VMOU MT-02 SOLVED ASSIGNMENT | MA/M.SC. MT- 02(Real Analysis and Topology) | July-2024 & January-2025

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.
  1. (i). Define base for a topology.
    (ii). Define a σ σ sigma\sigmaσ-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.
  1. Give an example of a locally connected space which is not connected.
  2. Prove that every open interval is a Borel set.
  3. Show that the space L 2 L 2 L_(2)L_2L2 of a square summable function is a linear space.
  4. Show that L p L p L^(p)L^pLp-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.
  1. (i). Show that second countable space is always first countable but converse is not true.
    (ii). Prove that the sequence of functions in L P L P L^(P)L^PLP space has at most one limit.
  2. (i). Show that one point compactification of set of rational numbers Q Q QQQ 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 XXX is a collection B B B\mathcal{B}B of subsets of X X XXX such that:
  1. Covering Property: Every open set in the topology can be written as a union of elements of B B B\mathcal{B}B.
  2. Intersection Property: If B 1 , B 2 B B 1 , B 2 B B_(1),B_(2)inBB_1, B_2 \in \mathcal{B}B1,B2B and x B 1 B 2 x B 1 B 2 x inB_(1)nnB_(2)x \in B_1 \cap B_2xB1B2, then there exists a B 3 B B 3 B B_(3)inBB_3 \in \mathcal{B}B3B such that x B 3 B 1 B 2 x B 3 B 1 B 2 x inB_(3)subeB_(1)nnB_(2)x \in B_3 \subseteq B_1 \cap B_2xB3B1B2.
Given B B B\mathcal{B}B, the topology generated by B B B\mathcal{B}B is the collection of all subsets of X X XXX that can be written as unions of elements of B B B\mathcal{B}B.

Question:-1(ii)

Define a σ σ sigma\sigmaσ-ring.

Answer:

Definition of a σ σ sigma\sigmaσ-Ring

A σ σ sigma\sigmaσ-ring is a non-empty collection R R R\mathcal{R}R of subsets of a universal set X X XXX that satisfies the following properties:
  1. Closure under set difference: If A , B R A , B R A,B inRA, B \in \mathcal{R}A,BR, then A B R A B R A\\B inRA \setminus B \in \mathcal{R}ABR.
    A B = { x A : x B } . A B = { x A : x B } . A\\B={x in A:x!in B}.A \setminus B = \{ x \in A : x \notin B \}.AB={xA:xB}.
  2. Closure under countable unions: If { A n } n = 1 { A n } n = 1 {A_(n)}_(n=1)^(oo)\{ A_n \}_{n=1}^\infty{An}n=1 is a countable collection of sets in R R R\mathcal{R}R, then their union is also in R R R\mathcal{R}R:
    n = 1 A n R . n = 1 A n R . uuu_(n=1)^(oo)A_(n)inR.\bigcup_{n=1}^\infty A_n \in \mathcal{R}.n=1AnR.
  3. Contains the empty set: The empty set O/\emptyset belongs to R R R\mathcal{R}R.

Remarks:

  • A σ σ sigma\sigmaσ-ring is not required to contain the universal set X X XXX.
  • If a σ σ sigma\sigmaσ-ring does contain X X XXX, then it becomes a σ σ sigma\sigmaσ-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 B f : A B f:A rarr Bf: A \to Bf:AB is called an embedding if:
  1. f f fff is injective (one-to-one), i.e., f ( a 1 ) = f ( a 2 ) a 1 = a 2 f ( a 1 ) = f ( a 2 ) a 1 = a 2 f(a_(1))=f(a_(2))Longrightarrowa_(1)=a_(2)f(a_1) = f(a_2) \implies a_1 = a_2f(a1)=f(a2)a1=a2.
  2. f f fff preserves the structure of A A AAA in B B BBB.

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:

  1. Bounded Sequence:
    • A sequence { x n } { x n } {x_(n)}\{x_n\}{xn} in a metric space ( X , d ) ( X , d ) (X,d)(X, d)(X,d) is bounded if there exists a real number M > 0 M > 0 M > 0M > 0M>0 and a point p X p X p in Xp \in XpX such that: d ( x n , p ) M for all n . d ( x n , p ) M for all n . d(x_(n),p) <= M quad”for all “n.d(x_n, p) \leq M \quad \text{for all } n.d(xn,p)Mfor all n.
  2. Convergent Subsequence:
    • A subsequence { x n k } { x n k } {x_(n_(k))}\{x_{n_k}\}{xnk} of { x n } { x n } {x_(n)}\{x_n\}{xn} is convergent if there exists a point x X x X x in Xx \in XxX such that: lim k x n k = x , lim k x n k = x , lim_(k rarr oo)x_(n_(k))=x,\lim_{k \to \infty} x_{n_k} = x,limkxnk=x,meaning d ( x n k , x ) 0 d ( x n k , x ) 0 d(x_(n_(k)),x)rarr0d(x_{n_k}, x) \to 0d(xnk,x)0 as k k k rarr ook \to \inftyk.



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 R R\mathbb{R}R.

Example:

Consider the space:
X = ( 0 , 1 ) ( 2 , 3 ) R , X = ( 0 , 1 ) ( 2 , 3 ) R , X=(0,1)uu(2,3)subR,X = (0, 1) \cup (2, 3) \subset \mathbb{R},X=(0,1)(2,3)R,
with the standard topology induced from R R R\mathbb{R}R.

