Section-A
(Very Short Answer Type Questions)
Note:- Answer all questions. As per the nature of the question you delimit your answer in one word, one sentence or maximum up to 30 words. Each question carries 1 (one) mark.
(Very Short Answer Type Questions)
Note:- Answer all questions. As per the nature of the question you delimit your answer in one word, one sentence or maximum up to 30 words. Each question carries 1 (one) mark.
- (i). Define base for a topology.
(ii). Define asigma \sigma -ring.
(iii). What is Embedding?
(iv). What is Bolazano -Weirstrass property?
Section – B
(Short Answer Questions)
Note :- Answer any two questions. Each answer should be given in 200 words. Each question carries 4 marks.
(Short Answer Questions)
Note :- Answer any two questions. Each answer should be given in 200 words. Each question carries 4 marks.
-
Give an example of a locally connected space which is not connected.
-
Prove that every open interval is a Borel set.
-
Show that the space
L_(2) L_2 of a square summable function is a linear space. -
Show that
L^(p) L^p -space is a normed metric space.
Section-C
(Long Answer Questions)
Note :- Answer any one question. Each answer should be given in 800 words. Each question carries 08 marks.
(Long Answer Questions)
Note :- Answer any one question. Each answer should be given in 800 words. Each question carries 08 marks.
- (i). Show that second countable space is always first countable but converse is not true.
(ii). Prove that the sequence of functions inL^(P) L^P space has at most one limit. - (i). Show that one point compactification of set of rational numbers
Q Q is not Hausdorff.
(ii) Prove that every second countable regular space is normal space.
Section-A
Very Short Answer Type Questions
Question:-1(i)
Define base for a topology.
Answer:
Definition of Base for a Topology
A base (or basis) for a topology on a set X X is a collection B \mathcal{B} of subsets of X X such that:
- Covering Property: Every open set in the topology can be written as a union of elements of
B \mathcal{B} . - Intersection Property: If
B_(1),B_(2)inB B_1, B_2 \in \mathcal{B} andx inB_(1)nnB_(2) x \in B_1 \cap B_2 , then there exists aB_(3)inB B_3 \in \mathcal{B} such thatx inB_(3)subeB_(1)nnB_(2) x \in B_3 \subseteq B_1 \cap B_2 .
Given B \mathcal{B} , the topology generated by B \mathcal{B} is the collection of all subsets of X X that can be written as unions of elements of B \mathcal{B} .
Question:-1(ii)
Define a sigma \sigma -ring.
Answer:
Definition of a sigma \sigma -Ring
A sigma \sigma -ring is a non-empty collection R \mathcal{R} of subsets of a universal set X X that satisfies the following properties:
-
Closure under set difference: If
A,B inR A, B \in \mathcal{R} , thenA\\B inR A \setminus B \in \mathcal{R} .A\\B={x in A:x!in B}. A \setminus B = \{ x \in A : x \notin B \}. -
Closure under countable unions: If
{A_(n)}_(n=1)^(oo) \{ A_n \}_{n=1}^\infty is a countable collection of sets inR \mathcal{R} , then their union is also inR \mathcal{R} :uuu_(n=1)^(oo)A_(n)inR. \bigcup_{n=1}^\infty A_n \in \mathcal{R}. -
Contains the empty set: The empty set
O/ \emptyset belongs toR \mathcal{R} .
Remarks:
- A
sigma \sigma -ring is not required to contain the universal setX X . - If a
sigma \sigma -ring does containX X , then it becomes asigma \sigma -algebra.
Question:-1(iii)
What is Embedding?
Answer:
Definition of Embedding
An embedding is a map (or function) between two mathematical structures that preserves the structure and injectively embeds one into the other.
General Definition:
A map f:A rarr B f: A \to B is called an embedding if:
f f is injective (one-to-one), i.e.,f(a_(1))=f(a_(2))Longrightarrowa_(1)=a_(2) f(a_1) = f(a_2) \implies a_1 = a_2 .f f preserves the structure ofA A inB B .
