Assume to the contrary that there does exist an f, that's continuous everywhere, and f = \chi_{[0,1]} a.e... (From here on out, let's just call it \chi.)
We have, \forall \epsilon > 0,\hspace{0.25cm} \exists \delta > 0 s.t. |x - y| < \delta \hspace{0.25cm} \Rightarrow |f(x) - f(y)| < \epsilon.
Choose x = 1 and \epsilon = \frac{1}{4}.
We know \exists \delta > 0 such that |f(y) - f(1)| < \frac{1}{4} \forall y \in (1,1+\delta) \hspace{0.25cm} (\dagger).
Since f is continuous everywhere, we have \lim_{x \to 1}f(x) = 1 = f(1). It follows from \dagger that:
-\frac{1}{4} < f(y) - 1 < \frac{1}{4}
...thus
f(y) \in (\frac{3}{4},\frac{5}{4})
...on (1, 1+\delta). This is a contradiction, since m\big((1, 1+\delta)\big) = \delta > 0, and \chi\big((1, 1+\delta)\big) = \lbrace 0 \rbrace.
In preparation for a qualifying exam in Real Analysis, during the summer of 2013, I plan to solve as many problems from Stein & Shakarchi's Real Analysis text as I can. Please feel free to comment or correct me as I make my way through this.
Friday, May 31, 2013
1.21
Let f: \mathcal{C} \to [0,1] be the Cantor-Lebesgue function. It's continuous, and surjective. Certainly, for any interval in \mathbb{R}, \exists \mathcal{N}, non-measurable. (Simply scale the non-measurable set constructed on p.24.)
Since f is continuous, and \mathcal{N} \subset [0,1], the pre-image, f^{-1}(\mathcal{N}) \subset \mathcal{C}.
Notice: 0 \leq m^*(f^{-1}(\mathcal{N})) \leq m^*(\mathcal{C}) = 0 ...and thus, m^*(f^{-1}(\mathcal{N})) = 0 ...and since all sets of outer-measure zero are measurable (by Property 2, in Section 1.3) f^{-1}(\mathcal{N}) is a measurable set. Thus, the continuous map f maps a measurable set to a non-measurable set.
Since f is continuous, and \mathcal{N} \subset [0,1], the pre-image, f^{-1}(\mathcal{N}) \subset \mathcal{C}.
Notice: 0 \leq m^*(f^{-1}(\mathcal{N})) \leq m^*(\mathcal{C}) = 0 ...and thus, m^*(f^{-1}(\mathcal{N})) = 0 ...and since all sets of outer-measure zero are measurable (by Property 2, in Section 1.3) f^{-1}(\mathcal{N}) is a measurable set. Thus, the continuous map f maps a measurable set to a non-measurable set.
1.18
The exercise didn't specify anything about f = \infty on sets with positive measure. I'll assume f is a.e. finite. From here, it, of course, suffices to consider only non-negative measurable functions. For any such f, we need to find a sequence of continuous functions \lbrace f_n \rbrace_{n = 1}^{\infty} such that the set:
E = \Big\lbrace x \in \mathbb{R}^d \hspace{0.25cm} \bigg| \hspace{0.25cm} \lim_{n \to \infty} |f(x) - f_n(x)| > 0 \Big\rbrace
has measure zero.
First, define the d-dimensional cubes:
Q_n = [-n,n]\times \ldots \times[-n,n]
And the functions:
g_n(x) = \min{\lbrace n,f(x) \rbrace}\chi_{Q_n}
It follows from Lusin's Theorem that for any of our g_n's, we can find a set F_n such that g_n \chi_{F_n} is continuous, and m(Q_n \backslash F_n)\leq \frac{1}{2^{n}}. Now, we can simply define f_n = g_n \chi_{F_n}.
