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Algebra of the Space of Continuous Functions 📂Analysis

Algebra of the Space of Continuous Functions

Definitions1

  1. A set AA that satisfies the following three conditions is called the algebra of C(X)C(X):
    • (i): AC(X)\emptyset \ne A \subset C(X)
    • (ii): f,gA    (f+g),fgAf,g \in A \implies (f+g) , fg \in A
    • (iii): fA,cR    cfAf \in A , c \in \mathbb{R} \implies cf \in A
  2. Let’s say XX is for metric space AC(X)A \subset C(X). If every sequence {fnA:nN}\left\{ f_{n} \in A : n \in \mathbb{N} \right\} of AA for some fAf \in A satisfies nn \to \infty, then AA is said to be uniformly closed.

Theorem

If XX is a compact metric space and AA includes constant functions and is a uniformly closed algebra of C(X)C(X), then the following holds: f,gA    (fg),(fg)A f,g \in A \implies (f \land g), ( f \lor g ) \in A


  • \land and \lor mean the following for f,gC(X)f,g \in C(X) and xXx \in X: (fg)(x):=min{f(x),g(x)}(fg)(x):=max{f(x),g(x)} \begin{align*} (f \land g) (x) :=& \min \left\{ f(x) , g(x) \right\} \\ (f \lor g) (x) :=& \max \left\{ f(x) , g(x) \right\} \end{align*}

Proof

Strategy: While the above corollary might seem like a simple fact, the proof is anything but simple. (fg)(f \land g) and (fg)(f \lor g) can be expressed as combinations of simpler functions. Among those simpler functions, there is f|f|, and showing that it is fA    fAf \in A \implies |f| \in A presents a challenge. A sequence {Mgn(x)}nN\left\{ M g_{n} (x) \right\}_{n \in \mathbb{N}} that converges to f|f| is directly constructed through a binomial series trick. Then, the proof concludes by the condition of being uniformly closed. This corollary can be usefully employed to prove the Stone-Weierstrass theorem.


  • Part 1. Algebra

    Since AA is an algebra, gA,0R    0AgA,(1)R    (g)Af,(g)A    (fg)A \begin{align*} g \in A, 0 \in \mathbb{R} \implies & 0 \in A \\ g \in A, (-1) \in \mathbb{R} \implies & (-g) \in A \\ f , (-g) \in A \implies & (f - g ) \in A \end{align*} . (fg)(x)(f \land g) (x) and (fg)(x)(f \lor g) (x) can respectively be expressed as combinations of: (fg)(x)=min{f(x),g(x)}=12[(f+g)(x)(fg)(x)](fg)(x)=max{f(x),g(x)}=12[(f+g)(x)+(fg)(x)] \begin{align*} (f \land g) (x) = \min \left\{ f(x) , g(x) \right\} =& {{1} \over {2}} \left[ (f+g) (x) - \left| (f - g)(x) \right| \right] \\ (f \lor g) (x) = \max \left\{ f(x) , g(x) \right\} =& {{1} \over {2}} \left[ (f+g) (x) + \left| (f - g)(x) \right| \right] \end{align*} and (f+g)(f + g) and fg| f - g |. Once again, since AA is an algebra, and given that (f+g)A(f + g ) \in A and therefore (fg)A( f - g ) \in A, it suffices to show fA    fAf \in A \implies | f | \in A. If f=0| f | = 0 is the case, obviously f=0A| f | = 0 \in A, so only consider the case of M:=f>0M := | f | > 0.

  • Part 2. ϵ>0,NN:nN    Pn(t)t<ε\forall \epsilon> 0 , \exists N \in \mathbb{N} : n \ge N \implies \left| P_{n} (t) - |t| \right| < \varepsilon

    Binomial Series : If x<1|x| < 1, then for αC\alpha \in \mathbb{C}, (1+x)α=k=0(αk)xk (1 + x )^{\alpha} = \sum_{k=0}^{\infty} \binom{\alpha}{k} x^{k}

    t=(1(1t2))1/2=112(1t2)124(1t2)2k=3135(2k3)246(2k)(1t2)k \begin{align*} \displaystyle | t | =& \left( 1 - \left( 1- t^2 \right) \right)^{1/2} \\ =& 1 - {{1} \over {2}} \left( 1- t^2 \right) - {{1} \over {2 \cdot 4}} \left( 1- t^2 \right)^2 - \sum_{k=3}^{\infty} {{ 1 \cdot 3 \cdot 5 \cdots (2k-3 ) } \over { 2 \cdot 4 \cdot 6 \cdots (2k) }} \left( 1- t^2 \right)^{k} \end{align*}

    uniformly converges on (2,2)( -\sqrt{2} , \sqrt{2} ), thus it also converges uniformly on [1,1][-1,1]. Let’s define PnP_{n} according to nNn \in \mathbb{N} as the following union.

    Pn(t):=112(1t2)124(1t2)2k=3n135(2k3)246(2k)(1t2)k P_{n} (t) := 1 - {{1} \over {2}} \left( 1- t^2 \right) - {{1} \over {2 \cdot 4}} \left( 1- t^2 \right)^2 - \sum_{k=3}^{n} {{ 1 \cdot 3 \cdot 5 \cdots (2k-3 ) } \over { 2 \cdot 4 \cdot 6 \cdots (2k) }} \left( 1- t^2 \right)^{k}

    Then, for any ε>0\varepsilon > 0 and t[1,1]t \in [-1 , 1 ], there exists NNN \in \mathbb{N} that satisfies nN    Pn(t)t<εn \ge N \implies \left| P_{n} (t) - |t| \right| < \varepsilon.

  • Part 3. fA    fAf \in A \implies | f | \in A

    For xXx \in X, let’s define gn(x)g_{n} (x) as

    gn(x):=Pn(f(x)M) g_{n} (x ) : = P_{n} \left( {{ f(x) } \over {M}} \right)

    Since AA includes constant functions as an algebra, for all cRc \in \mathbb{R}, there exists a corresponding constant function c(x)=cc(x) = c. Since Pn(f(x)M)\displaystyle P_{n} \left( {{ f(x) } \over {M}} \right) is expressed as a linear combination of constant functions and (f(x)M)2k\displaystyle \left( {{f(x)} \over {M}} \right)^{2k}, gnAg_{n} \in A is ensured. Assuming M=f>0M = | f | > 0 from Part 1, setting tt as t:=f(x)M\displaystyle t := {{ f(x) } \over { M }}, we have t[1,1]t \in [-1,1], and according to Part 2,

    gn(x)f(x)M=Pn(f(x)M)f(x)M=Pn(t)t<ε \left| g_{n} (x) - \left| {{f(x)} \over {M}} \right| \right| = \left| P_{n} \left( {{ f(x) } \over {M}} \right) - \left| {{f(x)} \over {M}} \right|\right| = \left| P_{n} (t) - |t| \right| < \varepsilon

    there exists NN satisfying. Multiplying both ends by MM gives

    Mgn(x)f(x)<Mε \left| M g_{n} (x) - \left| f(x) \right| \right| < M \varepsilon

    thus when xXx \in X and nn \to \infty, Mgnf0| M g_{n} - |f| | \to 0, and since AA is uniformly closed,

    fA |f| \in A


  1. William R. Wade, An Introduction to Analysis (4th Edition, 2010), p377-378 ↩︎