13.1 Vector Lattices
Definition 13.1.1 (Ordered Vector Space). Let $E$ be a vector space over $\real$ and $\le$ be a partial order on $E$, then $(E, \le)$ is a ordered vector space if
For any $x, y, z \in E$ with $x \le y$, $x + z \le y + z$.
For any $x, y \in E$ and $\lambda > 0$, $x \le y$ implies that $\lambda x \le \lambda y$.
Proposition 13.1.2. Let $(E, \le)$ be an ordered vector space and $A, B \subset E$ such that $\sup(A)$ and $\sup (B)$ exist, then
$\sup(A + B) = \sup(A) + \sup(B)$.
$\sup(A) = -\inf (-A)$
Proof. (1): For any $a \in A$ and $b \in B$, $a + b \le \sup(A) + \sup(B)$ by (LO1). Let $c \in E$ such that $c \ge a + b$ for all $a \in A$ and $b \in B$, then $c \ge a + \sup(B)$ for all $a \in A$, so $c \ge \sup(A) + \sup(B)$. Therefore $\sup(A) + \sup(B) = \sup(A + B)$.
(2): For any $a \in A$, $\sup(A) \ge a = -(-a)$, so $-\sup(A) \le \inf(-A)$, and $\sup(A) \ge -\inf(-A)$. On the other hand, for any $a \in A$, $-\inf(-A) \ge a$. Therefore $\sup(A) \le -\inf(-A)$.$\square$
Definition 13.1.3 (Interval). Let $(E, \le)$ be an ordered vector space and $x, y \in E$, then
is the order interval with endpoints $x$ and $y$.
Definition 13.1.4 (Order Bounded). Let $(E, \le)$ be an ordered vector space and $A \subset E$, then $A$ is order bounded if there exists $x, y \in E$ such that $A \subset [x, y]$.
Definition 13.1.5 (Order Complete). Let $(E, \le)$ be an ordered vector space, then $E$ is order complete if for any order bounded set $A \subset E$, $\sup (A)$ and $\inf (A)$ exist.
Definition 13.1.6 (Order Bounded Dual). Let $(E, \le)$ be an ordered vector space, then the space $E^{b}$ consisting of all linear functionals on $E$ that are bounded on order bounded sets is the order bounded dual of $E$.
Definition 13.1.7 (Order Dual). Let $(E, \le)$ be an ordered vector space and $\Phi^{+} \in \hom(E; \real)$, then $\Phi^{+}$ is positive if for any $x \in E$ with $x \ge 0$, $\Phi^{+}(x) \ge 0$. The subspace $E^{+} \subset \hom(E; \real)$ generated by the positive linear functionals on $E$ is the order dual of $E$.
Definition 13.1.8 (Vector Lattice). Let $(E, \le)$ be an ordered vector space, then $E$ is a vector lattice if for any $x, y \in E$, $x \vee y = \sup\bracs{x, y}$ and $x \wedge y = \inf\bracs{x, y}$ exist.
Definition 13.1.9 (Absolute Value). Let $(E, \le)$ be a vector lattice and $x \in E$, then $|x| = x \vee -x$ is the absolute value of $x$.
Lemma 13.1.10. Let $(E, \le)$ be a vector lattice and $x \in E$, then $|x| \ge 0$.
Proof. For any $x \in E$,
Definition 13.1.11 (Disjoint). Let $(E, \le)$ be a vector lattice and $x, y \in E$, then $x$ and $y$ are disjoint, denoted $x \perp y$, if $|x| \wedge |y| = 0$.
Proposition 13.1.12. Let $(E, \le)$ be a vector lattice, then:
For any $x, y \in E$,
\[x + y = x \vee y + x \wedge y\]Let $x \in E$, $x^{+} = x \vee 0 \ge 0$, and $x^{-} = -(x \wedge 0) \ge 0$, then $x = x^{+} - x^{-}$ and $|x| = x^{+} + x^{-}$. Moreover, $(x^{+}, x^{-})$ are the unique disjoint non-negative elements of $E$ such that $x = x^{+} - x^{-}$.
For any $x, y \in E$ and $\lambda \in \real$,
$|\lambda x| = |\lambda| \cdot |x|$
$|x + y| \le |x| + |y|$.
Finally, for any $x, y \in E$ with $x, y \ge 0$,
$[0, x] + [0, y] = [0, x + y]$.
Proof. (1): By Proposition 13.1.2,
(2): By (1),
By Proposition 13.1.2 and Lemma 13.1.10,
and
Since $x^{+}, x^{-} \ge 0$, $|x^{+}| = x^{+}$ and $|x^{-}| = x^{-}$, so by (1),
so $x^{+} \perp x^{-}$.