Lastly, define: E_n = Q_n \backslash F_n. Notice that: \sum_{n = 1}^{\infty} m(E_n) \leq \sum_{n=1}^{\infty} \frac{1}{2^n} \leq 1 Now, of course, we simply need to show that E is \sup{\lbrace E_n \rbrace}. This actually isn't all that hard. First, notice: \bigcup_{n \geq k} E_n = \Big\lbrace x \in \mathbb{R}^d \hspace{0.25cm} \bigg| \hspace{0.25cm} |f(x) - f_n(x)| > 0, \hspace{0.25cm} n \geq k \Big\rbrace Naturally, we arrive that the result that E = \bigcap_{k=1}^{\infty} \bigcup_{n \geq k} E_n, and thus, by the Borel-Cantelli Lemma, m(E) = 0, as desired.
Lastly, define: E_n = Q_n \backslash F_n. Notice that: \sum_{n = 1}^{\infty} m(E_n) \leq \sum_{n=1}^{\infty} \frac{1}{2^n} \leq 1 Now, of course, we simply need to show that E is \sup{\lbrace E_n \rbrace}. This actually isn't all that hard. First, notice: \bigcup_{n \geq k} E_n = \Big\lbrace x \in \mathbb{R}^d \hspace{0.25cm} \bigg| \hspace{0.25cm} |f(x) - f_n(x)| > 0, \hspace{0.25cm} n \geq k \Big\rbrace Naturally, we arrive that the result that E = \bigcap_{k=1}^{\infty} \bigcup_{n \geq k} E_n, and thus, by the Borel-Cantelli Lemma, m(E) = 0, as desired.
Thursday, May 30, 2013
1.17
The goal of this exercise is to show that if we choose c_n's as the hint prescribes, the set:
E = \Big\lbrace x \in [0,1] \hspace{0.25cm} \bigg| \hspace{0.25cm} \lim_{n \to \infty} \Big| \frac{f_n(x)}{c_n} \Big| > 0 \Big\rbrace
has measure zero. Define:
S_c = \Big\lbrace x \in [0,1] \hspace{0.25cm} \bigg| \hspace{0.25cm} |f_n(x)| > \frac{c}{n} \Big\rbrace
Notice that m(S_1) \leq 1. Also, notice S_{c+1} \subset S_{c} \hspace{0.25cm} \forall c, and \bigcap_{c=1}^{\infty}S_c = \emptyset. Thus, by Corollary 3.3, \lim_{n \to \infty} m(S_n) = 0.
With that out of the way, notice that for the sets: E_n = \Big\lbrace x \in [0,1] \hspace{0.25cm} \bigg| \hspace{0.25cm} \Big| \frac{f_n(x)}{c_n} \Big| > \frac{1}{n} \Big\rbrace ...we can choose c_n large enough such that for every n, m(E_n) \leq \frac{1}{2^n}. Certainly, it follows that (\dagger): \sum_{n=1}^{\infty} m(E_n) \leq \sum_{n=1}^{\infty} \frac{1}{2^n} = 1 < \infty Now, observe that E = \sup{ \lbrace E_n \rbrace }, i.e. (recalling problem 1.16), E = \bigcap_{k=1}^{\infty} \bigcup_{n \geq k}E_n. Thus, applying the Borel-Cantelli Lemma, we have that (\dagger) \Rightarrow m(E) = 0
With that out of the way, notice that for the sets: E_n = \Big\lbrace x \in [0,1] \hspace{0.25cm} \bigg| \hspace{0.25cm} \Big| \frac{f_n(x)}{c_n} \Big| > \frac{1}{n} \Big\rbrace ...we can choose c_n large enough such that for every n, m(E_n) \leq \frac{1}{2^n}. Certainly, it follows that (\dagger): \sum_{n=1}^{\infty} m(E_n) \leq \sum_{n=1}^{\infty} \frac{1}{2^n} = 1 < \infty Now, observe that E = \sup{ \lbrace E_n \rbrace }, i.e. (recalling problem 1.16), E = \bigcap_{k=1}^{\infty} \bigcup_{n \geq k}E_n. Thus, applying the Borel-Cantelli Lemma, we have that (\dagger) \Rightarrow m(E) = 0
Wednesday, May 29, 2013
1.16
This exercise is asking us to prove the Borel-Cantelli Lemma. In the measure theory settings, it states:
Since each E_k \in \mathcal{M}, certainly A_n = (\bigcup_{k \geq n} E_k) \in \mathcal{M} \hspace{0.25cm} \forall n. It follows that since E = \bigcap_{n=1}^{\infty} A_n, that E \in \mathcal{M}.