Question:-1(iv)
What is Bolazano-Weirstrass property?
Answer:
Definition of Bolzano-Weierstrass Property
The Bolzano-Weierstrass property states that:
Every bounded sequence in a Euclidean space (or a metric space) has a convergent subsequence.
Explanation:
-
Bounded Sequence:
- A sequence
{x_(n)} \{x_n\} in a metric space(X,d) (X, d) is bounded if there exists a real numberM > 0 M > 0 and a pointp in X p \in X such that:d(x_(n),p) <= M quad”for all “n. d(x_n, p) \leq M \quad \text{for all } n.
- A sequence
-
Convergent Subsequence:
- A subsequence
{x_(n_(k))} \{x_{n_k}\} of{x_(n)} \{x_n\} is convergent if there exists a pointx in X x \in X such that:lim_(k rarr oo)x_(n_(k))=x, \lim_{k \to \infty} x_{n_k} = x, meaningd(x_(n_(k)),x)rarr0 d(x_{n_k}, x) \to 0 ask rarr oo k \to \infty .
- A subsequence
Section-B
Short Answer Questions
Note: Answer any two questions. Each answer should be given in 200 words.
Question:-2
Give an example of a locally connected space which is not connected.
Answer:
Example of a Locally Connected Space that is Not Connected
A classic example of a locally connected space that is not connected is the disjoint union of two open intervals in R \mathbb{R} .
Example:
Consider the space:
with the standard topology induced from R \mathbb{R} .
Verification:
-
Locally Connected:
- A space is locally connected if every point has a basis of connected open neighborhoods.
- In
X X :- For any point
x in(0,1) x \in (0, 1) , a neighborhood of the form(a,b)nn(0,1) (a, b) \cap (0, 1) , wherea < x < b a < x < b , is connected. - Similarly, for
x in(2,3) x \in (2, 3) , a neighborhood of the form(a,b)nn(2,3) (a, b) \cap (2, 3) is connected.
- For any point
- Thus,
X X is locally connected.
-
Not Connected:
X X is not connected because it can be written as the union of two disjoint non-empty open sets:X=(0,1)uu(2,3). X = (0, 1) \cup (2, 3). - There is no way to connect points from
(0,1) (0, 1) to(2,3) (2, 3) using a path or a connected subset.
Conclusion:
The space X=(0,1)uu(2,3) X = (0, 1) \cup (2, 3) is an example of a space that is locally connected but not connected.
Question:-3
Prove that every open interval is a Borel set.
Answer:
Statement:
Every open interval in R \mathbb{R} is a Borel set.
Proof:
Definition of a Borel Set:
A Borel set is any set that belongs to the smallest sigma \sigma -algebra generated by the open subsets of R \mathbb{R} . This sigma \sigma -algebra, called the Borel sigma \sigma -algebra, is denoted by B(R) \mathcal{B}(\mathbb{R}) .
Open Intervals are Open Sets:
An open interval (a,b)subR (a, b) \subset \mathbb{R} is an open set by definition of the standard topology on R \mathbb{R} .
Open Sets are Borel Sets:
The Borel sigma \sigma -algebra B(R) \mathcal{B}(\mathbb{R}) is defined as the smallest sigma \sigma -algebra containing all open sets of R \mathbb{R} . Therefore:
Construction of Open Intervals:
- Open intervals
(a,b) (a, b) are basic building blocks of the topology onR \mathbb{R} . - Any open set in
R \mathbb{R} is a union of (possibly infinitely many) open intervals. - Since
B(R) \mathcal{B}(\mathbb{R}) is closed under countable unions, any union of open intervals, including the intervals themselves, must also be inB(R) \mathcal{B}(\mathbb{R}) .
Conclusion:
Every open interval (a,b) (a, b) is a Borel set because it is an open set, and open sets are part of the Borel sigma \sigma -algebra B(R) \mathcal{B}(\mathbb{R}) .
Question:-4
Show that the space L_(2) L_2 of square summable functions is a linear space.