Verification:

  1. Locally Connected:
    • A space is locally connected if every point has a basis of connected open neighborhoods.
    • In X X XXX:
      • For any point x ( 0 , 1 ) x ( 0 , 1 ) x in(0,1)x \in (0, 1)x(0,1), a neighborhood of the form ( a , b ) ( 0 , 1 ) ( a , b ) ( 0 , 1 ) (a,b)nn(0,1)(a, b) \cap (0, 1)(a,b)(0,1), where a < x < b a < x < b a < x < ba < x < ba<x<b, is connected.
      • Similarly, for x ( 2 , 3 ) x ( 2 , 3 ) x in(2,3)x \in (2, 3)x(2,3), a neighborhood of the form ( a , b ) ( 2 , 3 ) ( a , b ) ( 2 , 3 ) (a,b)nn(2,3)(a, b) \cap (2, 3)(a,b)(2,3) is connected.
    • Thus, X X XXX is locally connected.
  2. Not Connected:
    • X X XXX is not connected because it can be written as the union of two disjoint non-empty open sets: X = ( 0 , 1 ) ( 2 , 3 ) . X = ( 0 , 1 ) ( 2 , 3 ) . X=(0,1)uu(2,3).X = (0, 1) \cup (2, 3).X=(0,1)(2,3).
    • There is no way to connect points from ( 0 , 1 ) ( 0 , 1 ) (0,1)(0, 1)(0,1) to ( 2 , 3 ) ( 2 , 3 ) (2,3)(2, 3)(2,3) using a path or a connected subset.

Conclusion:

The space X = ( 0 , 1 ) ( 2 , 3 ) X = ( 0 , 1 ) ( 2 , 3 ) X=(0,1)uu(2,3)X = (0, 1) \cup (2, 3)X=(0,1)(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 R R\mathbb{R}R is a Borel set.

Proof:

Definition of a Borel Set:

A Borel set is any set that belongs to the smallest σ σ sigma\sigmaσ-algebra generated by the open subsets of R R R\mathbb{R}R. This σ σ sigma\sigmaσ-algebra, called the Borel σ σ sigma\sigmaσ-algebra, is denoted by B ( R ) B ( R ) B(R)\mathcal{B}(\mathbb{R})B(R).

Open Intervals are Open Sets:

An open interval ( a , b ) R ( a , b ) R (a,b)subR(a, b) \subset \mathbb{R}(a,b)R is an open set by definition of the standard topology on R R R\mathbb{R}R.

Open Sets are Borel Sets:

The Borel σ σ sigma\sigmaσ-algebra B ( R ) B ( R ) B(R)\mathcal{B}(\mathbb{R})B(R) is defined as the smallest σ σ sigma\sigmaσ-algebra containing all open sets of R R R\mathbb{R}R. Therefore:
All open sets, including open intervals, belong to B ( R ) . All open sets, including open intervals, belong to B ( R ) . “All open sets, including open intervals, belong to “B(R).\text{All open sets, including open intervals, belong to } \mathcal{B}(\mathbb{R}).All open sets, including open intervals, belong to B(R).

Construction of Open Intervals:

  1. Open intervals ( a , b ) ( a , b ) (a,b)(a, b)(a,b) are basic building blocks of the topology on R R R\mathbb{R}R.
  2. Any open set in R R R\mathbb{R}R is a union of (possibly infinitely many) open intervals.
  3. Since B ( R ) B ( R ) B(R)\mathcal{B}(\mathbb{R})B(R) is closed under countable unions, any union of open intervals, including the intervals themselves, must also be in B ( R ) B ( R ) B(R)\mathcal{B}(\mathbb{R})B(R).

Conclusion:

Every open interval ( a , b ) ( a , b ) (a,b)(a, b)(a,b) is a Borel set because it is an open set, and open sets are part of the Borel σ σ sigma\sigmaσ-algebra B ( R ) B ( R ) B(R)\mathcal{B}(\mathbb{R})B(R).
Q.E.D. Q.E.D. “Q.E.D.”\boxed{\text{Q.E.D.}}Q.E.D.

Question:-4

Show that the space L 2 L 2 L_(2)L_2L2 of square summable functions is a linear space.

Answer:

Statement:

Show that the space L 2 L 2 L_(2)L_2L2 of square-summable functions is a linear space.

Definition of L 2 L 2 L_(2)L_2L2:

The space L 2 L 2 L_(2)L_2L2 consists of equivalence classes of measurable functions f : [ a , b ] R f : [ a , b ] R f:[a,b]rarrRf : [a, b] \to \mathbb{R}f:[a,b]R (or C C C\mathbb{C}C) for which the square of the absolute value is integrable:
L 2 = { f : [ a , b ] R a b | f ( x ) | 2 d x < } . L 2 = f : [ a , b ] R a b | f ( x ) | 2 d x < . L_(2)={f:[a,b]rarrR∣int_(a)^(b)|f(x)|^(2)dx < oo}.L_2 = \left\{ f : [a, b] \to \mathbb{R} \mid \int_a^b |f(x)|^2 dx < \infty \right\}.L2={f:[a,b]Rab|f(x)|2dx<}.
Functions in L 2 L 2 L_(2)L_2L2 are considered equivalent if they differ on a set of measure zero.

Proof: L 2 L 2 L_(2)L_2L2 is a Linear Space

To show that L 2 L 2 L_(2)L_2L2 is a linear space, we must verify that it satisfies the axioms of a vector space.