Part b.) Assume to the contrary that m(E) = \delta > 0. Notice that if we define: S_N = \bigcap_{k=1}^N \bigcup_{n \geq k} E_n = \bigcup_{n \geq N} E_n Then, certainly, S_N \searrow E, and \forall N, \delta \leq m(S_N) = m(\bigcup_{n \geq N} E_n) \leq \sum_{n=N}^{\infty} m(E_n) Which certainly contradicts \dagger, completing the proof.
Suppose \lbrace E_n \rbrace_{n=1}^{\infty} is a countable family of subsets of \mathbb{R}^d, and (\dagger) \sum_{k=1}^{\infty} m(E_k) < \infty The set E = \bigcap_{n=1}^{\infty} \bigcup_{k \geq n} E_k has measure zero.Part a.) We first need to show E is a measurable set. Recall that the measurable sets form a \sigma-algebra, \mathcal{M}, which is closed under countable unions and intersections.
Since each E_k \in \mathcal{M}, certainly A_n = (\bigcup_{k \geq n} E_k) \in \mathcal{M} \hspace{0.25cm} \forall n. It follows that since E = \bigcap_{n=1}^{\infty} A_n, that E \in \mathcal{M}.
Part b.) Assume to the contrary that m(E) = \delta > 0. Notice that if we define: S_N = \bigcap_{k=1}^N \bigcup_{n \geq k} E_n = \bigcup_{n \geq N} E_n Then, certainly, S_N \searrow E, and \forall N, \delta \leq m(S_N) = m(\bigcup_{n \geq N} E_n) \leq \sum_{n=N}^{\infty} m(E_n) Which certainly contradicts \dagger, completing the proof.
1.14
Part a.) First notice that for any set E \subset \mathbb{R}, any finite closed covering, E \subset \bigcup_{k=1}^{N}I_k, must be a closed set. For any E \subset \mathbb{R}, choose an arbitrary convergent sequence, \lbrace x_n \rbrace \subset E. By definition, x_n \to x \in \overline{E}. Notice also, that \lbrace x_n \rbrace \subset E \Rightarrow \lbrace x_n \rbrace \subset \bigcup_{k=1}^{N}I_k. Since \bigcup_{k=1}^{N}I_k is closed, x_n \to x \in \bigcup_{k=1}^{N}I_k.
Thus, any finite closed covering of an arbitrary set E must also contain \overline{E}. Therefore, J_*{(E)} = J_*{(\overline{E})}.
Part b.) Consider \mathbb{Q} \cap [0,1]. Certainly, m(\mathbb{Q} \cap [0,1]) = 0. However, \overline{\mathbb{Q} \cap [0,1]} = [0,1]. The result from part (a) gives J_*{(\mathbb{Q} \cap [0,1])} = J_*{([0,1])} = 1.
Thus, any finite closed covering of an arbitrary set E must also contain \overline{E}. Therefore, J_*{(E)} = J_*{(\overline{E})}.
Part b.) Consider \mathbb{Q} \cap [0,1]. Certainly, m(\mathbb{Q} \cap [0,1]) = 0. However, \overline{\mathbb{Q} \cap [0,1]} = [0,1]. The result from part (a) gives J_*{(\mathbb{Q} \cap [0,1])} = J_*{([0,1])} = 1.
1.13
Part a.) Let F \subset \mathbb{R}^{d} be an arbitrary closed set. First, define: O_n = \lbrace x \in \mathbb{R} \hspace{0.25cm} | \hspace{0.25cm} \mathbb{d}{(x,F)} < \frac{1}{n} \rbrace
Notice \overline{F} = \bigcap_{n = 1}^{\infty} O_n. Since F is closed, F = \overline{F}. Thus F \in F_\sigma.
Part b.) There's a well-known corollary to Baire's Category Theorem that states:
First notice that we can write \mathbb{Q} = \bigcup_{n=1}^{\infty} \lbrace q_n \rbrace, where \lbrace q_n \rbrace_{n \in \mathbb{N}} is an enumeration of the rationals. Since each \lbrace q_n \rbrace is closed, it's easy to see that \mathbb{Q} \in F_\sigma.