Answer:
Statement:
Show that the space L_(2) L_2 of square-summable functions is a linear space.
Definition of L_(2) L_2 :
The space L_(2) L_2 consists of equivalence classes of measurable functions f:[a,b]rarrR f : [a, b] \to \mathbb{R} (or C \mathbb{C} ) for which the square of the absolute value is integrable:
Functions in L_(2) L_2 are considered equivalent if they differ on a set of measure zero.
Proof: L_(2) L_2 is a Linear Space
To show that L_(2) L_2 is a linear space, we must verify that it satisfies the axioms of a vector space.
1. Closure under Addition:
Let f,g inL_(2) f, g \in L_2 . This means:
Now consider h(x)=f(x)+g(x) h(x) = f(x) + g(x) . Using the inequality |f(x)+g(x)|^(2) <= 2|f(x)|^(2)+2|g(x)|^(2) |f(x) + g(x)|^2 \leq 2|f(x)|^2 + 2|g(x)|^2 (from the parallelogram law), we have:
Since int_(a)^(b)|f(x)|^(2)dx < oo \int_a^b |f(x)|^2 dx < \infty and int_(a)^(b)|g(x)|^(2)dx < oo \int_a^b |g(x)|^2 dx < \infty , it follows that:
Thus, h inL_(2) h \in L_2 , and L_(2) L_2 is closed under addition.
2. Closure under Scalar Multiplication:
Let f inL_(2) f \in L_2 and c inR c \in \mathbb{R} (or C \mathbb{C} ). Consider h(x)=cf(x) h(x) = c f(x) . Then:
Since |c|^(2) |c|^2 is a finite constant and int_(a)^(b)|f(x)|^(2)dx < oo \int_a^b |f(x)|^2 dx < \infty , we have:
Thus, h inL_(2) h \in L_2 , and L_(2) L_2 is closed under scalar multiplication.
3. Zero Function:
The zero function f(x)=0 f(x) = 0 for all x in[a,b] x \in [a, b] satisfies:
Hence, the zero function is in L_(2) L_2 .
4. Additive Inverses:
For f inL_(2) f \in L_2 , the function -f -f satisfies:
Thus, -f inL_(2) -f \in L_2 .
Conclusion:
The space L_(2) L_2 satisfies all the axioms of a vector space:
- Closure under addition,
- Closure under scalar multiplication,
- Contains the zero function,
- Contains additive inverses.
Thus, L_(2) L_2 is a linear space.
Question:-5
Show that L^(p) L^p -space is a normed metric space.
Answer:
Statement:
Show that L^(p) L^p -space is a normed metric space for 1 <= p < oo 1 \leq p < \infty .
Definition of L^(p) L^p -Space:
The L^(p) L^p -space consists of equivalence classes of measurable functions f:X rarrR f : X \to \mathbb{R} (or C \mathbb{C} ) defined on a measure space (X,Sigma,mu) (X, \Sigma, \mu) such that:
Functions in L^(p) L^p are considered equivalent if they differ only on a set of measure zero.
To Prove:
L^(p) L^p -space is a normed space.- The norm induces a metric, making
L^(p) L^p a metric space.
Proof:
1. L^(p) L^p -Space is a Normed Space
To show that ||f||_(p) \|f\|_p is a norm, we need to verify the following properties:
-
Non-negativity:
||f||_(p)=(int _(X)|f(x)|^(p)d mu)^(1//p) >= 0, \|f\|_p = \left( \int_X |f(x)|^p \, d\mu \right)^{1/p} \geq 0, and||f||_(p)=0 \|f\|_p = 0 if and only iff(x)=0 f(x) = 0 almost everywhere (a.e.).- This follows from the non-negativity of
|f(x)|^(p) |f(x)|^p and the fact that the integral of a non-negative function is zero only when the function is zero a.e.