1. Closure under Addition:

Let f , g L 2 f , g L 2 f,g inL_(2)f, g \in L_2f,gL2. This means:
a b | f ( x ) | 2 d x < and a b | g ( x ) | 2 d x < . a b | f ( x ) | 2 d x < and a b | g ( x ) | 2 d x < . int_(a)^(b)|f(x)|^(2)dx < ooquad”and”quadint_(a)^(b)|g(x)|^(2)dx < oo.\int_a^b |f(x)|^2 dx < \infty \quad \text{and} \quad \int_a^b |g(x)|^2 dx < \infty.ab|f(x)|2dx<andab|g(x)|2dx<.
Now consider h ( x ) = f ( x ) + g ( x ) h ( x ) = f ( x ) + g ( x ) h(x)=f(x)+g(x)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 2 | f ( x ) | 2 + 2 | g ( x ) | 2 |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|f(x)+g(x)|22|f(x)|2+2|g(x)|2 (from the parallelogram law), we have:
a b | h ( x ) | 2 d x = a b | f ( x ) + g ( x ) | 2 d x a b 2 | f ( x ) | 2 d x + a b 2 | g ( x ) | 2 d x . a b | h ( x ) | 2 d x = a b | f ( x ) + g ( x ) | 2 d x a b 2 | f ( x ) | 2 d x + a b 2 | g ( x ) | 2 d x . int_(a)^(b)|h(x)|^(2)dx=int_(a)^(b)|f(x)+g(x)|^(2)dx <= int_(a)^(b)2|f(x)|^(2)dx+int_(a)^(b)2|g(x)|^(2)dx.\int_a^b |h(x)|^2 dx = \int_a^b |f(x) + g(x)|^2 dx \leq \int_a^b 2|f(x)|^2 dx + \int_a^b 2|g(x)|^2 dx.ab|h(x)|2dx=ab|f(x)+g(x)|2dxab2|f(x)|2dx+ab2|g(x)|2dx.
Since a b | f ( x ) | 2 d x < a b | f ( x ) | 2 d x < int_(a)^(b)|f(x)|^(2)dx < oo\int_a^b |f(x)|^2 dx < \inftyab|f(x)|2dx< and a b | g ( x ) | 2 d x < a b | g ( x ) | 2 d x < int_(a)^(b)|g(x)|^(2)dx < oo\int_a^b |g(x)|^2 dx < \inftyab|g(x)|2dx<, it follows that:
a b | h ( x ) | 2 d x < . a b | h ( x ) | 2 d x < . int_(a)^(b)|h(x)|^(2)dx < oo.\int_a^b |h(x)|^2 dx < \infty.ab|h(x)|2dx<.
Thus, h L 2 h L 2 h inL_(2)h \in L_2hL2, and L 2 L 2 L_(2)L_2L2 is closed under addition.

2. Closure under Scalar Multiplication:

Let f L 2 f L 2 f inL_(2)f \in L_2fL2 and c R c R c inRc \in \mathbb{R}cR (or C C C\mathbb{C}C). Consider h ( x ) = c f ( x ) h ( x ) = c f ( x ) h(x)=cf(x)h(x) = c f(x)h(x)=cf(x). Then:
a b | h ( x ) | 2 d x = a b | c f ( x ) | 2 d x = | c | 2 a b | f ( x ) | 2 d x . a b | h ( x ) | 2 d x = a b | c f ( x ) | 2 d x = | c | 2 a b | f ( x ) | 2 d x . int_(a)^(b)|h(x)|^(2)dx=int_(a)^(b)|cf(x)|^(2)dx=|c|^(2)int_(a)^(b)|f(x)|^(2)dx.\int_a^b |h(x)|^2 dx = \int_a^b |c f(x)|^2 dx = |c|^2 \int_a^b |f(x)|^2 dx.ab|h(x)|2dx=ab|cf(x)|2dx=|c|2ab|f(x)|2dx.
Since | c | 2 | c | 2 |c|^(2)|c|^2|c|2 is a finite constant and a b | f ( x ) | 2 d x < a b | f ( x ) | 2 d x < int_(a)^(b)|f(x)|^(2)dx < oo\int_a^b |f(x)|^2 dx < \inftyab|f(x)|2dx<, we have:
a b | h ( x ) | 2 d x < . a b | h ( x ) | 2 d x < . int_(a)^(b)|h(x)|^(2)dx < oo.\int_a^b |h(x)|^2 dx < \infty.ab|h(x)|2dx<.
Thus, h L 2 h L 2 h inL_(2)h \in L_2hL2, and L 2 L 2 L_(2)L_2L2 is closed under scalar multiplication.

3. Zero Function:

The zero function f ( x ) = 0 f ( x ) = 0 f(x)=0f(x) = 0f(x)=0 for all x [ a , b ] x [ a , b ] x in[a,b]x \in [a, b]x[a,b] satisfies:
a b | f ( x ) | 2 d x = 0 < . a b | f ( x ) | 2 d x = 0 < . int_(a)^(b)|f(x)|^(2)dx=0 < oo.\int_a^b |f(x)|^2 dx = 0 < \infty.ab|f(x)|2dx=0<.
Hence, the zero function is in L 2 L 2 L_(2)L_2L2.

4. Additive Inverses:

For f L 2 f L 2 f inL_(2)f \in L_2fL2, the function f f -f-ff satisfies:
a b | ( f ) ( x ) | 2 d x = a b | f ( x ) | 2 d x < . a b | ( f ) ( x ) | 2 d x = a b | f ( x ) | 2 d x < . int_(a)^(b)|(-f)(x)|^(2)dx=int_(a)^(b)|f(x)|^(2)dx < oo.\int_a^b |(-f)(x)|^2 dx = \int_a^b |f(x)|^2 dx < \infty.ab|(f)(x)|2dx=ab|f(x)|2dx<.
Thus, f L 2 f L 2 -f inL_(2)-f \in L_2fL2.

