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==Introduction==   
==Introduction==   
In the case that the space <math>X</math> is compact then all continuous functions belongs to <math> C_{0}(X)  </math> as we will show in the next section. On the other hand if the space <math>X</math> is not compact while we always have the inclusion <math> C(X) \supseteq C_{0}(X)  </math> there may be some continuous function that do not belong to <math> C_{0}(X)  </math>. Some of them may even even be bounded and still not belong to <math> C_{0}(X)  </math>, this motivates us to consider the dual space of <math> C_{0}(X)  </math> and the dual space of <math> C_{b}(X)</math>.
In the case that the space <math>X</math> is compact then all continuous functions belong to <math> C_{0}(X)  </math> as we will show in the next section. On the other hand if the space <math>X</math> is not compact, we always have the inclusion <math> C(X) \supseteq C_{0}(X)  </math>, but there may be some continuous functions that do not belong to <math> C_{0}(X)  </math>. Some of them may even even be bounded and still not belong to <math> C_{0}(X)  </math>, which motivates us to consider the dual space of <math> C_{0}(X)  </math> and the dual space of <math> C_{b}(X)</math>.


==Background and Statement==
==Background and Statement==
Let <math> C_{0}(X) = \{f \in C(X) \text{ and } \forall \epsilon >0 \text{ } \exists \text{ a compact set} K\subset X \text{ s.t. } \mid f (x) \mid < \epsilon \text{ } \forall x\in X\setminus K  \} </math> equipped with the sup norm. In other words this is the space of continuous function vanishing at infinity. Note that in the case <math>X</math> is compact we can choose <math>K=X</math> in the previous definition, since properties on the empty set are trivially true, we can conclude that <math> C(X) = C_{0}(X)  </math>. Let <math> C_{b}(X) </math> be the space of bounded continuous functions on <math> X </math> together with the sup norm, Again in the case <math>X</math> is compact we have not introduced a new space since every continuous function on a compact metric space is bounded, to see this assume on the contrary that there is a sequence <math> \{x_n\}_{n \in \N} </math> such that <math>  |f(x_n)| \rightarrow \infty</math> as <math> n \rightarrow \infty </math>. I can then extract by compactness a sub sequence <math> \{x_{n_k}\}_{i \in \N} </math> converging to a point <math> \hat{x} \in X </math>. Therefore by continuity of <math>f</math> we have <math>  |f(x_{n_k})| \rightarrow |f(\hat{x})| < \infty</math>, and this is our desired contradiction. We conclude that <math> C(X) = C_{b}(X) = C_{0}(X)  </math>.
Let <math> C_{0}(X) = \{f \in C(X) \text{ and } \forall \epsilon >0 \text{ } \exists \text{ a compact set} K\subset X \text{ s.t. } \mid f (x) \mid < \epsilon \text{ } \forall x\in X\setminus K  \} </math> equipped with the sup norm. In other words this is the space of continuous functions vanishing at infinity. When <math>X</math> is compact we can choose <math>K=X</math> in the previous definition, and since properties on the empty set are trivially true, we can conclude that <math> C(X) = C_{0}(X)  </math>. Let <math> C_{b}(X) </math> be the space of bounded continuous functions on <math> X </math> together with the sup norm. Again when <math>X</math> is compact we have not introduced a new space since every continuous function on a compact metric space is bounded, to see this assume on the contrary that there is a sequence <math> \{x_n\}_{n \in \N} </math> such that <math>  |f(x_n)| \rightarrow \infty</math> as <math> n \rightarrow \infty </math>. By compactness there is a sub-sequence <math> \{x_{n_k}\}_{i \in \N} </math> converging to a point <math> \hat{x} \in X </math>. Therefore by continuity of <math>f</math> we have <math>  |f(x_{n_k})| \rightarrow |f(\hat{x})| < \infty</math>, and this is our desired contradiction. We conclude that <math> C(X) = C_{b}(X) = C_{0}(X)  </math>.


