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Thursday, October 11, 2012

There is no translation-invariant measure on an infinite-dimensional space

One difficulty in carrying out analysis on an infinite-dimensional normed vector space, e.g. L^p(\mathbb{R}), is that there is no analogue of Lebesgue measure on such a space. This comes from the observation that an open ball in an infinite-dimensional normed vector space contains infinitely many disjoint open balls of the same radius. We first give a formal statement of our goal.

Theorem. Let X be an infinite-dimensional normed vector space. Then there is no translational-invariant Borel measure \mu on X such that \mu(U) > 0 for every nonempty open set U and \mu(U_0) < \infty for some open set U_0.

To prove the theorem, we recall Riesz's Lemma.

Lemma (Riesz). Let X be a normed vector space and Y be a proper closed subspace. For every \epsilon > 0, there exists x \in X such that \|x\| = 1 and \mathrm{dist}(x, Y) = \inf\{\|x - y\|: y \in Y\} \geq 1 - \epsilon.

Proof of Theorem: Suppose \mu is a translation-invariant Borel measure on X with \mu(U) > 0 for every nonempty open U \subseteq X. Fix a nonempty open set U in X. Then there exists r > 0 and x_0 \in X such that W = r(U + x_0) contains B = \{x \in X: \|x\| < 2 \}. Using Riesz's Lemma and induction, we can find a sequence \{x_n\} of unit vectors in X such that \mathrm{dist}(x_{n + 1}, \mathrm{span}\{x_1, \ldots, x_n\}) \geq 1/2 for all n \geq 1. Hence \{x_n\} \subseteq B and \|x_n - x_m\| \geq 1/2 whenever n \neq m. Take B_n = \{x \in X: \|x - x_n\| < 1/2 \}, then \{B_n\} is a disjoint collection of open balls contained in B of radius half. Now let U_n = \frac{1}{r}B_n - x_0, then \{U_n\} is a disjoint collection of open balls contained in U of the same radius. It follows that  \mu(U) \geq \mu(\bigcup_{n = 1}^\infty U_n) = \sum_{n = 1}^\infty \mu(U_n) = \sum_{n = 1}^\infty \mu(U_1)  by translation-invariance of \mu. But \mu(U_1) > 0, forcing \mu(U) = \infty.

Reference:
Fabian, Habala, Hajek, Montesinos, Zizler - Banach Space Theory: The Basis for Linear and Nonlinear Analysis

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