Conclusion:

The space L 2 L 2 L_(2)L_2L2 satisfies all the axioms of a vector space:
  1. Closure under addition,
  2. Closure under scalar multiplication,
  3. Contains the zero function,
  4. Contains additive inverses.
Thus, L 2 L 2 L_(2)L_2L2 is a linear space.
Q.E.D. Q.E.D. “Q.E.D.”\boxed{\text{Q.E.D.}}Q.E.D.

Question:-5

Show that L p L p L^(p)L^pLp-space is a normed metric space.

Answer:

Statement:

Show that L p L p L^(p)L^pLp-space is a normed metric space for 1 p < 1 p < 1 <= p < oo1 \leq p < \infty1p<.

Definition of L p L p L^(p)L^pLp-Space:

The L p L p L^(p)L^pLp-space consists of equivalence classes of measurable functions f : X R f : X R f:X rarrRf : X \to \mathbb{R}f:XR (or C C C\mathbb{C}C) defined on a measure space ( X , Σ , μ ) ( X , Σ , μ ) (X,Sigma,mu)(X, \Sigma, \mu)(X,Σ,μ) such that:
f p = ( X | f ( x ) | p d μ ) 1 / p < . f p = X | f ( x ) | p d μ 1 / p < . ||f||_(p)=(int _(X)|f(x)|^(p)d mu)^(1//p) < oo.\|f\|_p = \left( \int_X |f(x)|^p \, d\mu \right)^{1/p} < \infty.fp=(X|f(x)|pdμ)1/p<.
Functions in L p L p L^(p)L^pLp are considered equivalent if they differ only on a set of measure zero.

To Prove:

  1. L p L p L^(p)L^pLp-space is a normed space.
  2. The norm induces a metric, making L p L p L^(p)L^pLp a metric space.

Proof:

1. L p L p L^(p)L^pLp-Space is a Normed Space

To show that f p f p ||f||_(p)\|f\|_pfp is a norm, we need to verify the following properties:
  1. Non-negativity:
    f p = ( X | f ( x ) | p d μ ) 1 / p 0 , f p = X | f ( x ) | p d μ 1 / p 0 , ||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,fp=(X|f(x)|pdμ)1/p0,
    and f p = 0 f p = 0 ||f||_(p)=0\|f\|_p = 0fp=0 if and only if f ( x ) = 0 f ( x ) = 0 f(x)=0f(x) = 0f(x)=0 almost everywhere (a.e.).
    • This follows from the non-negativity of | f ( x ) | p | f ( x ) | p |f(x)|^(p)|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.
  2. Scalar Multiplication:
    For c R c R c inRc \in \mathbb{R}cR (or C C C\mathbb{C}C) and f L p f L p f inL^(p)f \in L^pfLp:
    c f p = ( X | c f ( x ) | p d μ ) 1 / p = | c | ( X | f ( x ) | p d μ ) 1 / p = | c | f p . c f p = X | c f ( x ) | p d μ 1 / p = | c | X | f ( x ) | p d μ 1 / p = | c | f 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.cfp=(X|cf(x)|pdμ)1/p=|c|(X|f(x)|pdμ)1/p=|c|fp.
  3. Triangle Inequality (Minkowski’s Inequality):
    For f , g L p f , g L p f,g inL^(p)f, g \in L^pf,gLp:
    f + g p = ( X | f ( x ) + g ( x ) | p d μ ) 1 / p . f + g p = X | f ( x ) + g ( x ) | p d μ 1 / 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}.f+gp=(X|f(x)+g(x)|pdμ)1/p.
    Using Minkowski’s inequality:
    ( X | f ( x ) + g ( x ) | p d μ ) 1 / p ( X | f ( x ) | p d μ ) 1 / p + ( X | g ( x ) | p d μ ) 1 / p . X | f ( x ) + g ( x ) | p d μ 1 / p X | f ( x ) | p d μ 1 / p + X | g ( x ) | p d μ 1 / p . (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}.(X|f(x)+g(x)|pdμ)1/p(X|f(x)|pdμ)1/p+(X|g(x)|pdμ)1/p.
    Thus:
    f + g p f p + g p . f + g p f p + g p . ||f+g||_(p) <= ||f||_(p)+||g||_(p).\|f + g\|_p \leq \|f\|_p + \|g\|_p.f+gpfp+gp.
  4. Homogeneity and Definiteness:
    The properties of scalar multiplication and non-negativity ensure that f p f p ||f||_(p)\|f\|_pfp satisfies homogeneity and definiteness.
Thus, f p f p ||f||_(p)\|f\|_pfp is a norm on L p L p L^(p)L^pLp, making L p L p L^(p)L^pLp a normed vector space.

2. L p L p L^(p)L^pLp-Space is a Metric Space

The norm f p f p ||f||_(p)\|f\|_pfp induces a metric d ( f , g ) d ( f , g ) d(f,g)d(f, g)d(f,g) on L p L p L^(p)L^pLp defined by:
d ( f , g ) = f g p = ( X | f ( x ) g ( x ) | p d μ ) 1 / p . d ( f , g ) = f g p = X | f ( x ) g ( x ) | p d μ 1 / p . d(f,g)=||f-g||_(p)=(int _(X)|f(x)-g(x)|^(p)d mu)^(1//p).d(f, g) = \|f – g\|_p = \left( \int_X |f(x) – g(x)|^p \, d\mu \right)^{1/p}.d(f,g)=fgp=(X|f(x)g(x)|pdμ)1/p.
We verify the metric properties:
  1. Non-negativity:
    d ( f , g ) = f g p 0 , d ( f , g ) = f g p 0 , d(f,g)=||f-g||_(p) >= 0,d(f, g) = \|f – g\|_p \geq 0,d(f,g)=fgp0,
    and d ( f , g ) = 0 d ( f , g ) = 0 d(f,g)=0d(f, g) = 0d(f,g)=0 if and only if f = g f = g f=gf = gf=g almost everywhere.
  2. 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 ) . d(f,g)=||f-g||_(p)=||g-f||_(p)=d(g,f).d(f, g) = \|f – g\|_p = \|g – f\|_p = d(g, f).d(f,g)=fgp=gfp=d(g,f).
  3. Triangle Inequality:
    For f , g , h L p f , g , h L p f,g,h inL^(p)f, g, h \in L^pf,g,hLp:
    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 f g p + g h p = d ( f , g ) + d ( g , h ) . 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).d(f,h)=fhp=fg+ghpfgp+ghp=d(f,g)+d(g,h).
Thus, d ( f , g ) d ( f , g ) d(f,g)d(f, g)d(f,g) is a valid metric on L p L p L^(p)L^pLp.