The rest of this discussion will consider the case where <math>X</math> is not compact. We wont have the last chain of equalities but only the inequalities <math> C(X) \supset C_{b}(X) \supset C_{0}(X)  </math>
The rest of this discussion will consider the case where <math>X</math> is not compact. Rather than equality of the three spaces, we have the inclusions: <math> C(X) \supset C_{b}(X) \supset C_{0}(X)  </math>
==The case of <math> C_{0}(X)' </math> ==
==The case of <math> C_{0}(X)' </math> ==
The representation of the dual space of <math> C_{0}(X) </math> is a described by the following well known result in Functional Analysis (Riesz Representation Theorem 6.19 in Rudin <ref>Rudin, Walter. Real and Complex Analysis, 1966.</ref>):  
The representation of the dual space of <math> C_{0}(X) </math> is a described by the following well known result in Functional Analysis (Riesz Representation Theorem 6.19 in Rudin <ref>Rudin, Walter. Real and Complex Analysis, 1966.</ref>):  


Let <math> X </math> be a locally compact Hausdorff space, for any bounded linear function <math> \phi </math>, i.e. an element of the dual space <math> C_{0}(X)' </math>, there is a unique complex Borel measure <math> \mu </math> such that the following holds:
Let <math> X </math> be a locally compact Hausdorff space For any bounded linear function <math> \phi </math>, i.e. an element of the dual space <math> C_{0}(X)' </math>, there is a unique complex Borel measure <math> \mu </math> such that the following holds:


:<math> <\phi, f > = \int_{X} f d \mu, \text{ for every }  f \in C_{0}(X) </math>.
:<math> <\phi, f > = \int_{X} f d \mu, \text{ for every }  f \in C_{0}(X) </math>.
This allows us to identify <math> C_{0}(X)' </math> with <math> \mathcal{M}(X) </math>, space of complex Borel measures. Moreover we can endow <math> C_{0}(X)' </math> with the total variation norm: <math> \| \phi \| = |\mu|(X)  </math>.  
This allows us to identify <math> C_{0}(X)' </math> with <math> \mathcal{M}(X) </math>, the space of complex Borel measures. Moreover we can endow <math> C_{0}(X)' </math> with the total variation norm: <math> \| \phi \| = |\mu|(X)  </math>.  


==The case of <math> C_{b}(X)' </math> ==
==The case of <math> C_{b}(X)' </math> ==
To descrive the dual space of <math> C_{b}(X) </math>, I will focus my attention to only one property of functions which is the behavior at infinity, Exercise 1.23 of <ref>Villani, Cedric.  Topics In Optimal Transportation. American Mathematical Soc., 2003.</ref>. First we need a preliminary result: <math> C_{0}(X) </math> is a closed (vector) subspace of <math> C_{b}(X) </math>. In other words <math> C_{0}(X) </math> contains all its limit points. Let <math> f_n(x) </math> be a convergent sequence in <math> C_{0}(X)' </math>, <math> f_n(x) </math> are continuous functions vanishing at infinity and let <math> f(x) </math> their limit. f is continuous since the uniform norm we are using provides uniform convergence. It remains to show that such limit <math> f(x) </math> vanishes at infinity: let <math> n \in \N </math> be such that <math> \|f - f_n\|_\infty <\epsilon/2 </math>, now since each <math> f_n(x) </math> vanishes at infinity, we can find <math> K_n \subset X </math> such that <math> |f_n(x)|< \epsilon/2 </math> for any <math> x\in X \setminus K_n </math>. Then we can conclude by triangle inequality that
To describe the dual space of <math> C_{b}(X) </math>, we will focus on the behavior of functions at infinity, as in Exercise 1.23 of <ref>Villani, Cedric.  Topics In Optimal Transportation. American Mathematical Soc., 2003.</ref>. We first need a preliminary result: <math> C_{0}(X) </math> is a closed (vector) subspace of <math> C_{b}(X) </math>. In other words, <math> C_{0}(X) </math> contains all its limit points. Let <math> f_n(x) </math> be a convergent sequence in <math> C_{0}(X)' </math>, where <math> f_n(x) </math> are continuous functions vanishing at infinity and let <math> f(x) ne </math> their limit then f is continuous since the uniform norm we are using provides uniform convergence. It remains to show that the limit <math> f(x) </math> vanishes at infinity: let <math> n \in \N </math> be such that <math> \|f - f_n\|_\infty <\epsilon/2 </math>.Now since each <math> f_n(x) </math> vanishes at infinity, we can find <math> K_n \subset X </math> such that <math> |f_n(x)|< \epsilon/2 </math> for any <math> x\in X \setminus K_n </math>. Then we can conclude by the triangle inequality that