Next, observe that \mathbb{Q} \in F_\sigma \Rightarrow \mathbb{Q}^c \in G_\delta. Now it is clear from \dagger that \mathbb{Q} can not be G_\delta, since \mathbb{Q} \cap \mathbb{Q}^c = \emptyset, which is nowhere-dense. Thus, \mathbb{Q} is F_\sigma but not G_\delta, as desired.
Part c.) S = (\mathbb{Q} \cap (-\infty, 0]) \cup (\mathbb{Q}^c \cap (0, \infty))
Part b.) There's a well-known corollary to Baire's Category Theorem that states:
\dagger In a complete metric space, the intersection of any countable collection of dense G_\delta's is again a dense G_\delta.
First notice that we can write \mathbb{Q} = \bigcup_{n=1}^{\infty} \lbrace q_n \rbrace, where \lbrace q_n \rbrace_{n \in \mathbb{N}} is an enumeration of the rationals. Since each \lbrace q_n \rbrace is closed, it's easy to see that \mathbb{Q} \in F_\sigma.
Next, observe that \mathbb{Q} \in F_\sigma \Rightarrow \mathbb{Q}^c \in G_\delta. Now it is clear from \dagger that \mathbb{Q} can not be G_\delta, since \mathbb{Q} \cap \mathbb{Q}^c = \emptyset, which is nowhere-dense. Thus, \mathbb{Q} is F_\sigma but not G_\delta, as desired.
Part c.) S = (\mathbb{Q} \cap (-\infty, 0]) \cup (\mathbb{Q}^c \cap (0, \infty))
1.11
Notice that we can construct \mathcal{A} in a similar fashion to how we construct \mathcal{C}. Proceed as follows. Define:
\mathcal{A}_1 = [0, 0.4) \cup [0.5, 1].
\mathcal{A}_2 = \bigcup_{k=0}^{10^1 - 1} 10^{-1}([0 + k, 0.4 + k) \cup [0.5 + k, 1 + k])
\vdots
\mathcal{A}_n = \bigcup_{k=0}^{10^{n-1}-1} 10^{-n + 1}([0 + k, 0.4 + k) \cup [0.5 + k, 1+k]).
Now, just define \mathcal{A} = \bigcap_{n=1}^{\infty} \mathcal{A_n}. By corollary 3.3, since \bigcap_{n=1}^{N} \mathcal{A_n} \searrow \mathcal{A} as N \to \infty, and m(\mathcal{A_1}) = 0.9, then: m(A) = \lim_{N \to \infty} m(\bigcap_{n=1}^{N} \mathcal{A_n}) = \lim_{N \to \infty} (0.9)^N = 0
Now, just define \mathcal{A} = \bigcap_{n=1}^{\infty} \mathcal{A_n}. By corollary 3.3, since \bigcap_{n=1}^{N} \mathcal{A_n} \searrow \mathcal{A} as N \to \infty, and m(\mathcal{A_1}) = 0.9, then: m(A) = \lim_{N \to \infty} m(\bigcap_{n=1}^{N} \mathcal{A_n}) = \lim_{N \to \infty} (0.9)^N = 0
1.10
Part a.) Choose an arbitrary x \in [0,1]. Clearly, the sequence \lbrace f_n(x) \rbrace is monotonic-decreasing, and bounded below by 0. Thus, \lim_{n \to \infty} f_n(x) exists \forall x \in [0,1]. Simply define f to be the point-wise limit of f_n.
Part b.) Recall from the construction of \hat{\mathcal{C}} that: [0,1] \cap \hat{\mathcal{C}}^c = \bigcup_{k=1}^{\infty} \bigcup_{n = 1}^{3^{k-1}-1} O_n^k Where the length of the open intervals O_n^k depend on how we construct our specific \hat{\mathcal{C}}. Let's choose x \in \hat{\mathcal{C}} arbitrarily. Define: S = \lbrace x \in [0,1] | x = \frac{b_{n,k} - a_{n,k}}{2}, O_n^k = (a_{n,k}, b_{n,k}) \rbrace Notice, much like what we observed in (1.9), \forall r > 0, B_r(x) \cap S \neq \emptyset. Construct a sequence from S in this fashion. (I.e. \forall n choose any x_n \in B_{\frac{1}{n}}(x) \cap S.)