Conclusion:

The L p L p L^(p)L^pLp-space is both a normed vector space and a metric space with the metric induced by the norm. Therefore:
L p is a normed metric space. L p is a normed metric space. (L^(p))” is a normed metric space.”\boxed{\text{\( L^p \) is a normed metric space.}}Lp is a normed metric space.


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:

  1. Every second countable space is first countable.
  2. 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 XXX is second countable if it has a countable basis B B B\mathcal{B}B. This means:
  • B B B\mathcal{B}B is a collection of open sets,
  • For every open set U X U X U sube XU \subseteq XUX, there exists a subcollection { B α B } { B α B } {B_( alpha)inB}\{B_\alpha \in \mathcal{B}\}{BαB} such that U = α B α U = α B α U=uuu_(alpha)B_( alpha)U = \bigcup_{\alpha} B_\alphaU=αBα,
  • B B B\mathcal{B}B is countable.

2. First Countable Space:

A topological space X X XXX is first countable if every point x X x X x in Xx \in XxX has a countable neighborhood basis. This means:
  • For each x X x X x in Xx \in XxX, there exists a countable collection { U n } n = 1 { U n } n = 1 {U_(n)}_(n=1)^(oo)\{U_n\}_{n=1}^\infty{Un}n=1 of open sets such that: For any open set U x , there exists U n such that x U n U . For any open set U x , there exists U n such that x U n U . “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.For any open set Ux, there exists Un such that xUnU.

Part 1: A Second Countable Space is Always First Countable

Proof:

Let X X XXX be a second countable space with a countable basis B = { B 1 , B 2 , B 3 , } B = { B 1 , B 2 , B 3 , } B={B_(1),B_(2),B_(3),dots}\mathcal{B} = \{B_1, B_2, B_3, \dots\}B={B1,B2,B3,}.
  1. Neighborhood Basis Construction:
    • Fix x X x X x in Xx \in XxX.
    • Consider all basis elements B i B B i B B_(i)inBB_i \in \mathcal{B}BiB such that x B i x B i x inB_(i)x \in B_ixBi.
    • Let { B i k } k = 1 { B i k } k = 1 {B_(i_(k))}_(k=1)^(oo)\{B_{i_k}\}_{k=1}^\infty{Bik}k=1 be the collection of such basis elements. This is a countable set because B B B\mathcal{B}B is countable.
  2. Verification of Neighborhood Basis:
    • For any open set U x U x U∋xU \ni xUx, there exists a subcollection of basis elements { B α B } { B α B } {B_( alpha)inB}\{B_\alpha \in \mathcal{B}\}{BαB} such that U = α B α U = α B α U=uuu_(alpha)B_( alpha)U = \bigcup_{\alpha} B_\alphaU=αBα.
    • In particular, since x U x U x in Ux \in UxU, there exists B i k U B i k U B_(i_(k))sube UB_{i_k} \subseteq UBikU such that x B i k x B i k x inB_(i_(k))x \in B_{i_k}xBik.
    • Thus, { B i k } { B i k } {B_(i_(k))}\{B_{i_k}\}{Bik} forms a countable neighborhood basis for x x xxx.
  3. Conclusion:
    Since every point x X x X x in Xx \in XxX has a countable neighborhood basis, X X XXX is first countable.

Part 2: A First Countable Space May Not Be Second Countable

Counterexample:

The real line R R R\mathbb{R}R with the discrete topology is first countable but not second countable.
  1. First Countable:
    • In the discrete topology, the singleton set { x } { x } {x}\{x\}{x} is open for every x R x R x inRx \in \mathbb{R}xR.
    • For any point x R x R x inRx \in \mathbb{R}xR, a countable neighborhood basis is { { x } } { { x } } {{x}}\{\{x\}\}{{x}}, which is trivially countable.
    • Thus, R R R\mathbb{R}R with the discrete topology is first countable.
  2. Not Second Countable:
    • In the discrete topology, every subset of R R R\mathbb{R}R is open.
    • A basis for this topology is the collection of all singleton sets { { x } : x R } { { x } : x R } {{x}:x inR}\{\{x\} : x \in \mathbb{R}\}{{x}:xR}.
    • Since R R R\mathbb{R}R is uncountable, the basis is uncountable.
    • Therefore, R R R\mathbb{R}R with the discrete topology is not second countable.

Conclusion:

  1. Every second countable space is first countable because a countable basis ensures the existence of a countable neighborhood basis for each point.
  2. The converse is false; for example, R R R\mathbb{R}R with the discrete topology is first countable but not second countable.
Q.E.D. Q.E.D. “Q.E.D.”\boxed{\text{Q.E.D.}}Q.E.D.

Question:-6(ii)

Prove that the sequence of functions in L p L p L^(p)L^pLp space has at most one limit.

