5. Lebesgue measure on \(\mathbb R^d\) and its properties PDF TEX

Lebesgue measure on \(\mathbb R^d\)

\(d\)-dimensional Lebesgue measure

Definition. Let \({\rm v}_d:J^d\to[0, \infty]\) be the volume function on \(\mathbb R^d\). The \(d\)-dimensional Lebesgue outer measure is defined for any \(E \subseteq \mathbb{R}^d\) by setting \[\begin{align*} \lambda_d^{*}(E)&=\inf\Big\{\sum_{n \in \mathbb{N}}{\rm v}_d(E_n): (E_n)_{n \in \mathbb{N}}\subseteq J_{co}^d\quad \text{ and } \quad E \subseteq \bigcup_{n \in \mathbb{N}}E_n\Big\}. \end{align*}\]

  • The \(d\)-dimensional Lebesgue measure \(\lambda_d\) is the restriction of \(\lambda_d^*\) to the Carathéodory \(\sigma\)-algebra \(\mathcal{L}(\mathbb R^d)=\mathcal{M}(\lambda_d^{*})\) of \(\lambda_d^{*}\)-measurable sets.

  • \(\mathcal{L}(\mathbb R^d)=\mathcal{M}(\lambda_d^{*})\) will be called the Lebesgue \(\sigma\)-algebra.

  • The members of \(\mathcal{L}(\mathbb R^d)\) are the Lebesgue measurable sets.

  • By Carathéodory’s theorem \((\mathbb R^d, \mathcal{L}(\mathbb R^d), \lambda_d)\) is a complete measure space. For any rectangle \(E\in J^d=J_o^d \cup J_{oc}^d \cup J_{co}^d \cup J_c^d\), we have \(\lambda_d(E)={\rm v}_d(E)\) and \(\lambda_d\) is \(\sigma\)-finite on \(\mathbb R^d\), and \({\rm Bor}(\mathbb R^d)\subseteq \mathcal{L}(\mathbb R^d)\).

  • If \(d=1\) we shall abbreviate \(\lambda_d^*\) to \(\lambda^*\) and \(\lambda_d\) to \(\lambda\).

Regularity of the Lebesgue measure

Theorem. For \(E \subseteq \mathbb{R}^d\) the following conditions are equivalent:

  1. \(E \in \mathcal L(\mathbb{R}^d)\);

  2. For every \(\varepsilon>0\) there exists an open set \(O \supseteq E\) so that \(\lambda_d^{*}(O \setminus E) \leq \varepsilon\);

  3. There exists a \(G_{\delta}\)-set \(G \supseteq E\) with \(\lambda_d^{*}(G \setminus E)=0\);

  4. For every \(\varepsilon>0\) there exists a closed set \(C \subseteq E\) with \(\lambda_d^*(E \setminus C) \leq \varepsilon\);

  5. There exists an \(F_{\sigma}\) set \(F \subseteq E\) with \(\lambda_d^*(E \setminus F)=0\).

Moreover, if \(E \in \mathcal L(\mathbb{R}^d)\), then one has \[\begin{align*} \lambda_d(E)&=\inf\{\lambda_d(U): U\supseteq E \text{ and } U \text{ is open}\}\\ &=\sup\{\lambda_d(F): F\subseteq E \text{ and } F \text{ is closed}\}\\ &=\sup\{\lambda_d(K): K\subseteq E \text{ and } K \text{ is compact}\}. \end{align*}\]

Step 1. We show that \(\lambda_d^{*}(E)=\inf\{\lambda_d(U): U \supseteq E \text{ and } U \text{ is open}\}\) for every \(E \subseteq \mathbb R^d\). Let \(\alpha(E)=\inf\{\lambda_d(U): U \supseteq E \text{ and } U \text{ is open}\}\).

  • By monotonicity \(\lambda_d^{*}(E) \leq \lambda_d(U)\) for every open \(U \supseteq E\), so \(\lambda_d^{*}(E)\) is not larger than the infimum, i.e. \(\lambda_d^{*}(E) \leq \alpha(E)\).

  • For the converse we may assume that \(\lambda_d^{*}(E)<\infty\), since otherwise there is nothing to do. Let \(\varepsilon>0\) and choose \((I_n)_{n \in \mathbb N} \subseteq J_{co}^d\) such that \[E \subseteq \bigcup_{n \in \mathbb N}I_n \quad \text{ and } \quad \sum_{n \in \mathbb N}{\rm v}_d(I_n) \leq \lambda_d^{*}(E)+\frac{\varepsilon}{2}.\]

  • If \(I_n=[a_n, b_n)\) we may enlarge it slightly to an open rectangle \(U_n \supseteq I_n\) with \({\rm v}_d(U_n) \leq {\rm v}_d(I_n)+\varepsilon 2^{-n-1}\).

