Show Borel Measure of a Closed Ball is Upper Semi Continuous

Measure defined on all open sets of a topological space

In mathematics, specifically in measure theory, a Borel measure on a topological space is a measure that is defined on all open sets (and thus on all Borel sets).[1] Some authors require additional restrictions on the measure, as described below.

Formal definition [edit]

Let X {\displaystyle X} be a locally compact Hausdorff space, and let B ( X ) {\displaystyle {\mathfrak {B}}(X)} be the smallest σ-algebra that contains the open sets of X {\displaystyle X} ; this is known as the σ-algebra of Borel sets. A Borel measure is any measure μ {\displaystyle \mu } defined on the σ-algebra of Borel sets.[2] A few authors require in addition that μ {\displaystyle \mu } is locally finite, meaning that μ ( C ) < {\displaystyle \mu (C)<\infty } for every compact set C {\displaystyle C} . If a Borel measure μ {\displaystyle \mu } is both inner regular and outer regular, it is called a regular Borel measure. If μ {\displaystyle \mu } is both inner regular, outer regular, and locally finite, it is called a Radon measure.

On the real line [edit]

The real line R {\displaystyle \mathbb {R} } with its usual topology is a locally compact Hausdorff space, hence we can define a Borel measure on it. In this case, B ( R ) {\displaystyle {\mathfrak {B}}(\mathbb {R} )} is the smallest σ-algebra that contains the open intervals of R {\displaystyle \mathbb {R} } . While there are many Borel measures μ, the choice of Borel measure that assigns μ ( ( a , b ] ) = b a {\displaystyle \mu ((a,b])=b-a} for every half-open interval ( a , b ] {\displaystyle (a,b]} is sometimes called "the" Borel measure on R {\displaystyle \mathbb {R} } . This measure turns out to be the restriction to the Borel σ-algebra of the Lebesgue measure λ {\displaystyle \lambda } , which is a complete measure and is defined on the Lebesgue σ-algebra. The Lebesgue σ-algebra is actually the completion of the Borel σ-algebra, which means that it is the smallest σ-algebra that contains all the Borel sets and has a complete measure on it. Also, the Borel measure and the Lebesgue measure coincide on the Borel sets (i.e., λ ( E ) = μ ( E ) {\displaystyle \lambda (E)=\mu (E)} for every Borel measurable set, where μ {\displaystyle \mu } is the Borel measure described above).

Product spaces [edit]

If X and Y are second-countable, Hausdorff topological spaces, then the set of Borel subsets B ( X × Y ) {\displaystyle B(X\times Y)} of their product coincides with the product of the sets B ( X ) × B ( Y ) {\displaystyle B(X)\times B(Y)} of Borel subsets of X and Y.[3] That is, the Borel functor

B o r : T o p 2 C H a u s M e a s {\displaystyle \mathbf {Bor} \colon \mathbf {Top} _{2CHaus}\to \mathbf {Meas} }

from the category of second-countable Hausdorff spaces to the category of measurable spaces preserves finite products.

Applications [edit]

Lebesgue–Stieltjes integral [edit]

The Lebesgue–Stieltjes integral is the ordinary Lebesgue integral with respect to a measure known as the Lebesgue–Stieltjes measure, which may be associated to any function of bounded variation on the real line. The Lebesgue–Stieltjes measure is a regular Borel measure, and conversely every regular Borel measure on the real line is of this kind.[4]

Laplace transform [edit]

One can define the Laplace transform of a finite Borel measure μ on the real line by the Lebesgue integral[5]

( L μ ) ( s ) = [ 0 , ) e s t d μ ( t ) . {\displaystyle ({\mathcal {L}}\mu )(s)=\int _{[0,\infty )}e^{-st}\,d\mu (t).}

An important special case is where μ is a probability measure or, even more specifically, the Dirac delta function. In operational calculus, the Laplace transform of a measure is often treated as though the measure came from a distribution function f. In that case, to avoid potential confusion, one often writes

( L f ) ( s ) = 0 e s t f ( t ) d t {\displaystyle ({\mathcal {L}}f)(s)=\int _{0^{-}}^{\infty }e^{-st}f(t)\,dt}

where the lower limit of 0 is shorthand notation for

lim ε 0 ε . {\displaystyle \lim _{\varepsilon \downarrow 0}\int _{-\varepsilon }^{\infty }.}

This limit emphasizes that any point mass located at 0 is entirely captured by the Laplace transform. Although with the Lebesgue integral, it is not necessary to take such a limit, it does appear more naturally in connection with the Laplace–Stieltjes transform.

Hausdorff dimension and Frostman's lemma [edit]

Given a Borel measure μ on a metric space X such that μ(X) > 0 and μ(B(x, r)) ≤ rs holds for some constant s > 0 and for every ball B(x, r) in X, then the Hausdorff dimension dimHaus(X) ≥ s. A partial converse is provided by the Frostman lemma:[6]

Lemma: Let A be a Borel subset of R n , and let s > 0. Then the following are equivalent:

  • H s (A) > 0, where H s denotes the s-dimensional Hausdorff measure.
  • There is an (unsigned) Borel measure μ satisfying μ(A) > 0, and such that
μ ( B ( x , r ) ) r s {\displaystyle \mu (B(x,r))\leq r^{s}}
holds for all x ∈R n and r > 0.

Cramér–Wold theorem [edit]

The Cramér–Wold theorem in measure theory states that a Borel probability measure on R k {\displaystyle \mathbb {R} ^{k}} is uniquely determined by the totality of its one-dimensional projections.[7] It is used as a method for proving joint convergence results. The theorem is named after Harald Cramér and Herman Ole Andreas Wold.

References [edit]

  1. ^ D. H. Fremlin, 2000. Measure Theory Archived 2010-11-01 at the Wayback Machine. Torres Fremlin.
  2. ^ Alan J. Weir (1974). General integration and measure. Cambridge University Press. pp. 158–184. ISBN0-521-29715-X.
  3. ^ Vladimir I. Bogachev. Measure Theory, Volume 1. Springer Science & Business Media, Jan 15, 2007
  4. ^ Halmos, Paul R. (1974), Measure Theory , Berlin, New York: Springer-Verlag, ISBN978-0-387-90088-9
  5. ^ Feller 1971, §XIII.1
  6. ^ Rogers, C. A. (1998). Hausdorff measures. Cambridge Mathematical Library (Third ed.). Cambridge: Cambridge University Press. pp. xxx+195. ISBN0-521-62491-6.
  7. ^ K. Stromberg, 1994. Probability Theory for Analysts. Chapman and Hall.

Further reading [edit]

  • Gaussian measure, a finite-dimensional Borel measure
  • Feller, William (1971), An introduction to probability theory and its applications. Vol. II., Second edition, New York: John Wiley & Sons, MR 0270403 .
  • J. D. Pryce (1973). Basic methods of functional analysis. Hutchinson University Library. Hutchinson. p. 217. ISBN0-09-113411-0.
  • Ransford, Thomas (1995). Potential theory in the complex plane. London Mathematical Society Student Texts. Vol. 28. Cambridge: Cambridge University Press. pp. 209–218. ISBN0-521-46654-7. Zbl 0828.31001.
  • Teschl, Gerald, Topics in Real and Functional Analysis, (lecture notes)
  • Wiener's lemma related

External links [edit]

  • Borel measure at Encyclopedia of Mathematics

lewismights.blogspot.com

Source: https://en.wikipedia.org/wiki/Borel_measure

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