Answer:

Statement:

Prove that a sequence of functions in L p L p L^(p)L^pLp space ( 1 p < 1 p < 1 <= p < oo1 \leq p < \infty1p<) can have at most one limit in the L p L p L^(p)L^pLp-norm.

Definitions:

1. L p L p L^(p)L^pLp-Space:

The L p L p L^(p)L^pLp-space consists of equivalence classes of measurable functions f : X R f : X R f:X rarrRf : X \to \mathbb{R}f:XR (or C C C\mathbb{C}C) defined on a measure space ( X , Σ , μ ) ( X , Σ , μ ) (X,Sigma,mu)(X, \Sigma, \mu)(X,Σ,μ) such that:
f p = ( X | f ( x ) | p d μ ) 1 / p < . f p = X | f ( x ) | p d μ 1 / p < . ||f||_(p)=(int _(X)|f(x)|^(p)d mu)^(1//p) < oo.\|f\|_p = \left( \int_X |f(x)|^p \, d\mu \right)^{1/p} < \infty.fp=(X|f(x)|pdμ)1/p<.

2. Convergence in L p L p L^(p)L^pLp-Norm:

A sequence of functions { f n } { f n } {f_(n)}\{f_n\}{fn} converges to f f fff in the L p L p L^(p)L^pLp-norm if:
lim n f n f p = 0. lim n f n f p = 0. lim_(n rarr oo)||f_(n)-f||_(p)=0.\lim_{n \to \infty} \|f_n – f\|_p = 0.limnfnfp=0.

3. Uniqueness of Limits:

To show uniqueness, we need to prove that if f , g L p f , g L p f,g inL^(p)f, g \in L^pf,gLp are limits of the same sequence { f n } { f n } {f_(n)}\{f_n\}{fn}, then f = g f = g f=gf = gf=g almost everywhere.

Proof:

Step 1: Assumption of Two Limits

Let f , g L p f , g L p f,g inL^(p)f, g \in L^pf,gLp be two limits of the sequence { f n } { f n } {f_(n)}\{f_n\}{fn} in L p L p L^(p)L^pLp-norm. This means:
lim n f n f p = 0 and lim n f n g p = 0. lim n f n f p = 0 and lim n f n g p = 0. lim_(n rarr oo)||f_(n)-f||_(p)=0quad”and”quadlim_(n rarr oo)||f_(n)-g||_(p)=0.\lim_{n \to \infty} \|f_n – f\|_p = 0 \quad \text{and} \quad \lim_{n \to \infty} \|f_n – g\|_p = 0.limnfnfp=0andlimnfngp=0.

Step 2: Triangle Inequality

Consider the norm f g p f g p ||f-g||_(p)\|f – g\|_pfgp. Using the triangle inequality for the L p L p L^(p)L^pLp-norm:
f g p = f f n + f n g p f f n p + f n g p . f g p = f f n + f n g p f f n p + f n g p . ||f-g||_(p)=||f-f_(n)+f_(n)-g||_(p) <= ||f-f_(n)||_(p)+||f_(n)-g||_(p).\|f – g\|_p = \|f – f_n + f_n – g\|_p \leq \|f – f_n\|_p + \|f_n – g\|_p.fgp=ffn+fngpffnp+fngp.

Step 3: Taking the Limit

As n n n rarr oon \to \inftyn, both f f n p f f n p ||f-f_(n)||_(p)\|f – f_n\|_pffnp and f n g p f n g p ||f_(n)-g||_(p)\|f_n – g\|_pfngp converge to 0 0 000 (by the assumption that f f fff and g g ggg are limits of { f n } { f n } {f_(n)}\{f_n\}{fn}). Thus:
f g p lim n f f n p + lim n f n g p = 0. f g p lim n f f n p + lim n f n g p = 0. ||f-g||_(p) <= lim_(n rarr oo)||f-f_(n)||_(p)+lim_(n rarr oo)||f_(n)-g||_(p)=0.\|f – g\|_p \leq \lim_{n \to \infty} \|f – f_n\|_p + \lim_{n \to \infty} \|f_n – g\|_p = 0.fgplimnffnp+limnfngp=0.

Step 4: Norm Zero Implies Equality Almost Everywhere

In L p L p L^(p)L^pLp-spaces, f g p = 0 f g p = 0 ||f-g||_(p)=0\|f – g\|_p = 0fgp=0 implies that f ( x ) = g ( x ) f ( x ) = g ( x ) f(x)=g(x)f(x) = g(x)f(x)=g(x) for almost all x X x X x in Xx \in XxX (i.e., f = g f = g f=gf = gf=g almost everywhere).

Conclusion:

If a sequence { f n } { f n } {f_(n)}\{f_n\}{fn} in L p L p L^(p)L^pLp converges to two functions f f fff and g g ggg in the L p L p L^(p)L^pLp-norm, then f = g f = g f=gf = gf=g almost everywhere. Therefore, the sequence { f n } { f n } {f_(n)}\{f_n\}{fn} can have at most one limit in L p L p L^(p)L^pLp-norm.
Q.E.D. Q.E.D. “Q.E.D.”\boxed{\text{Q.E.D.}}Q.E.D.

Question:-7(i)

Show that one point compactification of the set of rational numbers Q Q QQQ is not Hausdorff.

Answer:

Statement:

The one-point compactification of the set of rational numbers Q Q Q\mathbb{Q}Q is not Hausdorff.