  • Then \(U=\bigcup_{n \in \mathbb N}U_n\) is open, \(E \subseteq U\) and, by subadditivity, \[\alpha(E)\le \lambda_d(U) \leq \sum_{n \in \mathbb N}{\rm v}_d(U_n) \leq \sum_{n \in \mathbb N}{\rm v}_d(I_n)+\frac{\varepsilon}{2} \leq \lambda_d^{*}(E)+\varepsilon.\]

Step 2. We show that (i) \(\Longrightarrow\) (ii). Let \(E \in \mathcal L(\mathbb R^d)\) and \(\varepsilon>0\).

  • Assume first that \(\lambda_d(E)<\infty\). By Step 1 there is an open set \(O \supseteq E\) with \(\lambda_d(O) \leq \lambda_d(E)+\varepsilon\). Since \(E\) is measurable and \(\lambda_d(E)<\infty\), \[\lambda_d^{*}(O \setminus E)=\lambda_d(O)-\lambda_d(E) \leq \varepsilon.\]

  • The assumption \(\lambda_d(E)<\infty\) is essential here, since otherwise we cannot subtract \(\lambda_d(E)\).

  • In the general case put \(E_n=E \cap (-n, n)^d\) for \(n \in \mathbb N\). Then we have \(\lambda_d(E_n)<\infty\), so by the previous case there are open sets \(O_n \supseteq E_n\) with \(\lambda_d^{*}(O_n \setminus E_n) \leq \varepsilon 2^{-n}\).

  • Since \(E=\bigcup_{n \in \mathbb N}E_n\), the set \(O=\bigcup_{n \in \mathbb N}O_n\) is open, \(E \subseteq O\) and \(O \setminus E \subseteq \bigcup_{n \in \mathbb N}(O_n \setminus E_n)\), hence \[\lambda_d^{*}(O \setminus E) \leq \sum_{n \in \mathbb N}\lambda_d^{*}(O_n \setminus E_n) \leq \sum_{n \in \mathbb N}\varepsilon 2^{-n}=\varepsilon.\]

Step 3. We show that (ii) \(\Longrightarrow\) (iii) \(\Longrightarrow\) (i).

  • Assume (ii). For every \(j \in \mathbb N\) choose an open set \(O_j \supseteq E\) such that \(\lambda_d^{*}(O_j \setminus E) \leq \frac{1}{j}\) and put \[G=\bigcap_{j \in \mathbb N}O_j.\]

  • Then \(G\) is a \(G_{\delta}\)-set, \(E \subseteq G\) and \(G \setminus E \subseteq O_j \setminus E\) for every \(j \in \mathbb N\), so by monotonicity \[\lambda_d^{*}(G \setminus E) \leq \inf_{j \in \mathbb N}\frac{1}{j}=0,\] which is (iii).

  • Assume (iii) and let \(G \supseteq E\) be a \(G_{\delta}\)-set with \(\lambda_d^{*}(G \setminus E)=0\).

  • Then \(G \in {\rm Bor}(\mathbb R^d) \subseteq \mathcal L(\mathbb R^d)\), and \(G \setminus E \in \mathcal L(\mathbb R^d)\) because \(\lambda_d\) is a complete measure and \(\lambda_d^{*}(G \setminus E)=0\). Consequently \[E=G \setminus (G \setminus E) \in \mathcal L(\mathbb R^d),\] which is (i).

Step 4. We show that (i) \(\Longleftrightarrow\) (iv) and (iii) \(\Longleftrightarrow\) (v) by passing to complements.

  • If \(C \subseteq E\) then \(O=C^c\) satisfies \(O \supseteq E^c\) and \[O \setminus E^c=O \cap E=E \setminus C,\] and \(C\) is closed if and only if \(O\) is open.

  • Hence \(E\) satisfies (iv) if and only if \(E^c\) satisfies (ii). Since \(E \in \mathcal L(\mathbb R^d)\) if and only if \(E^c \in \mathcal L(\mathbb R^d)\), the equivalence (i) \(\Longleftrightarrow\) (iv) follows from (i) \(\Longleftrightarrow\) (ii) applied to \(E^c\).

  • Similarly, \(F \subseteq E\) is an \(F_{\sigma}\)-set if and only if \(F^c \supseteq E^c\) is a \(G_{\delta}\)-set, and \(F^c \setminus E^c=E \setminus F\), so \(E\) satisfies (v) if and only if \(E^c\) satisfies (iii).

Step 5. We prove the first two equalities. Let \(E \in \mathcal L(\mathbb R^d)\).

  • Let \(\alpha(E)=\inf\{\lambda_d(U): U \supseteq E \text{ and } U \text{ is open}\}\). By monotonicity \(\lambda_d(E) \leq \alpha(E)\), and the reverse inequality is precisely Step 1.

  • Let \(\beta(E)=\sup\{\lambda_d(C): C \subseteq E \text{ and } C \text{ is closed}\}\). By monotonicity we also have \(\beta(E)\leq \lambda_d(E)\).