- This follows from the non-negativity of
-
Scalar Multiplication:
Forc inR c \in \mathbb{R} (orC \mathbb{C} ) andf inL^(p) f \in L^p :||cf||_(p)=(int _(X)|cf(x)|^(p)d mu)^(1//p)=|c|(int _(X)|f(x)|^(p)d mu)^(1//p)=|c|||f||_(p). \|cf\|_p = \left( \int_X |cf(x)|^p \, d\mu \right)^{1/p} = |c| \left( \int_X |f(x)|^p \, d\mu \right)^{1/p} = |c| \|f\|_p. -
Triangle Inequality (Minkowski’s Inequality):
Forf,g inL^(p) f, g \in L^p :||f+g||_(p)=(int _(X)|f(x)+g(x)|^(p)d mu)^(1//p). \|f + g\|_p = \left( \int_X |f(x) + g(x)|^p \, d\mu \right)^{1/p}. Using Minkowski’s inequality:(int _(X)|f(x)+g(x)|^(p)d mu)^(1//p) <= (int _(X)|f(x)|^(p)d mu)^(1//p)+(int _(X)|g(x)|^(p)d mu)^(1//p). \left( \int_X |f(x) + g(x)|^p \, d\mu \right)^{1/p} \leq \left( \int_X |f(x)|^p \, d\mu \right)^{1/p} + \left( \int_X |g(x)|^p \, d\mu \right)^{1/p}. Thus:||f+g||_(p) <= ||f||_(p)+||g||_(p). \|f + g\|_p \leq \|f\|_p + \|g\|_p. -
Homogeneity and Definiteness:
The properties of scalar multiplication and non-negativity ensure that||f||_(p) \|f\|_p satisfies homogeneity and definiteness.
Thus, ||f||_(p) \|f\|_p is a norm on L^(p) L^p , making L^(p) L^p a normed vector space.
2. L^(p) L^p -Space is a Metric Space
The norm ||f||_(p) \|f\|_p induces a metric d(f,g) d(f, g) on L^(p) L^p defined by:
We verify the metric properties:
-
Non-negativity:
d(f,g)=||f-g||_(p) >= 0, d(f, g) = \|f – g\|_p \geq 0, andd(f,g)=0 d(f, g) = 0 if and only iff=g f = g almost everywhere. -
Symmetry:
d(f,g)=||f-g||_(p)=||g-f||_(p)=d(g,f). d(f, g) = \|f – g\|_p = \|g – f\|_p = d(g, f). -
Triangle Inequality:
Forf,g,h inL^(p) f, g, h \in L^p :d(f,h)=||f-h||_(p)=||f-g+g-h||_(p) <= ||f-g||_(p)+||g-h||_(p)=d(f,g)+d(g,h). d(f, h) = \|f – h\|_p = \|f – g + g – h\|_p \leq \|f – g\|_p + \|g – h\|_p = d(f, g) + d(g, h).
Thus, d(f,g) d(f, g) is a valid metric on L^(p) L^p .
Conclusion:
The L^(p) L^p -space is both a normed vector space and a metric space with the metric induced by the norm. Therefore:
Section-C
Long Answer Questions
Note: Answer any one question. Each answer should be given in 800 words.
Question:-6(i)
Show that second countable space is always first countable, but the converse is not true.
Answer:
Statement:
- Every second countable space is first countable.
- The converse is not true; i.e., a first countable space may not be second countable.
Definitions:
1. Second Countable Space:
A topological space X X is second countable if it has a countable basis B \mathcal{B} . This means:
B \mathcal{B} is a collection of open sets,- For every open set
U sube X U \subseteq X , there exists a subcollection{B_( alpha)inB} \{B_\alpha \in \mathcal{B}\} such thatU=uuu_(alpha)B_( alpha) U = \bigcup_{\alpha} B_\alpha , B \mathcal{B} is countable.
2. First Countable Space:
A topological space X X is first countable if every point x in X x \in X has a countable neighborhood basis. This means:
- For each
x in X x \in X , there exists a countable collection{U_(n)}_(n=1)^(oo) \{U_n\}_{n=1}^\infty of open sets such that:“For any open set “U∋x,” there exists “U_(n)” such that “x inU_(n)sube U. \text{For any open set } U \ni x, \text{ there exists } U_n \text{ such that } x \in U_n \subseteq U.