Definitions:

1. One-Point Compactification:

Let X X XXX be a non-compact, locally compact, Hausdorff topological space. The one-point compactification X X X^(**)X^*X of X X XXX is defined as:
X = X { } , X = X { } , X^(**)=X uu{oo},X^* = X \cup \{\infty\},X=X{},
where oo\infty is an additional point, and the topology on X X X^(**)X^*X is defined as:
  • The open sets of X X X^(**)X^*X include:
    • All open sets of X X XXX,
    • Sets of the form U = X K U = X K U_( oo)=X^(**)\\KU_\infty = X^* \setminus KU=XK, where K X K X K sube XK \subseteq XKX is compact in X X XXX.

2. Hausdorff Space:

A topological space Y Y YYY is Hausdorff if for any two distinct points y 1 , y 2 Y y 1 , y 2 Y y_(1),y_(2)in Yy_1, y_2 \in Yy1,y2Y, there exist disjoint open sets U 1 , U 2 U 1 , U 2 U_(1),U_(2)U_1, U_2U1,U2 such that y 1 U 1 y 1 U 1 y_(1)inU_(1)y_1 \in U_1y1U1 and y 2 U 2 y 2 U 2 y_(2)inU_(2)y_2 \in U_2y2U2.

Proof:

Step 1: The Rational Numbers Q Q Q\mathbb{Q}Q

The set of rational numbers Q Q Q\mathbb{Q}Q with the usual topology induced from R R R\mathbb{R}R is:
  • Locally compact: Every point q Q q Q q inQq \in \mathbb{Q}qQ has a compact neighborhood (e.g., [ q ϵ , q + ϵ ] Q [ q ϵ , q + ϵ ] Q [q-epsilon,q+epsilon]nnQ[q – \epsilon, q + \epsilon] \cap \mathbb{Q}[qϵ,q+ϵ]Q).
  • Not compact: The space Q Q Q\mathbb{Q}Q is not compact because it is not closed in R R R\mathbb{R}R, and sequences like q n = 1 + 1 / n q n = 1 + 1 / n q_(n)=1+1//nq_n = 1 + 1/nqn=1+1/n do not have convergent subsequences in Q Q Q\mathbb{Q}Q.
Thus, the one-point compactification Q = Q { } Q = Q { } Q^(**)=Quu{oo}\mathbb{Q}^* = \mathbb{Q} \cup \{\infty\}Q=Q{} is well-defined.

Step 2: Neighborhoods in Q Q Q^(**)\mathbb{Q}^*Q

  1. In Q Q Q\mathbb{Q}Q, the open sets are the usual open sets inherited from R R R\mathbb{R}R.
  2. For the point oo\infty, open neighborhoods are of the form: U = Q K , U = Q K , U_( oo)=Q^(**)\\K,U_\infty = \mathbb{Q}^* \setminus K,U=QK,where K Q K Q K subeQK \subseteq \mathbb{Q}KQ is compact.
Since Q Q Q\mathbb{Q}Q is not compact, any compact subset K K KKK of Q Q Q\mathbb{Q}Q is a finite union of closed and bounded subsets of Q Q Q\mathbb{Q}Q. Therefore, U U U_( oo)U_\inftyU is "large" in Q Q Q\mathbb{Q}Q, and neighborhoods of oo\infty will always include all but a compact subset of Q Q Q\mathbb{Q}Q.

Step 3: Hausdorff Property and Failure

To show Q Q Q^(**)\mathbb{Q}^*Q is not Hausdorff, we need to find two points x , y Q x , y Q x,y inQ^(**)x, y \in \mathbb{Q}^*x,yQ such that no disjoint open sets separate x x xxx and y y yyy.
  1. Let x Q x Q x inQx \in \mathbb{Q}xQ and oo\infty. Suppose there exist disjoint open sets U U UUU and V V VVV such that:
    • x U x U x in Ux \in UxU,
    • V V oo in V\infty \in VV.
  2. By definition of neighborhoods of oo\infty, V = U = Q K V = U = Q K V=U_( oo)=Q^(**)\\KV = U_\infty = \mathbb{Q}^* \setminus KV=U=QK for some compact K Q K Q K subeQK \subseteq \mathbb{Q}KQ. Thus, K K KKK is closed and bounded in Q Q Q\mathbb{Q}Q.
  3. Since K K KKK is compact, it contains only finitely many points of Q Q Q\mathbb{Q}Q. However, Q Q Q\mathbb{Q}Q is dense in R R R\mathbb{R}R, so any open set U Q U Q U subeQU \subseteq \mathbb{Q}UQ containing x x xxx will intersect K K KKK. This implies U V U V U nn V!=O/U \cap V \neq \emptysetUV, contradicting the assumption that U U UUU and V V VVV are disjoint.

Conclusion:

The one-point compactification Q = Q { } Q = Q { } Q^(**)=Quu{oo}\mathbb{Q}^* = \mathbb{Q} \cup \{\infty\}Q=Q{} fails the Hausdorff condition because neighborhoods of oo\infty cannot be disjoint from neighborhoods of points in Q Q Q\mathbb{Q}Q. Therefore:
The one-point compactification of Q is not Hausdorff. The one-point compactification of Q is not Hausdorff. “The one-point compactification of “Q” is not Hausdorff.”\boxed{\text{The one-point compactification of \( \mathbb{Q} \) is not Hausdorff.}}The one-point compactification of Q is not Hausdorff.