  • If \(\lambda_d(E)<\infty\), then by (iv) for every \(\varepsilon>0\) there is a closed set \(C \subseteq E\) with \(\lambda_d(E \setminus C) \leq \varepsilon\), whence \[\beta(E)\ge \lambda_d(C)=\lambda_d(E)-\lambda_d(E \setminus C) \geq \lambda_d(E)-\varepsilon.\]

  • If \(\lambda_d(E)=\infty\), then by (iv) there is a closed set \(C \subseteq E\) with \(\lambda_d(E \setminus C) \leq 1\), and since \(\lambda_d(E) \leq \lambda_d(C)+\lambda_d(E \setminus C)\) we obtain \(\lambda_d(C)=\infty\), which also gives \(\beta(E)\ge\lambda_d(E)\).

  • In both cases we have \(\beta(E)=\lambda_d(E)\).

Step 6. We prove the third equality.

  • Set \[\begin{align*} \beta(E)=&\sup\{\lambda_d(C): C \subseteq E \text{ and } C \text{ is closed}\},\\ \gamma(E)=&\sup\{\lambda_d(K): K \subseteq E \text{ and } K \text{ is compact}\}. \end{align*}\]

  • Every compact subset of \(\mathbb R^d\) is closed, so \(\gamma(E) \leq \beta(E)\).

  • Fix a closed set \(C \subseteq E\) and put \(K_n=C \cap \overline{B(0, n)}\) for \(n \in \mathbb N\). Each \(K_n\) is closed and bounded, hence compact, and \(K_n \subseteq K_{n+1} \subseteq C\subseteq E\).

  • By continuity from below \(\lim_{n\to \infty}\lambda_d(K_n) = \lambda_d(C)\), so for every \(n \in \mathbb N\) we have \(\lambda_d(K_n)\le \gamma(E)\) and consequently \[\lambda_d(C) = \lim_{n\to \infty}\lambda_d(K_n) \leq \gamma(E).\]

  • Taking the supremum over all closed \(C \subseteq E\) we obtain \(\beta(E) \leq \gamma(E)\).

  • Hence \(\beta(E) = \gamma(E)\) and the proof is finished.

Approximation by finite unions of open rectangles

Theorem. If \(E \in \mathcal L(\mathbb R^d)\) and \(\lambda_d(E)<\infty\), then for every \(\varepsilon>0\) there is a set \(A\in \mathcal L(\mathbb R^d)\) which is a finite union of open rectangles such that \[\lambda_d(E \triangle A)<\varepsilon,\] where \(E \triangle A=(E \setminus A) \cup (A \setminus E)\) is the symmetric difference of \(E\) and \(A\).

  • In other words, every Lebesgue measurable set of finite measure is, up to a set of arbitrarily small measure, a finite union of open rectangles.

Proof: Let \(\varepsilon>0\). Since \(E \in \mathcal L(\mathbb R^d)\), by the previous theorem there is an open set \(U \supseteq E\) with \(\lambda_d(U \setminus E)<\frac{\varepsilon}{2}\). In particular \[\lambda_d(U) \leq \lambda_d(E)+\frac{\varepsilon}{2}<\infty.\]

  • Since \(U\) is open, \(U \in \mathcal L(\mathbb R^d)\), so by the previous theorem there is a compact set \(K \subseteq U\) with \(\lambda_d(U \setminus K)<\frac{\varepsilon}{2}\).

  • Every \(x \in K\) has an open rectangle \(R_x\) with \(x \in R_x \subseteq U\), and by compactness finitely many of them cover \(K\). Let \[A=R_{x_1} \cup \ldots \cup R_{x_m},\] so that \(K \subseteq A \subseteq U\) and, by monotonicity, \[\lambda_d(U \setminus A) \leq \lambda_d(U \setminus K)<\frac{\varepsilon}{2}.\]

  • Since \(E \subseteq U\) and \(A \subseteq U\) we have \(E \setminus A \subseteq U \setminus A\) and \(A \setminus E \subseteq U \setminus E\), hence \[\lambda_d(E \triangle A)=\lambda_d(E \setminus A)+\lambda_d(A \setminus E) \leq \lambda_d(U \setminus A)+\lambda_d(U \setminus E)<\varepsilon. \]

Translation invariance of the Lebesgue measure

Theorem.

  1. For every \(E \subseteq \mathbb R^d\) and \(x \in \mathbb R^d\) we have \[\lambda_d^{*}(x+E)=\lambda_d^{*}(E), \quad \text{ where } \quad x+E=\{x+y: y \in E\}.\]

  2. For every \(E \in \mathcal L(\mathbb R^d)\) and \(x \in \mathbb R^d\) we have \(x+E \in \mathcal L(\mathbb R^d)\) and \[\lambda_d(x+E)=\lambda_d(E).\]

  • The key observation is that \(x+I \in J_{co}^d\) and \[{\rm v}_d(x+I)={\rm v}_d(I)\] for every \(I \in J_{co}^d\), since a translation shifts all the vertices of a rectangle by the same vector.

Proof of (i).

  • For every \(I \in J_{co}^d\) and \(x \in \mathbb R^d\) we have \(x+I \in J_{co}^d\) and \({\rm v}_d(x+I)={\rm v}_d(I)\).