Part 1: A Second Countable Space is Always First Countable
Proof:
Let X X be a second countable space with a countable basis B={B_(1),B_(2),B_(3),dots} \mathcal{B} = \{B_1, B_2, B_3, \dots\} .
-
Neighborhood Basis Construction:
- Fix
x in X x \in X . - Consider all basis elements
B_(i)inB B_i \in \mathcal{B} such thatx inB_(i) x \in B_i . - Let
{B_(i_(k))}_(k=1)^(oo) \{B_{i_k}\}_{k=1}^\infty be the collection of such basis elements. This is a countable set becauseB \mathcal{B} is countable.
- Fix
-
Verification of Neighborhood Basis:
- For any open set
U∋x U \ni x , there exists a subcollection of basis elements{B_( alpha)inB} \{B_\alpha \in \mathcal{B}\} such thatU=uuu_(alpha)B_( alpha) U = \bigcup_{\alpha} B_\alpha . - In particular, since
x in U x \in U , there existsB_(i_(k))sube U B_{i_k} \subseteq U such thatx inB_(i_(k)) x \in B_{i_k} . - Thus,
{B_(i_(k))} \{B_{i_k}\} forms a countable neighborhood basis forx x .
- For any open set
-
Conclusion:
Since every pointx in X x \in X has a countable neighborhood basis,X X is first countable.
Part 2: A First Countable Space May Not Be Second Countable
Counterexample:
The real line R \mathbb{R} with the discrete topology is first countable but not second countable.
-
First Countable:
- In the discrete topology, the singleton set
{x} \{x\} is open for everyx inR x \in \mathbb{R} . - For any point
x inR x \in \mathbb{R} , a countable neighborhood basis is{{x}} \{\{x\}\} , which is trivially countable. - Thus,
R \mathbb{R} with the discrete topology is first countable.
- In the discrete topology, the singleton set
-
Not Second Countable:
- In the discrete topology, every subset of
R \mathbb{R} is open. - A basis for this topology is the collection of all singleton sets
{{x}:x inR} \{\{x\} : x \in \mathbb{R}\} . - Since
R \mathbb{R} is uncountable, the basis is uncountable. - Therefore,
R \mathbb{R} with the discrete topology is not second countable.
- In the discrete topology, every subset of
Conclusion:
- Every second countable space is first countable because a countable basis ensures the existence of a countable neighborhood basis for each point.
- The converse is false; for example,
R \mathbb{R} with the discrete topology is first countable but not second countable.
Question:-6(ii)
Prove that the sequence of functions in L^(p) L^p space has at most one limit.
Answer:
Statement:
Prove that a sequence of functions in L^(p) L^p space (1 <= p < oo 1 \leq p < \infty ) can have at most one limit in the L^(p) L^p -norm.
Definitions:
1. L^(p) L^p -Space:
The L^(p) L^p -space consists of equivalence classes of measurable functions f:X rarrR f : X \to \mathbb{R} (or C \mathbb{C} ) defined on a measure space (X,Sigma,mu) (X, \Sigma, \mu) such that:
2. Convergence in L^(p) L^p -Norm:
A sequence of functions {f_(n)} \{f_n\} converges to f f in the L^(p) L^p -norm if:
3. Uniqueness of Limits:
To show uniqueness, we need to prove that if f,g inL^(p) f, g \in L^p are limits of the same sequence {f_(n)} \{f_n\} , then f=g f = g almost everywhere.
Proof:
Step 1: Assumption of Two Limits
Let f,g inL^(p) f, g \in L^p be two limits of the sequence {f_(n)} \{f_n\} in L^(p) L^p -norm. This means:
Step 2: Triangle Inequality
Consider the norm ||f-g||_(p) \|f – g\|_p . Using the triangle inequality for the L^(p) L^p -norm:
Step 3: Taking the Limit
As n rarr oo n \to \infty , both ||f-f_(n)||_(p) \|f – f_n\|_p and ||f_(n)-g||_(p) \|f_n – g\|_p converge to 0 0 (by the assumption that f f and g g are limits of {f_(n)} \{f_n\} ). Thus:
Step 4: Norm Zero Implies Equality Almost Everywhere
In L^(p) L^p -spaces, ||f-g||_(p)=0 \|f – g\|_p = 0 implies that f(x)=g(x) f(x) = g(x) for almost all x in X x \in X (i.e., f=g f = g almost everywhere).
