Measurable space

Borel space

$ \newcommand{\R}{\mathbb R} \newcommand{\C}{\mathbb C} \newcommand{\Om}{\Omega} \newcommand{\A}{\mathcal A} \newcommand{\B}{\mathcal B} \newcommand{\P}{\mathbf P} $ A set with a distinguished σ-algebra of subsets (called measurable). More formally: a pair $(X,\A)$ consisting of a set $X$ and a σ-algebra $\A$ of subsets of $X$.

Examples: $\R^n$ with the Borel σ-algebra; $\R^n$ with the Lebesgue σ-algebra.

Let $(X,\A)$ and $(Y,\B)$ be measurable spaces.

• A map $f:X\to Y$ is called measurable if $f^{-1}(B) \in \A$ for every $B\in\B$.
• These two measurable spaces are called isomorphic if there exists a bijection $f:X\to Y$ such that $f$ and $f^{-1}$ are measurable (such $f$ is called an isomorphism).

Let $X$ be a set, $(Y,\B)$ a measurable space, and $(f_i)_{i\in I}$ a family of maps $f_i:X\to Y$. The σ-algebra generated by these maps is defined as the smallest σ-algebra $\A$ on $X$ such that all $f_i$ are measurable from $(X,\A)$ to $(Y,\B)$. More generally, one may take measurable spaces $(Y_i,\B_i)$ and maps $f_i:X\to Y_i$. On the other hand, if $Y$ is $\R$ (or $\C$, $\R^n$ etc.) then $\B$ is by default the Borel σ-algebra.

Given a family of measurable spaces $(X_i,\A_i)$ for $i\in I$, their product is defined as the measurable space $(X,\A)$ where $X=\prod_i X_i$ is the direct product of sets, and $\A$ is generated by the projection maps $p_i:X\to X_i$ [3, Sect. 10.B].

Example and warning. Denoting the Borel σ-algebra on $\R^n$ by $ \B_n $ and the Lebesgue σ-algebra on $\R^n$ by $ \A_n $ we have $ (\R^m,\B_m) \times (\R^n,\B_n) = (\R^{m+n},\B_{m+n}) $ but $ (\R^m,\A_m) \times (\R^n,\A_n) \ne (\R^{m+n},\A_{m+n}) $ [1, Exercise 1.7.19]. Denoting $ (\R^m,\A_m) \times (\R^n,\A_n) = (\R^{m+n},\A_{m,n}) $ we have for every $ A \in \A_{m,n} $ \begin{align*} &\{y\in\R^n:(x,y)\in A\} \in \B_n \quad \text{for almost all } x\in\R^m,\\ &\{x\in\R^m:(x,y)\in A\} \in \B_m \quad \text{for almost all } y\in\R^n. \end{align*} In particular, a set of the form $ \{(x,y)\in\R^2:x-y\in B\} $ belongs to $ \A_{1,1}$ if and only if $B\in\B_1$.

Every topology generates a σ-algebra, called Borel σ-algebra. That is, the Borel σ-algebra on a topological space is, by definition, generated by the open sets.

Example. The following three σ-algebras on a separable Hilbert space $H$ are equal:

• the σ-algebra generated by the linear functionals $ x \mapsto \langle x,y \rangle $ for $y\in H$;
• the Borel σ-algebra corresponding to the norm topology on $H$;
• the Borel σ-algebra corresponding to the weak topology on $H$.

That is instructive: topological spaces are not a prerequisite to measurable spaces.

The Borel σ-algebra is not the only bridge between topological and measurable spaces. All sets having the Baire property (sometimes called Baire sets, which may be confusing) are a σ-algebra (generated by open sets together with meager sets) greater than Borel [3, Sect.8.F]. On the other hand, all compact $G_\delta$ subsets of a compact Hausdorff topological space generate a σ-algebra (smaller than Borel) of sets called Baire sets in [4, Sect.7.1], [5, Sect.51]. For more general (in particular, uncountable discrete) topological spaces the definitions of [4] and [5] disagree. Note also the σ-algebra of universally measurable sets.

Older terminology

Weaker assumptions on $\A$ were usual in the past. For example, according to [5], $\A$ need not contain the whole $X$, it is a σ-ring, not necessarily a σ-algebra. According to [6], a measurable space is not a pair $(X,\A)$ but a measure space $(X,\A,\mu)$ such that $X\in\A$ (and again, $\A$ is generally a σ-ring).

References

[1]	Terence Tao, "An introduction to measure theory", AMS (2011) MR2827917
[2]	David Pollard, "A user's guide to measure theoretic probability", Cambridge (2002) MR1873379
[3]	Alexander S. Kechris, "Classical descriptive set theory", Springer-Verlag (1995) MR1321597
[4]	Richard M. Dudley, "Real analysis and probability", Wadsworth&Brooks/Cole (1989) MR0982264
[5]	Paul R. Halmos, "Measure theory", v. Nostrand (1950) MR0033869
[6]	Walter Rudin, "Principles of mathematical analysis", McGraw-Hill (1953) MR0055409