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:

  1. Second Countable Space:
    A topological space X X XXX is second countable if it has a countable basis B B B\mathcal{B}B, i.e., a countable collection of open sets such that every open set in X X XXX can be expressed as a union of sets in B B B\mathcal{B}B.
  2. Regular Space:
    A topological space X X XXX is regular if:
    • X X XXX is T 1 T 1 T_(1)T_1T1, meaning every singleton set { x } { x } {x}\{x\}{x} is closed, and
    • For every closed set F X F X F sube XF \subseteq XFX and a point p F p F p!in Fp \notin FpF, there exist disjoint open sets U U UUU and V V VVV such that: F U and p V . F U and p V . F sube U quad”and”quad p in V.F \subseteq U \quad \text{and} \quad p \in V.FUandpV.
  3. Normal Space:
    A topological space X X XXX is normal if:
    • X X XXX is T 1 T 1 T_(1)T_1T1, and
    • For any two disjoint closed sets F 1 , F 2 X F 1 , F 2 X F_(1),F_(2)sube XF_1, F_2 \subseteq XF1,F2X, there exist disjoint open sets U 1 U 1 U_(1)U_1U1 and U 2 U 2 U_(2)U_2U2 such that: F 1 U 1 and F 2 U 2 . F 1 U 1 and F 2 U 2 . F_(1)subeU_(1)quad”and”quadF_(2)subeU_(2).F_1 \subseteq U_1 \quad \text{and} \quad F_2 \subseteq U_2.F1U1andF2U2.

Proof:

Given:

X X XXX is a second countable, regular topological space. We need to show X X XXX is normal.

Step 1: Second Countability and Regularity

  • Second countability implies that X X XXX has a countable basis B B B\mathcal{B}B.
  • Regularity means for any closed set F X F X F sube XF \subseteq XFX and p F p F p!in Fp \notin FpF, there exist disjoint open sets separating F F FFF and p p ppp.

Step 2: Let F 1 F 1 F_(1)F_1F1 and F 2 F 2 F_(2)F_2F2 be Two Disjoint Closed Sets

We need to find disjoint open sets U 1 U 1 U_(1)U_1U1 and U 2 U 2 U_(2)U_2U2 such that:
F 1 U 1 and F 2 U 2 . F 1 U 1 and F 2 U 2 . F_(1)subeU_(1)quad”and”quadF_(2)subeU_(2).F_1 \subseteq U_1 \quad \text{and} \quad F_2 \subseteq U_2.F1U1andF2U2.

Step 3: Use Regularity to Separate Points

Fix a point x F 1 x F 1 x inF_(1)x \in F_1xF1. Since F 1 F 1 F_(1)F_1F1 and F 2 F 2 F_(2)F_2F2 are disjoint and closed, x F 2 x F 2 x!inF_(2)x \notin F_2xF2. By the regularity of X X XXX, there exist disjoint open sets U x U x U_(x)U_xUx and V x V x V_(x)V_xVx such that:
x U x and F 2 V x . x U x and F 2 V x . x inU_(x)quad”and”quadF_(2)subeV_(x).x \in U_x \quad \text{and} \quad F_2 \subseteq V_x.xUxandF2Vx.

Step 4: Cover F 1 F 1 F_(1)F_1F1 Using B B B\mathcal{B}B

For each x F 1 x F 1 x inF_(1)x \in F_1xF1, choose U x U x U_(x)U_xUx as above. Since F 1 F 1 F_(1)F_1F1 is closed and B B B\mathcal{B}B is a countable basis, we can cover F 1 F 1 F_(1)F_1F1 by a countable subcollection of the sets { U x } x F 1 { U x } x F 1 {U_(x)}_(x inF_(1))\{U_x\}_{x \in F_1}{Ux}xF1. Let this subcollection be { U x 1 , U x 2 , } { U x 1 , U x 2 , } {U_(x_(1)),U_(x_(2)),dots}\{U_{x_1}, U_{x_2}, \ldots\}{Ux1,Ux2,}.
Define:
U 1 = i = 1 U x i . U 1 = i = 1 U x i . U_(1)=uuu_(i=1)^(oo)U_(x_(i)).U_1 = \bigcup_{i=1}^\infty U_{x_i}.U1=i=1Uxi.
Clearly:
F 1 U 1 . F 1 U 1 . F_(1)subeU_(1).F_1 \subseteq U_1.F1U1.

Step 5: Ensure U 1 U 1 U_(1)U_1U1 and U 2 U 2 U_(2)U_2U2 are Disjoint

For each U x U x U_(x)U_xUx, the corresponding V x V x V_(x)V_xVx separates x x xxx from F 2 F 2 F_(2)F_2F2. Since F 2 x F 1 V x F 2 x F 1 V x F_(2)subennn_(x inF_(1))V_(x)F_2 \subseteq \bigcap_{x \in F_1} V_xF2xF1Vx, define:
U 2 = x F 1 V x . U 2 = x F 1 V x . U_(2)=nnn_(x inF_(1))V_(x).U_2 = \bigcap_{x \in F_1} V_x.U2=xF1Vx.
Thus, U 1 U 1 U_(1)U_1U1 and U 2 U 2 U_(2)U_2U2 are disjoint open sets satisfying:
F 1 U 1 and F 2 U 2 . F 1 U 1 and F 2 U 2 . F_(1)subeU_(1)quad”and”quadF_(2)subeU_(2).F_1 \subseteq U_1 \quad \text{and} \quad F_2 \subseteq U_2.F1U1andF2U2.

Step 6: Conclusion

We have shown that for any two disjoint closed sets F 1 , F 2 F 1 , F 2 F_(1),F_(2)F_1, F_2F1,F2 in X X XXX, there exist disjoint open sets U 1 U 1 U_(1)U_1U1 and U 2 U 2 U_(2)U_2U2 such that F 1 U 1 F 1 U 1 F_(1)subeU_(1)F_1 \subseteq U_1F1U1 and F 2 U 2 F 2 U 2 F_(2)subeU_(2)F_2 \subseteq U_2F2U2. This proves X X XXX is normal.
Q.E.D. Q.E.D. “Q.E.D.”\boxed{\text{Q.E.D.}}Q.E.D.

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