:<math>  |f(x)|  \leq |f(x) - f_n(x)| + |f_n(x)| < \epsilon </math>,
:<math>  |f(x)|  \leq |f(x) - f_n(x)| + |f_n(x)| < \epsilon </math>.
That is, <math> f(x) \in C_{0}(X) </math>. This proved <math> C_{0}(X) </math> is a closed subspace of <math> C_{b}(X) </math>. I now need to carefully specify the local property at infinity for <math> C_{b}(X) </math>.
That is, <math> f(x) \in C_{0}(X) </math>. This proves <math> C_{0}(X) </math> is a closed subspace of <math> C_{b}(X) </math>. We may now carefully specify the local property at infinity for <math> C_{b}(X) </math>.


We say that a function <math> u \in C_{b}(X) </math> admits a limit at infinity <math> u(\infty) </math> if for any <math> \epsilon >0  </math> there exists a compact <math> K_{\epsilon} \sub X </math> such that if <math> x \notin K_{\epsilon} </math> implies <math> |u(x) - u(\infty)|\leq \epsilon </math>. We can see this operation as a linear function 'limit at infinity'. Thanks to Hahn-Banach we can build a continuous extension of it for all <math> C_{b}(X) </math>. This is another spectacular consequence of Axiom of Choice (Hahn-Banach theorem [https://en.wikipedia.org/wiki/Hahn%E2%80%93Banach_theorem] in this case). Intuitively we can partition the space <math> C_{b}(X) </math> into equivalence classes of the equivalence relation of having the same limit at infinity. Then thanks to the axiom of choice choose a representative for each class. The problem with this argument that we don't know yet that every functions in <math> C_{b}(X) </math> admits such limit. But this will not stop us from falling down the rabbit hole: Note that every function in <math>  C_{0}(X) </math> admit such limit, let <math> l : C_{0}(X) \rightarrow \R </math>
We say that a function <math> u \in C_{b}(X) </math> admits a limit at infinity, <math> u(\infty) </math>, if for any <math> \epsilon >0  </math> there exists a compact set <math> K_{\epsilon} \sub X </math> such that <math> x \notin K_{\epsilon} </math> implies <math> |u(x) - u(\infty)|\leq \epsilon </math>. We can see this operation as a linear function 'limit at infinity'. Thanks to Hahn-Banach we can build a continuous extension of it for all of <math> C_{b}(X) </math>. This is another spectacular consequence of Axiom of Choice (Hahn-Banach theorem [https://en.wikipedia.org/wiki/Hahn%E2%80%93Banach_theorem] in this case). Intuitively we can partition the space <math> C_{b}(X) </math> into equivalence classes of the equivalence relation of having the same limit at infinity. Then by to the axiom of choice we choose a representative for each class. The problem with this argument, however, is that we don't know yet that every function in <math> C_{b}(X) </math> admits such a limit. But this will not stop us from falling down the rabbit hole: note that every function in <math>  C_{0}(X) </math> admits such a limit, let <math> l : C_{0}(X) \rightarrow \R </math>


