Question #163047

(i) Let V be a Banach space and let L ⊆ V be a linear manifold. Show that L, the closure of L, is a subspace of V .


(ii) Let H be a Hilbert space. Let B be an orthonormal set in H. Show that span B is dense in H if and only if B is an orthonormal basis.


1
Expert's answer
2021-02-24T07:04:00-0500

CORRECTED SOLUTION

1. Let L ⊆ V be a linear manifold, and Lˉ\bar L be its closure. For every xLˉx\in \bar L there exist a sequence {xn}n=1L\{x_n\}_{n=1}^{\infty}\subset L which is converges to x.

Let a,bLˉa, b\in\bar L are arbitrary vectors, a=limn+ana=\lim_{n\to+\infty}a_n, b=limn+bnb=\lim_{n\to+\infty}b_n with an,bnLa_n, b_n\in L for every n. Then an+bnLa_n+b_n\in L and limn+(an+bn)=a+b\lim_{n\to+\infty}(a_n+b_n)=a+b. Hence, a+bLˉa+ b\in\bar L .

Let λ\lambda be any scalar constant, then λanL\lambda a_n\in L for every n and limn+λan=λlimn+an=λa\lim_{n\to+\infty}\lambda a_n=\lambda\lim_{n\to+\infty} a_n =\lambda a.

Hence, λaLˉ\lambda a\in\bar L .

Since Lˉ\bar L is a closer of L, it is shown that Lˉ\bar L is a closed linear subspace of V.


2. if B is an orthonormal basis of H, then every element x in H may be approximated by a finite linear combinations of vectors from B, which are form span B. Hence, span B is dense.

Conversely, let span B is dense in H. Since B is an orthonormal set, for any xyBxy=2x\ne y \in B |x-y|=\sqrt 2 . Since H is separable, this means that B must be countable or finite. Let B={v1,v2,...}B = \{v_1, v_2, ...\} and x be an element of H. We show that the series xn=k=1nx,vkvkx_n=\sum_{k=1}^n\langle x, v_k\rangle v_k converges to x.

Let ε>0\varepsilon>0 and xk=1nλkvk<ε|x-\sum_{k=1}^n\lambda_kv_k|<\varepsilon (it is possible to find such linear combination, since span B is dense in H). Then xxn,vk=x,vkxn,vk=x,vkx,vk=0\langle x-x_n,v_k\rangle=\langle x,v_k\rangle-\langle x_n,v_k\rangle=\langle x,v_k\rangle-\langle x,v_k\rangle=0, hence xxn,xnk=1nλkvk=0\langle x-x_n,x_n-\sum_{k=1}^n\lambda_kv_k\rangle=0 and, by Pythagorean theorem, xk=1nλkvk2=(xxn)+(xnk=1nλkvk)2=xxn2+xnk=1nλkvk2|x-\sum_{k=1}^n\lambda_kv_k|^2=|(x-x_n)+(x_n-\sum_{k=1}^n\lambda_kv_k)|^2 = |x-x_n|^2+|x_n-\sum_{k=1}^n\lambda_kv_k|^2 , which implies xxn2=xk=1nλkvk2xnk=1nλkvk2<ε2|x-x_n|^2=|x-\sum_{k=1}^n\lambda_kv_k|^2-|x_n-\sum_{k=1}^n\lambda_kv_k|^2<\varepsilon^2 and xxn<ε|x-x_n|<\varepsilon.

For instance, if we take k=1nλkvk=xn1\sum_{k=1}^n\lambda_kv_k=x_{n-1} , then we have xxn2=xxn12xnxn12xxn12|x-x_n|^2=|x-x_{n-1}|^2-|x_n-x_{n-1}|^2\leq |x-x_{n-1}|^2 which implies xxnxxn1|x-x_n|\leq|x-x_{n-1}|.

Therefore, the sequense xxn|x-x_n| is monotonous, non-negative and starting from some n is lesser than ε\varepsilon. This means xnx_n converges to x and, therefore, B is an orthonormal basis in H.


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