Certainly, we observe x_n \to x as n \to \infty. However, by construction of f, notice f(x_n) = 0 for every n. Thus, \lim_{n \to \infty} f(x_n) = 0 \neq f(x) = 1. Therefore f must be discontinuous \forall x \in \hat{\mathcal{C}}.
Finally, the author wants you to observe that since f_n is both Riemann integrable \forall n, and decreasing, that the sequence \lbrace \int f_n \rbrace is both decreasing and bounded below (by, say, 0). Therefore \lim_{n \to \infty} \int f_n exists. However, we have \int \lim_{n \to \infty} f_n = \int f, but f clearly isn't Reimann integrable, since it's discontinuous on \hat{\mathcal{C}}, a set with positive measure. Thus, the point-wise limit of a sequence of Riemann-integrable functions isn't necessarily Riemann integrable in general.
Part b.) Recall from the construction of \hat{\mathcal{C}} that: [0,1] \cap \hat{\mathcal{C}}^c = \bigcup_{k=1}^{\infty} \bigcup_{n = 1}^{3^{k-1}-1} O_n^k Where the length of the open intervals O_n^k depend on how we construct our specific \hat{\mathcal{C}}. Let's choose x \in \hat{\mathcal{C}} arbitrarily. Define: S = \lbrace x \in [0,1] | x = \frac{b_{n,k} - a_{n,k}}{2}, O_n^k = (a_{n,k}, b_{n,k}) \rbrace Notice, much like what we observed in (1.9), \forall r > 0, B_r(x) \cap S \neq \emptyset. Construct a sequence from S in this fashion. (I.e. \forall n choose any x_n \in B_{\frac{1}{n}}(x) \cap S.)
Certainly, we observe x_n \to x as n \to \infty. However, by construction of f, notice f(x_n) = 0 for every n. Thus, \lim_{n \to \infty} f(x_n) = 0 \neq f(x) = 1. Therefore f must be discontinuous \forall x \in \hat{\mathcal{C}}.
Finally, the author wants you to observe that since f_n is both Riemann integrable \forall n, and decreasing, that the sequence \lbrace \int f_n \rbrace is both decreasing and bounded below (by, say, 0). Therefore \lim_{n \to \infty} \int f_n exists. However, we have \int \lim_{n \to \infty} f_n = \int f, but f clearly isn't Reimann integrable, since it's discontinuous on \hat{\mathcal{C}}, a set with positive measure. Thus, the point-wise limit of a sequence of Riemann-integrable functions isn't necessarily Riemann integrable in general.
Tuesday, May 28, 2013
1.9
Consider a Cantor-like set \hat{\mathcal{C}} such that m(\hat{\mathcal{C}}) > 0. Similar to how the hint prescribes, let O be the union of all of the open intervals removed during the odd stages of the construction of \hat{\mathcal{C}}. Next, let O' be the union of all of the open intervals removed during the even stages of the construction of \hat{\mathcal{C}}.
Notice (\dagger): [0,1] \backslash \hat{\mathcal{C}} = O \cup O' Now, given the construction of \hat{\mathcal{C}}, \forall x \in \hat{\mathcal{C}}, it's easy to see that \forall r > 0, B_r{(x)} \cap O \neq \emptyset.
Thus, since every element of \hat{\mathcal{C}} is a limit point of O, (given \dagger), \hat{\mathcal{C}} = \overline{O} \backslash O. Thus, m(\overline{O} \backslash O) > 0, as desired.
Notice (\dagger): [0,1] \backslash \hat{\mathcal{C}} = O \cup O' Now, given the construction of \hat{\mathcal{C}}, \forall x \in \hat{\mathcal{C}}, it's easy to see that \forall r > 0, B_r{(x)} \cap O \neq \emptyset.
Thus, since every element of \hat{\mathcal{C}} is a limit point of O, (given \dagger), \hat{\mathcal{C}} = \overline{O} \backslash O. Thus, m(\overline{O} \backslash O) > 0, as desired.