Conclusion:
If a sequence {f_(n)} \{f_n\} in L^(p) L^p converges to two functions f f and g g in the L^(p) L^p -norm, then f=g f = g almost everywhere. Therefore, the sequence {f_(n)} \{f_n\} can have at most one limit in L^(p) L^p -norm.
Question:-7(i)
Show that one point compactification of the set of rational numbers Q Q is not Hausdorff.
Answer:
Statement:
The one-point compactification of the set of rational numbers Q \mathbb{Q} is not Hausdorff.
Definitions:
1. One-Point Compactification:
Let X X be a non-compact, locally compact, Hausdorff topological space. The one-point compactification X^(**) X^* of X X is defined as:
where oo \infty is an additional point, and the topology on X^(**) X^* is defined as:
- The open sets of
X^(**) X^* include:- All open sets of
X X , - Sets of the form
U_( oo)=X^(**)\\K U_\infty = X^* \setminus K , whereK sube X K \subseteq X is compact inX X .
- All open sets of
2. Hausdorff Space:
A topological space Y Y is Hausdorff if for any two distinct points y_(1),y_(2)in Y y_1, y_2 \in Y , there exist disjoint open sets U_(1),U_(2) U_1, U_2 such that y_(1)inU_(1) y_1 \in U_1 and y_(2)inU_(2) y_2 \in U_2 .
Proof:
Step 1: The Rational Numbers Q \mathbb{Q}
The set of rational numbers Q \mathbb{Q} with the usual topology induced from R \mathbb{R} is:
- Locally compact: Every point
q inQ q \in \mathbb{Q} has a compact neighborhood (e.g.,[q-epsilon,q+epsilon]nnQ [q – \epsilon, q + \epsilon] \cap \mathbb{Q} ). - Not compact: The space
Q \mathbb{Q} is not compact because it is not closed inR \mathbb{R} , and sequences likeq_(n)=1+1//n q_n = 1 + 1/n do not have convergent subsequences inQ \mathbb{Q} .
Thus, the one-point compactification Q^(**)=Quu{oo} \mathbb{Q}^* = \mathbb{Q} \cup \{\infty\} is well-defined.
Step 2: Neighborhoods in Q^(**) \mathbb{Q}^*
- In
Q \mathbb{Q} , the open sets are the usual open sets inherited fromR \mathbb{R} . - For the point
oo \infty , open neighborhoods are of the form:U_( oo)=Q^(**)\\K, U_\infty = \mathbb{Q}^* \setminus K, whereK subeQ K \subseteq \mathbb{Q} is compact.
Since Q \mathbb{Q} is not compact, any compact subset K K of Q \mathbb{Q} is a finite union of closed and bounded subsets of Q \mathbb{Q} . Therefore, U_( oo) U_\infty is "large" in Q \mathbb{Q} , and neighborhoods of oo \infty will always include all but a compact subset of Q \mathbb{Q} .
Step 3: Hausdorff Property and Failure
To show Q^(**) \mathbb{Q}^* is not Hausdorff, we need to find two points x,y inQ^(**) x, y \in \mathbb{Q}^* such that no disjoint open sets separate x x and y y .
-
Let
x inQ x \in \mathbb{Q} andoo \infty . Suppose there exist disjoint open setsU U andV V such that:x in U x \in U ,oo in V \infty \in V .