:<math>  u \rightarrow u(\infty)  </math>,
:<math>  u \rightarrow u(\infty)  </math>,
Since the functions vanishes at infinity this operation of assigning limit at infinity is clearly a linear map. It's not hard to see that <math> l\in C_{0}(X)' </math>, i.e. a bounded linear operator on <math> C_{0}(X) </math>. We showed before that <math> C_{0}(X) </math> is a closed (vector) subspace of <math> C_{b}(X) </math> therefore we can extend <math> l </math> to the whole <math> C_{b}(X) </math> using the formulation of Hahn Banach Theorem for normed spaces. Let <math> L </math> be such extension, <math> L \in C_{b}(X)' </math> and <math> L=l </math> on <math> C_{0}(X) </math>. Note that this functional is supported at infinity, in the sense that for any <math> u \in C_{0}(X) </math> then <math> <L,u>=0 </math>.
Since the functions vanish at infinity this operation of assigning the limit at infinity is clearly a linear map. It's not hard to see that <math> l\in C_{0}(X)' </math>, i.e. a bounded linear operator on <math> C_{0}(X) </math>. We showed before that <math> C_{0}(X) </math> is a closed (vector) subspace of <math> C_{b}(X) </math> therefore we can extend <math> l </math> to all of <math> C_{b}(X) </math> using the formulation of the Hahn Banach Theorem for normed spaces. Let <math> L </math> be such extension, <math> L \in C_{b}(X)' </math> and <math> L=l </math> on <math> C_{0}(X) </math>. Note that this functional is supported at infinity, in the sense that for any <math> u \in C_{0}(X) </math>, we have <math> <L,u>=0 </math>.


==Kantorovich Duality for <math> C_{b}(X \times Y) </math> ==
==Kantorovich Duality for <math> C_{b}(X \times Y) </math> ==
As it can be found in Villani, Proposition 1.22 <ref>Villani, Cedric.  Topics In Optimal Transportation. American Mathematical Soc., 2003.</ref> also  [http://34.106.105.83/wiki/Kantorovich_Problem], the following version of Kantorovich duality holds: let <math> X </math> and <math> Y </math> locally compact Polish spaces, let <math> c </math> be a lower semi-continuous non negative function on <math> X \times Y </math> and let <math> \mu </math> and <math> \nu </math> be two Borel probability measures on <math> X \times Y </math> respectively then:
As it can be found in Villani, Proposition 1.22 <ref>Villani, Cedric.  Topics In Optimal Transportation. American Mathematical Soc., 2003.</ref> also  ([http://34.106.105.83/wiki/Kantorovich_Problem]), the following version of Kantorovich duality holds: let <math> X </math> and <math> Y </math> be locally compact Polish spaces, let <math> c </math> be a lower semi-continuous non negative function on <math> X \times Y </math> and let <math> \mu </math> and <math> \nu </math> be two Borel probability measures on <math> X \times Y </math> respectively, then,


:<math> \inf_{\pi \in \Pi(\mu,\nu)} \int_{X \times Y} c(x,y) d\pi(x,y)= \sup_{(\phi,\psi) \in \Phi_{c}} \int_{X}\phi d\mu + \int_{X}\psi d\nu </math>,
:<math> \inf_{\pi \in \Pi(\mu,\nu)} \int_{X \times Y} c(x,y) d\pi(x,y)= \sup_{(\phi,\psi) \in \Phi_{c}} \int_{X}\phi d\mu + \int_{X}\psi d\nu </math>,


Here <math> \Pi(\mu,\nu) </math> is the set of all probability measures <math> \pi </math> that satisfies <math> \pi(A \times Y)= \mu(A) </math> and <math> \pi(X \times B)= \nu(B) </math> for any measurable set <math> A \subset X </math> and any measurable set <math> B \subset Y </math>; <math> \Phi_{c} </math> is the set of all measurable functions <math> (\phi,\psi) \in L^1(d\mu)\times L^1(d\nu) </math> that satisfies <math> \phi(x)+\psi(x) \leq c(x,y) </math> for <math> d\mu </math> almost all <math> x \in X </math> and for <math> d\nu </math> almost all <math> y \in Y </math>.
Here <math> \Pi(\mu,\nu) </math> is the set of all probability measures <math> \pi </math> that satisfy <math> \pi(A \times Y)= \mu(A) </math> and <math> \pi(X \times B)= \nu(B) </math> for any measurable set <math> A \subset X </math> and any measurable set <math> B \subset Y </math>; <math> \Phi_{c} </math> is the set of all measurable functions <math> (\phi,\psi) \in L^1(d\mu)\times L^1(d\nu) </math> that satisfy <math> \phi(x)+\psi(x) \leq c(x,y) </math> for <math> d\mu </math> for almost all <math> x \in X </math> and for <math> d\nu </math> almost all <math> y \in Y </math>.