  • Take \((I_n)_{n \in \mathbb N} \subseteq J_{co}^d\) so that \(E \subseteq \bigcup_{n \in \mathbb N}I_n\), then for any \(x \in \mathbb R^d\): \[x+E \subseteq x+\bigcup_{n \in \mathbb N}I_n=\bigcup_{n \in \mathbb N}(x+I_n).\]

  • Thus \[\lambda_d^{*}(x+E) \leq \sum_{n \in \mathbb N}{\rm v}_d(x+I_n)=\sum_{n \in \mathbb N}{\rm v}_d(I_n),\] and taking the infimum over all such coverings we obtain \(\lambda_d^{*}(x+E) \leq \lambda_d^{*}(E)\) for any \(E \subseteq \mathbb R^d\) and \(x \in \mathbb R^d\).

  • Applying this result with \(-x\) in place of \(x\) and \(x+E\) in place of \(E\) we obtain \[\lambda_d^{*}(E)=\lambda_d^{*}(-x+(x+E)) \leq \lambda_d^{*}(x+E).\]

  • Consequently we obtain \(\lambda_d^{*}(E)=\lambda_d^{*}(x+E)\) as desired.

Proof of (ii).

  • If \(E \in \mathcal L(\mathbb R^d)\) and \(x \in \mathbb R^d\) we show that \(x+E \in \mathcal L(\mathbb R^d)\).

  • Let \(A \subseteq \mathbb R^d\) and observe that, by part (i), we have \[\begin{align*} &\lambda_d^{*}(A \cap (x+E))+\lambda_d^{*}(A \cap (x+E)^c)\\ &=\lambda_d^{*}\big((A \cap (x+E))-x\big)+\lambda_d^{*}\big((A \cap (x+E)^c)-x\big)\\ &=\lambda_d^{*}((A-x) \cap E)+\lambda_d^{*}((A-x) \cap E^c)\\ &=\lambda_d^{*}(A-x)\\ &=\lambda_d^{*}(A), \end{align*}\] where we used that \((x+E)^c=x+E^c\) and that \(E \in \mathcal L(\mathbb R^d)\).

  • Thus \(x+E \in \mathcal L(\mathbb R^d)\) and \[\lambda_d(x+E)=\lambda_d(E),\] which completes the proof.

Positive homogeneity of the Lebesgue measure

Theorem.

  1. For every \(E \subseteq \mathbb R^d\) and \(\alpha \in \mathbb R\) we have \[\lambda_d^{*}(\alpha E)=|\alpha|^{d}\lambda_d^{*}(E), \quad \text{ where } \quad \alpha E=\{\alpha y: y \in E\}.\]

  2. If \(E \in \mathcal L(\mathbb R^d)\) and \(\alpha \in \mathbb R\), then \(\alpha E \in \mathcal L(\mathbb R^d)\) and \[\lambda_d(\alpha E)=|\alpha|^{d}\lambda_d(E).\]

  • Recall from Lecture 4 that \(\lambda_d^{*}=\lambda_{d, o}^{*}\), so we may compute \(\lambda_d^{*}\) using coverings by open rectangles.

  • This is convenient here, since for \(\alpha \neq 0\) we have \(\alpha I \in J_{o}^d\) and \({\rm v}_d(\alpha I)=|\alpha|^{d}{\rm v}_d(I)\) for every \(I \in J_{o}^d\), whereas the family \(J_{co}^d\) is not preserved by \(\alpha<0\), because \(\alpha[a, b)=(\alpha b, \alpha a]\).

Proof of (i).

  • If \(\alpha=0\), then \(\alpha E \subseteq \{0\}\), thus \(\lambda_d^{*}(\alpha E)=0=|\alpha|^{d}\lambda_d^{*}(E)\), with the convention \(0 \cdot \infty=0\).

  • Let \(\alpha \neq 0\) and \(E \subseteq \mathbb R^d\). Let \[S=\{(I_n)_{n \in \mathbb N}: (I_n)_{n \in \mathbb N} \subseteq J_o^d\}.\]

  • Define a mapping \(M_{\alpha}:S \to S\) by \(M_{\alpha}(s)=(\alpha I_n)_{n \in \mathbb N}\) if \(s=(I_n)_{n \in \mathbb N}\).

  • \(M_{\alpha}\) is \(1-1\) and onto and its inverse is given by \(M_{1/\alpha}\).

