Start with the simplest possible case. Write down what Rademacher's theorem claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Rademacher's theorem before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Rademacher's theorem ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Rademacher's theorem

In research
Rademacher's theorem appears in mathematics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Rademacher's theorem in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Rademacher's theorem is common in secondary-school and first-year university syllabi. It links to neighbouring topics Lipschitz maps, Theorems in measure theory, so understanding it makes those chapters shorter.
In everyday life
Look for Rademacher's theorem outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Rademacher's theorem in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Rademacher's theorem means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Rademacher's theorem out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Rademacher's theorem in simple terms?

In mathematical analysis, Rademacher's theorem, named after Hans Rademacher, states the following: If U is an open subset of Rn and f: U → Rm is Lipschitz continuous, then f is differentiable almost everywhere in U; that is, the points in U at which f is not differentiable form a set of Lebesgue me…

Why does Rademacher's theorem matter?

Because it connects several mathematics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Rademacher's theorem?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Rademacher's theorem.

Tags

  • Lipschitz maps
  • Theorems in measure theory

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