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Linear Functionals

Let $ X$ be a vector space over $ \mathbb{F}$. Call $ M$, a linear subspace, a hyperplane if $ \dim(X/M) = 1$.

Example:
If $ f: X \rightarrow \mathbb{F}$, then $ \ker F$ is a hyperplane (if $ f \neq 0$). In fact, $ f$ induces an isomorphism of $ \mathbb{F}$ and $ X/M$.

Properties

  1. Every hyperplane arises in this way. If $ \dim(X/M) = 1$, then there is an isomorphism

    $\displaystyle T : X/M \rightarrow \mathbb{F}$

    If $ Q:X \rightarrow X/M$ is the quotient map, then $ T \circ Q$ is a bounded linear functional with kernel equal to $ M$.
  2. Two linear functionals have the same kernel if and only if they are (nonzero) multiples of each other. In particular, every functional with kernel $ M$ is a scalar multiple of $ T \circ Q$.

    Proof. Suppose $ f,g : X \rightarrow \mathbb{F}$, $ \ker f = \ker g$. Pick $ x_0 \in X$ such that $ f(x_0) = 1$, So $ g(x_0) \neq 0$. For $ x \in X$, let $ \alpha = f(x)$ and then $ y = x - \alpha x_0 \in \ker F$. So $ 0 = g(y) = g(x) - f(x)g(x)$. Thus,

    $\displaystyle g = (g(x_0)) f $

    $ \qedsymbol$

  3. Every hyperplane is either dense or closed.

    Proof. If $ M \neq \bar M$, then pick $ y \in \bar M \setminus M$. Since $ \dim(X/M) = 1$, $ y+M \neq M$. So, given $ x + M \in X/M$, there is $ \alpha \in \mathbb{F}$ such that $ x+M = \alpha(y+M)$. Thus, $ x = \alpha y + M \in \bar M$. So, $ \bar M = X$. $ \qedsymbol$

    Example: of a not closed hyperplane. Let $ X = c_0$, the space of sequences converging to 0 with the infinity norm. Let

    $\displaystyle x = (1, \frac12, \frac13, \ldots) $

    and let $ e_1, e_2, \ldots$ be the usual basis. Since $ \{ x_1, e_1, e_2, \ldots \}$ is a linearly independent set. There is a a $ B \subset c_0$ so that $ \{ x, e_1, e_2, \ldots \} \cup B$ is a linear basis for $ c_0$. Thus, for $ y \in c_0$, we can write $ y$ as

    $\displaystyle \alpha_0 x + \alpha_1 e_1 + \alpha_2 e_2 + \cdots + \sum_{b \in B} \alpha_b b $

    with at most finitely many indices nonzero.
    Define a map $ f : c_0 \rightarrow \mathbb{F}$ by $ f(y) = \alpha_0$. Then this is a linear map, so $ \ker f$ is a hyperplane. Notice $ x \notin \ker f$ as $ f(x) = 1$. But $ e_i \in \ker f$ for $ i = 1,2, \ldots$. Further, $ x$ is in the closed span of the $ e_i$, so $ x \in \overline{ker f} \setminus \ker f$.

Theorem 10.0.1   For $ x$ a normed space, $ f: X \rightarrow \mathbb{F}$ is continuous if and only if $ \ker f$ is closed.

Proof. For the forward direction, $ \ker f = f^{-1}(\{0\})$ is closed if $ f$ is continuous.
If $ \ker f$ is closed, then $ Q:X \rightarrow X/\ker f$ is continuous and let $ T:X / \ker f \rightarrow \mathbb{F}$ be an isomorphism. Then $ T \circ Q$ is continuous and, by property $ 2$, $ f$ is a scalar multiple of $ T \circ Q$. $ \qedsymbol$

Definition 10.0.2   For $ X$ a normed space, the dual space of $ X$, denoted $ X^*$ (or $ X^\char93 $) is the vector space of all bounded linear functionals, equipped with the norm $ \Vert f\Vert = \sup_{\Vert x\Vert \leq 1} \vert f(x)\vert$. That is, $ X^* = B(X,\mathbb{F})$.

Proposition 10.0.3   For $ X$ a normed vector space, $ X^*$ is a Banach space.

Examples of Dual Spaces:

  1. Riesz Representation Theorem for $ L^p$, $ 1 < p < \infty$. As usual, $ L(X,\Omega, \mu)$ is a measure space. For every $ F \in L^p(X)^*$, there is a unique $ g \in L^q(X)$ (where $ \frac1p + \frac1q = 1$) so that

    $\displaystyle F(f) = \int_X fg d\mu, \forall f \in L^p(X) $

    moreover $ \Vert F\Vert _{(L^p)^*} = \Vert g\Vert _{L^q}$.
  2. If $ (X,\Omega,\mu)$ is a $ \sigma$-finite measure space, then for every $ F \in L^1(X)^*$, there is a unique $ g \in L^\infty(X)$ so that

    $\displaystyle F(f) = \int_X fg d\mu, \, \forall f \in L^1(X) $

    Moreover, $ \Vert F\Vert _{(L^1)^*} = \Vert g\Vert _{L^\infty}$
  3. $ (L^\infty)^*$ is not $ L^1$.
  4. Let $ X$ be a locally compact space. For every $ F \in (C_0(X))^*$, there is a regular Borel measure $ \mu$ on $ X$ so that

    $\displaystyle F(f) = \int_X f d\mu, \, \forall f \in C_0(X) $

    Define for such a $ \mu$

    $\displaystyle \Vert\mu\Vert = \sup_ \{ \sum_{i=1}^n \vert\mu(S_1)\vert : S_i \in \Omega, \bigcup S_i = X, \mu(S_i \cup S_j) = 0, i \neq j \} $

    Then $ \Vert F\Vert _{C_0(X)^*} = \Vert\mu\Vert$.
Important Special Cases:
  1. $ (c_0)^* = \ell^1$
  2. $ (\ell^1)^* = \ell^\infty$
  3. $ (\ell^p)^* = \ell^q$, $ \frac1p + \frac1q = 1$.

Q: Find a functional on $ \ell^\infty$ that does not come from an element of $ \ell^1$.
If $ x = (x_1, x_2, \ldots) \in \ell^1$, then $ F_x \in (\ell^\infty)^*$ by

$\displaystyle F_x(y_1, y_2, \ldots) = \sum_{i=1}^\infty x_i y_i $

Define $ G(y_1,y_2, \ldots) = \limsup_i y_i$. Then, $ G \in (\ell^\infty)^\char93 $, but

$\displaystyle G((0,0,\ldots, 0,1,0, \ldots) = 0 $

for all $ i \in \mathbb{N}$. But if $ F_x( 0, 0, \ldots, 0, 1, 0, \ldots ) = 0$, then $ x_i 0$. So if $ G = F_x$ then $ x = (0,0,0, \ldots )$ and $ G = F_x$ is the zero functional. But $ G(1,1,1,\ldots) = 1 \neq 0$.



Subsections
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Next: Hahn-Banach Theorem Up: Functional Analysis Notes Previous: Quotients
Brian Bockelman 2005-12-12