  • Let \[S_E=\big\{(I_n)_{n \in \mathbb N} \in S: E \subseteq \bigcup_{n \in \mathbb N}I_n\big\}.\] Then \(M_{\alpha}[S_E]=S_{\alpha E}\), since \[E \subseteq \bigcup_{n \in \mathbb N}I_n \quad \iff \quad \alpha E \subseteq \bigcup_{n \in \mathbb N}\alpha I_n.\]

  • Define a set function \(\beta:S \to [0, \infty]\) by \(\beta(s)=\sum_{n \in \mathbb N}{\rm v}_d(I_n)\) for \(s=(I_n)_{n \in \mathbb N}\). Then \[\lambda_d^{*}(E)=\inf_{s \in S_E}\beta(s) \quad \text{ and } \quad \lambda_d^{*}(\alpha E)=\inf_{t \in S_{\alpha E}}\beta(t).\]

  • Moreover \[\beta(M_{\alpha}(s))=\sum_{n \in \mathbb N}{\rm v}_d(\alpha I_n) =|\alpha|^{d}\sum_{n \in \mathbb N}{\rm v}_d(I_n)=|\alpha|^{d}\beta(s).\]

  • Thus we obtain \(\lambda_d^{*}(\alpha E)=|\alpha|^{d}\lambda_d^{*}(E)\), since \(M_{\alpha}[S_E]=S_{\alpha E}\) and \[\lambda_d^{*}(\alpha E)=\inf_{t \in S_{\alpha E}}\beta(t)=\inf_{s \in S_E}\beta(M_{\alpha}(s)) =\inf_{s \in S_E}|\alpha|^{d}\beta(s)=|\alpha|^{d}\lambda_d^{*}(E)\] as desired.

Proof of (ii).

  • If \(\alpha=0\), then \(\alpha E \subseteq \{0\}\) is a null set, hence \(\alpha E \in \mathcal L(\mathbb R^d)\) by the completeness of \(\lambda_d\) and \(\lambda_d(\alpha E)=0=|\alpha|^{d}\lambda_d(E)\).

  • Let \(E \in \mathcal L(\mathbb R^d)\), \(\alpha \neq 0\) and \(A \subseteq \mathbb R^d\). We show that \(\alpha E \in \mathcal L(\mathbb R^d)\). Note that \[\lambda_d^{*}(\alpha^{-1}A)=\lambda_d^{*}(\alpha^{-1}A \cap E)+\lambda_d^{*}(\alpha^{-1}A \cap E^c).\]

  • Since \(\alpha^{-1}A \cap E=\alpha^{-1}(A \cap \alpha E)\) and \(\alpha^{-1}A \cap E^c=\alpha^{-1}(A \cap (\alpha E)^c)\), part (i) gives \[\frac{1}{|\alpha|^{d}}\lambda_d^{*}(A)=\frac{1}{|\alpha|^{d}}\lambda_d^{*}(A \cap \alpha E) +\frac{1}{|\alpha|^{d}}\lambda_d^{*}(A \cap (\alpha E)^c).\]

  • Hence \(\alpha E \in \mathcal L(\mathbb R^d)\), since \[\lambda_d^{*}(A)=\lambda_d^{*}(A \cap \alpha E)+\lambda_d^{*}(A \cap (\alpha E)^c).\]

  • By the previous part we also obtain \(\lambda_d(\alpha E)=|\alpha|^{d}\lambda_d(E)\).

Completion of Lebesgue measure space on \({\rm Bor}(\mathbb{R}^d)\)

The Lebesgue measure space \((\mathbb{R}^d,\mathcal{L}(\mathbb{R}^d),\lambda_d)\) is the completion of the Borel measure space \((\mathbb{R}^d,{\rm Bor}(\mathbb{R}^d),\lambda_d)\).

Proof. Let \(\overline{{\rm Bor}(\mathbb{R}^d)}\) be the completion of \({\rm Bor}(\mathbb{R}^d)\) with respect to \(\lambda_d\). i.e. \[\overline{{\rm Bor}(\mathbb{R}^d)}=\{A\cup B \subseteq \mathbb R^d: A\in {\rm Bor}(\mathbb{R}^d) \text{ and } B\subseteq C \in {\rm Bor}_0(\mathbb{R}^d)\},\] where \({\rm Bor}_0(\mathbb{R}^d)=\{C\in {\rm Bor}(\mathbb{R}^d): \lambda_d(C)=0 \}\). Since \((\mathbb{R}^d,\mathcal{L}(\mathbb{R}^d),\lambda_d)\) is complete and \({\rm Bor}(\mathbb{R}^d) \subseteq \mathcal{L}(\mathbb{R}^d)\) thus \[\overline{{\rm Bor}(\mathbb{R}^d)}\subseteq \mathcal{L}(\mathbb{R}^d).\]

Conversely, if \(E \in \mathcal{L}(\mathbb{R}^d)\) then \(E=F\cup N\), where \(F\) is an \(F_\sigma\) set and \(\lambda_d(N)=0\) thus \(E\in \overline{{\rm Bor}(\mathbb{R}^d)}\) and consequently \[\qquad \qquad \mathcal{L}(\mathbb{R}^d) \subseteq \overline{{\rm Bor}(\mathbb{R}^d)}. \qquad \]

Lebesgue–Stieltjes measures on \(\mathbb R\)

Lebesgue–Stieltjes measure is a Borel measure

Definition. Let \(F:\mathbb R\to \mathbb R\) be an increasing and right-continuous function. The Lebesgue–Stieltjes outer measure is defined for any \(E \subseteq \mathbb{R}\) by \[\begin{align*} \mu_{F}^{*}(E)=\inf\Big\{\sum_{n \in \mathbb{N}}(F(b_n)-F(a_n)): E \subseteq \bigcup_{n \in \mathbb{N}}(a_n, b_n]\Big\}. \end{align*}\]

  • The Lebesgue–Stieltjes measure \(\mu_F\) is the restriction of \(\mu_F^*\) to the Carathéodory \(\sigma\)-algebra \(\mathcal{L}_{\mu_F}=\mathcal{M}(\mu^{*}_F)\) of \(\mu^{*}_F\)-measurable sets.