-
By definition of neighborhoods of
oo \infty ,V=U_( oo)=Q^(**)\\K V = U_\infty = \mathbb{Q}^* \setminus K for some compactK subeQ K \subseteq \mathbb{Q} . Thus,K K is closed and bounded inQ \mathbb{Q} . -
Since
K K is compact, it contains only finitely many points ofQ \mathbb{Q} . However,Q \mathbb{Q} is dense inR \mathbb{R} , so any open setU subeQ U \subseteq \mathbb{Q} containingx x will intersectK K . This impliesU nn V!=O/ U \cap V \neq \emptyset , contradicting the assumption thatU U andV V are disjoint.
Conclusion:
The one-point compactification Q^(**)=Quu{oo} \mathbb{Q}^* = \mathbb{Q} \cup \{\infty\} fails the Hausdorff condition because neighborhoods of oo \infty cannot be disjoint from neighborhoods of points in Q \mathbb{Q} . Therefore:
Question:-7(ii)
Prove that every second countable regular space is a normal space.
Answer:
Statement:
Every second countable, regular topological space is a normal space.
Definitions:
-
Second Countable Space:
A topological spaceX X is second countable if it has a countable basisB \mathcal{B} , i.e., a countable collection of open sets such that every open set inX X can be expressed as a union of sets inB \mathcal{B} . -
Regular Space:
A topological spaceX X is regular if:X X isT_(1) T_1 , meaning every singleton set{x} \{x\} is closed, and- For every closed set
F sube X F \subseteq X and a pointp!in F p \notin F , there exist disjoint open setsU U andV V such that:F sube U quad”and”quad p in V. F \subseteq U \quad \text{and} \quad p \in V.
-
Normal Space:
A topological spaceX X is normal if:X X isT_(1) T_1 , and- For any two disjoint closed sets
F_(1),F_(2)sube X F_1, F_2 \subseteq X , there exist disjoint open setsU_(1) U_1 andU_(2) U_2 such that:F_(1)subeU_(1)quad”and”quadF_(2)subeU_(2). F_1 \subseteq U_1 \quad \text{and} \quad F_2 \subseteq U_2.
Proof:
Given:
Step 1: Second Countability and Regularity
- Second countability implies that
X X has a countable basisB \mathcal{B} . - Regularity means for any closed set
F sube X F \subseteq X andp!in F p \notin F , there exist disjoint open sets separatingF F andp p .
Step 2: Let F_(1) F_1 and F_(2) F_2 be Two Disjoint Closed Sets
We need to find disjoint open sets U_(1) U_1 and U_(2) U_2 such that:
Step 3: Use Regularity to Separate Points
Fix a point x inF_(1) x \in F_1 . Since F_(1) F_1 and F_(2) F_2 are disjoint and closed, x!inF_(2) x \notin F_2 . By the regularity of X X , there exist disjoint open sets U_(x) U_x and V_(x) V_x such that:
Step 4: Cover F_(1) F_1 Using B \mathcal{B}
For each x inF_(1) x \in F_1 , choose U_(x) U_x as above. Since F_(1) F_1 is closed and B \mathcal{B} is a countable basis, we can cover F_(1) F_1 by a countable subcollection of the sets {U_(x)}_(x inF_(1)) \{U_x\}_{x \in F_1} . Let this subcollection be {U_(x_(1)),U_(x_(2)),dots} \{U_{x_1}, U_{x_2}, \ldots\} .
Define:
Clearly:
Step 5: Ensure U_(1) U_1 and U_(2) U_2 are Disjoint
For each U_(x) U_x , the corresponding V_(x) V_x separates x x from F_(2) F_2 . Since F_(2)subennn_(x inF_(1))V_(x) F_2 \subseteq \bigcap_{x \in F_1} V_x , define:
Thus, U_(1) U_1 and U_(2) U_2 are disjoint open sets satisfying:
Step 6: Conclusion
We have shown that for any two disjoint closed sets F_(1),F_(2) F_1, F_2 in X X , there exist disjoint open sets U_(1) U_1 and U_(2) U_2 such that F_(1)subeU_(1) F_1 \subseteq U_1 and F_(2)subeU_(2) F_2 \subseteq U_2 . This proves X X is normal.