1.6
\dagger Note that it was simpler for me to first consider problem 1.7.
Since the Lebesgue measure is translation-invariant, it suffices to only consider balls centered at the origin. Theorem 1.4 gives that B_1{(0)} = \bigcup_{k=1}^{\infty} Q_k, where \left\lbrace Q_n \right\rbrace_{n \in \mathbb{N}} is a countable collection of pairwise almost-disjoint cubes. Thus, v_d = m(B_1{(0)}) = \sum_{k=1}^{\infty} m(Q_k) By \dagger, any dilation of the unit ball in \mathbb{R}^d is equivalent to letting \delta = (r, r, \ldots, r). It follows from the main argument in 1.7 that:
m(B_r{(0)}) = m(\delta B_1{(0)}) = r^d m(B_1{(0)}) = r^d v_d, as desired.
Since the Lebesgue measure is translation-invariant, it suffices to only consider balls centered at the origin. Theorem 1.4 gives that B_1{(0)} = \bigcup_{k=1}^{\infty} Q_k, where \left\lbrace Q_n \right\rbrace_{n \in \mathbb{N}} is a countable collection of pairwise almost-disjoint cubes. Thus, v_d = m(B_1{(0)}) = \sum_{k=1}^{\infty} m(Q_k) By \dagger, any dilation of the unit ball in \mathbb{R}^d is equivalent to letting \delta = (r, r, \ldots, r). It follows from the main argument in 1.7 that:
m(B_r{(0)}) = m(\delta B_1{(0)}) = r^d m(B_1{(0)}) = r^d v_d, as desired.
1.7
It suffices to show that \forall \epsilon > 0, \exists \mathcal{O}, open, such that m^*(\mathcal{O}-\delta E) < \epsilon. Before we move ahead, first define:
\Delta = (\delta_1 \cdot \ldots \cdot \delta_d)
Recall that if Q_k is a closed cube,
Q_k = [a_1, b_1]\times[a_2,b_2]\times \ldots \times[a_d,b_d]
...where a_k < b_k \in \mathbb{R}, and:
m(Q_k) = \prod_{k = 1}^{d}(b_k - a_k)
\dagger Observe that for any closed cube Q, \delta Q = [\delta_1 a_1, \delta_1 b_1]\times[\delta_2 a_2,\delta_2 b_2]\times \ldots \times[\delta_d a_d,\delta_d b_d] \Rightarrow m(\delta Q) = \prod_{k = 1}^{d}\delta_k(b_k - a_k) = \Delta m(Q)
Next, observe that if \mathcal{O} is open, \delta \mathcal{O} is open. (This is somewhat trivial... just notice that x \in \mathcal{O} \Rightarrow \exists r > 0 s.t. B_r{(x)} \subset \mathcal{O}.
Now, just let \tau = \min\left\lbrace \delta_1, \ldots, \delta_d \right\rbrace, and observe that x \in \mathcal{O} \Rightarrow \delta x \in \delta \mathcal{O} and B_{\tau r}{(\delta x)} \subset \delta \mathcal{O}.)
Next, since E is measurable, \forall \epsilon > 0, \exists \mathcal{O}, open, such that E \subset \mathcal{O}, and m^*(\mathcal{O}-E) < \frac{\epsilon}{\Delta}. Certainly, E \subset \mathcal{O} \Rightarrow \delta E \subset \delta \mathcal{O}.
Lastly, notice: m^*(\delta \mathcal{O} - \delta E) = \inf \Big\lbrace \sum_{k=1}^{\infty} m(\delta Q_k) \hspace{0.25cm} \Big| \hspace{0.25cm} (\mathcal{O} - E) \subset \bigcup_{k=1}^{\infty} Q_k \Big\rbrace ...which, by (\dagger): = \inf \Big\lbrace \Delta \sum_{k=1}^{\infty} m(Q_k) \hspace{0.25cm} \Big|\hspace{0.25cm} (\mathcal{O} - E) \subset \bigcup_{k=1}^{\infty} Q_k \Big\rbrace = \ldots
\ldots = \Delta m^*(\mathcal{O}-E) < \Delta \frac{\epsilon}{\Delta} = \epsilon ...as desired.