  • \(\mathcal{L}_{\mu_F}=\mathcal{M}(\mu^{*}_F)\) will be called the Lebesgue–Stieltjes \(\sigma\)-algebra.

  • The members of \(\mathcal{L}_{\mu_F}\) are the Lebesgue–Stieltjes measurable sets.

  • By Carathéodory’s theorem \((\mathbb R, \mathcal{L}_{\mu_F}, \mu_F)\) is a complete measure space.

  • Moreover, \((\mathbb R, \mathcal{L}_{\mu_F}, \mu_F)\) is a \(\sigma\)-finite measure space and \({\rm Bor}(\mathbb{R})\subseteq\mathcal{L}_{\mu_F}\) and \(\mu_F((a, b])=F(b)-F(a)\) for any \(-\infty\le a\le b\le \infty\).

Regularity of the Lebesgue–Stieltjes measure

Problem 1. For \(E \subseteq \mathbb{R}\) prove that \(\mu_{F}^{*}(E)=\inf\big\{\sum_{n \in \mathbb{N}}\mu_F((a_n,b_n)): E \subseteq \bigcup_{n \in \mathbb{N}}(a_n, b_n)\big\}\).

Using this show that the following conditions are equivalent:

  1. \(E \in \mathcal{L}_{\mu_F}\);

  2. For every \(\varepsilon>0\) there exists an open set \(O \supseteq E\) so that \(\mu_F^{*}(O \setminus E) \leq \varepsilon\);

  3. There exists a \(G_{\delta}\)-set \(G \supseteq E\) with \(\mu_F^{*}(G \setminus E)=0\);

  4. For every \(\varepsilon>0\) there exists a closed set \(C \subseteq E\) with \(\mu_F^*(E \setminus C) \leq \varepsilon\);

  5. There exists an \(F_{\sigma}\) set \(F \subseteq E\) with \(\mu_F^*(E \setminus F)=0\).

Moreover, if \(E \in \mathcal{L}_{\mu_F}\), then one has \[\begin{align*} \mu_F(E)&=\inf\{\mu_F(U): U\supseteq E \text{ and } U \text{ is open}\}\\ &=\sup\{\mu_F(F): F\subseteq E \text{ and } F \text{ is closed}\}\\ &=\sup\{\mu_F(K): K\subseteq E \text{ and } K \text{ is compact}\}. \end{align*}\]

Outer and inner regularity of outer measures

Outer measures induced by set functions

Outer measures induced by general set functions

Outer measures induced by set functions. Let \(X \neq\varnothing\) be a set and let \(\mathcal E \subseteq \mathcal P(X)\) be a collection containing \(\varnothing, X\). Let \(\rho:\mathcal E \to [0, \infty]\) be a set function such that \(\rho(\varnothing)=0\). For any \(A \subseteq X\)

\[\mu^{*}(A)=\inf\bigg\{\sum_{j \in \mathbb N}\rho(E_j): (E_j)_{j \in \mathbb N} \subseteq \mathcal E \text{ and } A \subseteq \bigcup_{j \in \mathbb N}E_j\bigg\}\] defines an outer measure, which we call an outer measure induced by \(\rho\).

  • By Carathéodory’s theorem the collection of \(\mu^{*}\)-measurable sets

    \[\mathcal M(\mu^{*})=\big\{A \subseteq X: \mu^{*}(E)=\mu^{*}(E \cap A)+\mu^{*}(E \cap A^c) \ \text{ for all } \ E \subseteq X\big\}\] is a \(\sigma\)-algebra, which will be called the Carathéodory \(\sigma\)-algebra.

  • Moreover, \((X, \mathcal M(\mu^{*}), \mu^{*})\) is a complete measure space, and the outer measure \(\mu^{*}\) restricted to \(\mathcal M(\mu^{*})\) will be called the Carathéodory measure.

The sets \(F_{\sigma}, G_{\delta}, F_{\sigma\delta}, G_{\delta\sigma}, \ldots\)

Definition. Let \(X\) be a set and let \(\mathcal E \subseteq \mathcal P(X)\). We define

  • \(\mathcal E_{\sigma}=\{\bigcup_{n \in \mathbb N}E_n: (E_n)_{n \in \mathbb N} \subseteq \mathcal E\}\) - the collection of countable unions of sets from \(\mathcal E\).

  • \(\mathcal E_{\delta}=\{\bigcap_{n \in \mathbb N}E_n: (E_n)_{n \in \mathbb N} \subseteq \mathcal E\}\) - the collection of countable intersections of sets from \(\mathcal E\).