Now, let $y, z \in E$ with $y, z \ge 0$ such that $x = y - z$, then
and $x^{-} \le z$. If $y \perp z$, then $y - x^{+} \perp z - x^{-}$. Since $y - x^{+} = z - x^{-}$, $y - x^{+} = z - x^{-} = 0$, so $y = x^{+}$ and $z = x^{-}$.
(3): For any $\lambda > 0$, by (LO2),
(4): For any $x, y \in E$, by Proposition 13.1.2,
Likewise, $x^{-} + y^{-} \ge (x + y)^{-}$. Thus
(5): Let $x, y \in E$ with $x, y \ge 0$, then $[0, x] + [0, y] \subset [0, x + y]$. For any $z \in [0, x + y]$, let $u = z \wedge x$ and $v = z - u$, then
Lemma 13.1.13. Let $(E, \le)$ be a vector lattice, $C = \bracs{x \in E|x \ge 0}$ and $\phi: C \to [0, \infty)$ such that:
For any $x \in C$ and $\lambda \in \real$ with $\lambda \ge 0$, $\phi(\lambda x) = \lambda \phi(x)$.
For any $x, y \in C$, $\phi(x + y) = \phi(x) + \phi(y)$.
then the mapping
is a positive linear functional on $E$.
Proof. For any $\lambda \in \real$ with $\lambda \ge 0$,
Likewise, if $\lambda < 0$, then
For any $x, y \in E$, let $z = x + y$, then $z = z^{+} - z^{-} = x^{+} + y^{+} - x^{-} - y^{-}$. Thus
Proposition 13.1.14. Let $(E, \le)$ be an ordered vector space. If for any $x, y \in E$ with $x, y \ge 0$, $[0, x] + [0, y] = [0, x + y]$, then:
$E^{b} = E^{+}$.
The order bound dual $E^{b}$ equipped with its canonical ordering is a vector lattice.
$E^{b}$ is order complete.
For any $\phi \in E^{b}$ and $x \in E$ with $x \ge 0$,
\[|\phi|(x) = \sup\bracs{\phi(y)|y \in E, |y| \le x}\]
Proof. (1): Let $C = \bracs{x \in E|x \ge 0}$, $\Phi^{+} \in E^{b}$, and
then for any $x, y \in C$ and $\lambda \in \real$ with $\lambda \ge 0$,
Let
then $\Phi$ is a positive linear functional by Lemma 13.1.13.
For any $x \in C$, $\Phi(x) \ge \phi(x)$, so $\Phi \ge \phi$. On the other hand, let $\psi \in \hom(E; \real)$ such that $\psi \ge 0$ and $\psi \ge \phi$, then for each $x \in C$, $\psi(x) \ge \sup(\phi([0, x]))$. Therefore $\Phi = 0 \vee \phi$.
Since $0 \wedge \phi = -(0 \vee -\phi)$, $\phi = (0 \vee \phi) - (0 \vee -\phi)$ is a sum of two positive linear functionals, so $E^{b} = E^{+}$.
(2): For any $x, y \in E^{b}$, $x \wedge y = (x - y) \wedge 0 + y$ and $x \vee y = (x - y) \vee 0 + y$, so $E^{b}$ is a lattice.
(3): Let $A \subset E^{b}$ be order bounded, then since $E^{b}$ is a lattice, assume without loss of generality that $A$ is upward-directed under the canonical ordering. Let
then for any $\lambda \ge 0$ and $x \in C$, $\phi(\lambda x) = \lambda \phi(x)$. Let $x, y \in C$, then for any $f \in A$,
As this holds for all $f \in A$, $\phi(x + y) \le \phi(x) + \phi(y)$. On the other hand, for any $f, g \in A$, there exists $h \in A$ such that
Since such an $h \in A$ exists for all $f, g \in A$, $\phi(x + y) \ge \phi(x) + \phi(y)$.
By Lemma 13.1.13, the mapping
is a positive linear functional on $E$. By definition $\Phi \ge f$ for all $f \in A$. If $\psi \in \hom(E; \real)$ is a linear functional such that $\psi \ge f$ for all $f \in A$, then for any $x \in C$, $\psi(x) \ge \sup_{f \in A}f(x)$. Therefore $\Phi = \sup(A)$, and $E^{b}$ is order complete.
(3): Let $\phi \in E^{b}$ and $x \in E$ with $x \ge 0$, then by (1),
For any $u, v \in [0, x]$, $|u - v| \le x$, so
On the other hand, for any $y \in E$ with $|y| \le x$, $y^{+}, y^{-} \le x$, so
Therefore