\dagger Observe that for any closed cube Q, \delta Q = [\delta_1 a_1, \delta_1 b_1]\times[\delta_2 a_2,\delta_2 b_2]\times \ldots \times[\delta_d a_d,\delta_d b_d] \Rightarrow m(\delta Q) = \prod_{k = 1}^{d}\delta_k(b_k - a_k) = \Delta m(Q)
Next, observe that if \mathcal{O} is open, \delta \mathcal{O} is open. (This is somewhat trivial... just notice that x \in \mathcal{O} \Rightarrow \exists r > 0 s.t. B_r{(x)} \subset \mathcal{O}.
Now, just let \tau = \min\left\lbrace \delta_1, \ldots, \delta_d \right\rbrace, and observe that x \in \mathcal{O} \Rightarrow \delta x \in \delta \mathcal{O} and B_{\tau r}{(\delta x)} \subset \delta \mathcal{O}.)
Next, since E is measurable, \forall \epsilon > 0, \exists \mathcal{O}, open, such that E \subset \mathcal{O}, and m^*(\mathcal{O}-E) < \frac{\epsilon}{\Delta}. Certainly, E \subset \mathcal{O} \Rightarrow \delta E \subset \delta \mathcal{O}.
Lastly, notice: m^*(\delta \mathcal{O} - \delta E) = \inf \Big\lbrace \sum_{k=1}^{\infty} m(\delta Q_k) \hspace{0.25cm} \Big| \hspace{0.25cm} (\mathcal{O} - E) \subset \bigcup_{k=1}^{\infty} Q_k \Big\rbrace ...which, by (\dagger): = \inf \Big\lbrace \Delta \sum_{k=1}^{\infty} m(Q_k) \hspace{0.25cm} \Big|\hspace{0.25cm} (\mathcal{O} - E) \subset \bigcup_{k=1}^{\infty} Q_k \Big\rbrace = \ldots
\ldots = \Delta m^*(\mathcal{O}-E) < \Delta \frac{\epsilon}{\Delta} = \epsilon ...as desired.
1.5
Part a.) Since E is compact, it's clear that O_n \searrow E, and \forall n, m(O_n) < \infty. Thus, it follows from corollary 3.3 that m(E) = \lim_{n \to \infty} m(O_n).
Part bi.) Let E = \bigcup_{k=1}^{\infty} [k - \frac{1}{2^{k+1}}, k + \frac{1}{2^{k+1}}]. Notice that E^c is clearly an open set, so E must be closed. Certainly, m(E) = \sum_{k = 1}^{\infty} \frac{1}{2^k} = 1.
However, \forall n > 5, (I say 5, but it's probably 2 or 3... who cares, haha.) m(O_n) > \sum_{k = 1}^{\infty} \frac{2}{n} = \infty.
Thus, \lim_{n \to \infty} m(O_n) = \infty \neq m(E).
Part bii.) We see in a later exercise (1.9) that there exist bounded open sets S such that m(\overline{S} \backslash S) > 0. Since for any bounded open set S, O_n \searrow \overline{S}, certainly \lim_{n \to \infty} m(O_n) \neq m(S).
Part bi.) Let E = \bigcup_{k=1}^{\infty} [k - \frac{1}{2^{k+1}}, k + \frac{1}{2^{k+1}}]. Notice that E^c is clearly an open set, so E must be closed. Certainly, m(E) = \sum_{k = 1}^{\infty} \frac{1}{2^k} = 1.
However, \forall n > 5, (I say 5, but it's probably 2 or 3... who cares, haha.) m(O_n) > \sum_{k = 1}^{\infty} \frac{2}{n} = \infty.
Thus, \lim_{n \to \infty} m(O_n) = \infty \neq m(E).
Part bii.) We see in a later exercise (1.9) that there exist bounded open sets S such that m(\overline{S} \backslash S) > 0. Since for any bounded open set S, O_n \searrow \overline{S}, certainly \lim_{n \to \infty} m(O_n) \neq m(S).
Test!
This is a test: \cos{(x + y)} = 1
This is also a test: \mu(E_n) = 0
Nice! We seem to be up and running!
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