  • \(\mathcal E_{\sigma\delta}=(\mathcal E_{\sigma})_{\delta}\) - the collection of countable intersections of sets from \(\mathcal E_{\sigma}\).

  • \(\mathcal E_{\delta\sigma}=(\mathcal E_{\delta})_{\sigma}\) - the collection of countable unions of sets from \(\mathcal E_{\delta}\).

  • \(\mathcal E^c=\{E^c: E \in \mathcal E\}\) - the collection of complements of sets from \(\mathcal E\).

Note that \((\mathcal E_{\sigma})^c=(\mathcal E^c)_{\delta}\) and \((\mathcal E_{\delta})^c=(\mathcal E^c)_{\sigma}\).

Outer measures induced by general set functions

Problem 2. Let \(X\), \(\mathcal E\), \(\rho\) and \(\mu^{*}\) be as above. Prove that \(\mu^{*}\) is an outer measure on \(X\). Where do we use the assumption that \(\varnothing, X \in \mathcal E\)?

Problem 3. Let \(\mathcal E \subseteq \mathcal P(X)\). Prove that \[(\mathcal E_{\sigma})^c=(\mathcal E^c)_{\delta}, \quad (\mathcal E_{\delta})^c=(\mathcal E^c)_{\sigma} \quad \text{ and } \quad (\mathcal E_{\sigma\delta})^c=(\mathcal E^c)_{\delta\sigma}.\]

  • The Lebesgue outer measure \(\lambda_d^{*}\) is the outer measure induced by the volume function \({\rm v}_d\) on \(\mathcal E=J_{o}^d\); in this case

    • \(\mathcal E_{\sigma\delta}\) plays the role of the \(G_{\delta}\)-sets;

    • \((\mathcal E^c)_{\delta\sigma}\) the role of the \(F_{\sigma}\)-sets.

Standing assumptions for Problems 3–7

Assumptions. Let \(X \neq\varnothing\) be a set and let \(\mathcal E \subseteq \mathcal P(X)\) be a collection containing \(\varnothing, X\). Let \(\rho:\mathcal E \to [0, \infty]\) be a set function such that \(\rho(\varnothing)=0\), and for \(A \subseteq X\) let

\[\mu^{*}(A)=\inf\bigg\{\sum_{j \in \mathbb N}\rho(E_j): (E_j)_{j \in \mathbb N} \subseteq \mathcal E \text{ and } A \subseteq \bigcup_{j \in \mathbb N}E_j\bigg\}.\] Let \(\mathcal M(\mu^{*})\) be the Carathéodory \(\sigma\)-algebra. In the problems below we assume, as indicated in each of them, that

  • (a) \(\mu^{*}=\rho\) on \(\mathcal E\);

  • (b) \(\mathcal E \subseteq \mathcal M(\mu^{*})\);

  • (c) \(\mu^{*}\) is a \(\sigma\)-finite measure on \((X, \mathcal M(\mu^{*}))\).

Outer regularity of outer measures

Problem 4. Suppose that (a) holds. Prove that

  • (i) for any \(A \subseteq X\) and \(\varepsilon>0\) there exists a set \(U \supseteq A\) such that

    \[U \in \mathcal E_{\sigma} \quad \text{ and } \quad \mu^{*}(A) \leq \mu^{*}(U) \leq \mu^{*}(A)+\varepsilon;\]

  • (ii) for any \(A \subseteq X\) there exists a set \(B \supseteq A\) such that

    \[B \in \mathcal E_{\sigma\delta} \quad \text{ and } \quad \mu^{*}(A)=\mu^{*}(B).\]

Problem 5. Suppose that (a) holds. Prove that \(\mu^{*}\) is outer regular with respect to the family \(\mathcal E_{\sigma}\), that is, for every \(E \subseteq X\) one has

\[\mu^{*}(E)=\inf\{\mu^{*}(U): U \supseteq E \text{ and } U \in \mathcal E_{\sigma}\}.\]

Regularity of the Carathéodory measures

Problem 6. Suppose that (a), (b) and (c) hold. Prove that for \(E \subseteq X\) the following conditions are equivalent:

  • (i) \(E \in \mathcal M(\mu^{*})\);

  • (ii) for every \(\varepsilon>0\) there exists a set \(U \supseteq E\) such that

    \[U \in \mathcal E_{\sigma} \quad \text{ and } \quad \mu^{*}(U \setminus E) \leq \varepsilon;\]

  • (iii) there exists a set \(G \supseteq E\) such that

    \[G \in \mathcal E_{\sigma\delta} \quad \text{ and } \quad \mu^{*}(G \setminus E)=0;\]

  • (iv) for every \(\varepsilon>0\) there exists a set \(C \subseteq E\) such that

    \[C \in (\mathcal E^c)_{\delta} \quad \text{ and } \quad \mu^{*}(E \setminus C) \leq \varepsilon;\]

  • (v) there exists a set \(F \subseteq E\) such that

    \[F \in (\mathcal E^c)_{\delta\sigma} \quad \text{ and } \quad \mu^{*}(E \setminus F)=0.\]

Outer and inner regularity of the Carathéodory measures

Problem 7. Suppose that assumptions (a), (b) and (c) hold. Prove that

  • (i) \(\mu^{*}\) is outer regular with respect to the family \(\mathcal E_{\sigma}\), that is,

    \[\mu^{*}(E)=\inf\{\mu^{*}(U): U \supseteq E \text{ and } U \in \mathcal E_{\sigma}\} \quad \text{ for any } \quad E \in \mathcal M(\mu^{*});\]

  • (ii) \(\mu^{*}\) is inner regular with respect to the family \((\mathcal E^c)_{\delta}\), that is,

    \[\mu^{*}(E)=\sup\{\mu^{*}(C): C \subseteq E \text{ and } C \in (\mathcal E^c)_{\delta}\} \quad \text{ for any } \quad E \in \mathcal M(\mu^{*}).\]

  • Compare with the regularity theorem for \(\lambda_d\) proved earlier in this lecture.

Approximations

Problem 8. Suppose that assumptions (a) and (b) hold and that \((X, \mathcal M(\mu^{*}), \mu^{*})\) is a finite measure space. Prove that for every \(E \in \mathcal M(\mu^{*})\) and every \(\varepsilon>0\) there exists a set \(A \in \mathcal E_{\sigma}\) such that \[\mu^{*}(E \triangle A)<\varepsilon.\] In fact one can take \(A\) to be a finite union of elements of \(\mathcal E\), which is the important part of the statement.

  • For \(X=\mathbb R^d\), \(\mathcal E=J_{o}^d\) and \(\rho={\rm v}_d\) this is the theorem on approximation of sets of finite measure by finite unions of rectangles.

  • We now deduce an analogue for the Lebesgue–Stieltjes measures:

If \(E\in \mathcal L_{\mu_F}\) and \(\mu_F(E)<\infty\), then for every \(\varepsilon>0\) there is a set \(A\) that is a finite union of open intervals such that \(\mu_F(E\triangle A)<\varepsilon.\)

Regularity conditions

Outer regularity: equivalent forms

Problem 9. Let \((X, \mathcal M, \mu)\) be a measure space and let \(\mathcal E \subseteq \mathcal M\) be a collection containing \(\varnothing, X\). Consider the following two conditions:

  • (a) for every \(E \in \mathcal M\) and every \(\varepsilon>0\) there exists a set \(G \in \mathcal E\) such that

    \[G \supseteq E \quad \text{ and } \quad \mu(G \setminus E) \leq \varepsilon;\]

  • (b) \(\mu\) is outer regular with respect to the family \(\mathcal E\), i.e.

    \[\mu(E)=\inf\{\mu(U): U \supseteq E \text{ and } U \in \mathcal E\} \ \text{ for any } \ E \in \mathcal M.\]

Prove that

  • (i) (a) implies (b);

  • (ii) if \(\mu(X)<\infty\), then (b) implies (a);

  • (iii) if \(\mu\) is \(\sigma\)-finite and \(\mathcal E\) is closed under countable unions, then (b) implies (a).

Inner regularity: equivalent forms

Problem 10. Let \((X, \mathcal M, \mu)\) be a measure space and let \(\mathcal E \subseteq \mathcal M\) be a collection containing \(\varnothing, X\). Consider the following two conditions:

  • (a) for every \(E \in \mathcal M\) and every \(\varepsilon>0\) there exists a set \(F \in \mathcal E\) such that

    \[F \subseteq E \quad \text{ and } \quad \mu(E \setminus F) \leq \varepsilon;\]

  • (b) \(\mu\) is inner regular with respect to the family \(\mathcal E\), i.e.

    \[\mu(E)=\sup\{\mu(C): C \subseteq E \text{ and } C \in \mathcal E\} \ \text{ for any } \ E \in \mathcal M.\]

Prove that

  • (i) (a) implies (b);

  • (ii) if \(\mu(X)<\infty\), then (b) implies (a);

  • (iii) if \(\mu\) is \(\sigma\)-finite and \(\mathcal E\) is closed under countable unions, then (b) implies (a).

Regularity and approximation by null sets

Problem 11. Let \((X, \mathcal M, \mu)\) be a \(\sigma\)-finite measure space and let \(\mathcal E \subseteq \mathcal M\) be a collection containing \(\varnothing, X\). Prove that

  • (i) if \(\mu\) is outer regular with respect to \(\mathcal E\) and \(\mathcal E\) is closed under countable unions, then for every \(E \in \mathcal M\) there exists a set \(G \in \mathcal E_{\delta}\) such that

    \[G \supseteq E \quad \text{ and } \quad \mu(G \setminus E)=0;\]

  • (ii) if \(\mu\) is inner regular with respect to \(\mathcal E\), then for every \(E \in \mathcal M\) there exists a set \(F \in \mathcal E_{\sigma}\) such that

    \[F \subseteq E \quad \text{ and } \quad \mu(E \setminus F)=0.\]

  • Note the asymmetry: in (ii) no closure assumption on \(\mathcal E\) is needed.

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