As mentioned in Villani Section 1.3 pag. 39<ref>Villani, Cedric.  Topics In Optimal Transportation. American Mathematical Soc., 2003.</ref>, if we try to extend the proof of the compact case we run into a problem since the dual of <math> C_{b}(X\times Y)</math> strictly contains <math> \mathcal{M}(X\times Y)</math>. If we restrict to the closed subspace <math> C_{0}(X\times Y) \subset C_{b}(X\times Y)</math> than any elements <math> C_{b}(X\times Y)'</math> acts continuously, as mentioned before, can be represented by a unique <math> \pi \in \mathcal{M}(X\times Y)</math> such that  
As mentioned in Villani Section 1.3 pg. 39<ref>Villani, Cedric.  Topics In Optimal Transportation. American Mathematical Soc., 2003.</ref>, if we try to extend the proof of the compact case we run into a problem since the dual of <math> C_{b}(X\times Y)</math> strictly contains <math> \mathcal{M}(X\times Y)</math>. If we restrict to the closed subspace <math> C_{0}(X\times Y) \subset C_{b}(X\times Y)</math> then any element in <math> C_{b}(X\times Y)'</math> which acts continuously, as mentioned before, can be represented by a unique <math> \pi \in \mathcal{M}(X\times Y)</math> such that  


:<math> <l,f> = \int_{X\times Y} f(x,y) d \pi, \text{ for every }  f \in C_{0}(X \times Y) </math>.
:<math> <l,f> = \int_{X\times Y} f(x,y) d \pi, \text{ for every }  f \in C_{0}(X \times Y) </math>.
Line 39: Line 39:
We can then write <math> l = \pi +R </math> where <math> R </math> is a continuous linear functional supported at infinity, i.e.  <math> \forall f \in C_{0}(X\times Y)</math> implies <math> <R,f>=0 </math>.
We can then write <math> l = \pi +R </math> where <math> R </math> is a continuous linear functional supported at infinity, i.e.  <math> \forall f \in C_{0}(X\times Y)</math> implies <math> <R,f>=0 </math>.


For what discussed in the previous section the behavior of some <math> R </math> may not be clear at first glance as the following result showed in exercise 1.23 of <ref>Villani, Cedric.  Topics In Optimal Transportation. American Mathematical Soc., 2003.</ref>.
From what is discussed in the previous section, the behavior of some <math> R </math> may not be clear at first glance as the following result shows in exercise 1.23 of <ref>Villani, Cedric.  Topics In Optimal Transportation. American Mathematical Soc., 2003.</ref>.


Let <math> \mu </math> and <math> \nu </math> be two Borel probability measures on <math> X \times Y </math> respectively, there is a continuous linear functional <math> L </math> on <math> C_{b}(X\times Y)</math>, supported at infinity, such that the following holds
Let <math> \mu </math> and <math> \nu </math> be two Borel probability measures on <math> X \times Y </math> respectively There is a continuous linear functional <math> L </math> on <math> C_{b}(X\times Y)</math>, supported at infinity, such that the following holds:


:<math> \forall (\phi,\psi) \in C_{0}(X) \times C_{0}(Y), <L,\phi +\psi>= \int_{X}\phi d\mu + \int_{Y}\psi d\nu.  \text{        } \bigstar  </math>.
:<math> \forall (\phi,\psi) \in C_{0}(X) \times C_{0}(Y), <L,\phi +\psi>= \int_{X}\phi d\mu + \int_{Y}\psi d\nu.  \text{        } \bigstar  </math>.
To prove this we want to apply what we have seen in the previous section, lets consider the function <math> u(x,y) \in C_0(X \times Y) </math>, for fixed <math> x </math> we can see this function as a function of <math> y </math> i,e, let <math> \hat{u}(y)=u(x,y) </math>. Noticing that <math>\hat{u} \in  C_0(Y) </math>, we can assign a limit at infinity <math> l </math> to <math>\hat{u} </math> and then extend it to all <math>\phi \in  C_b(Y) </math> following the construction of <math>L</math> in the precious section. Similarly we will do the same by considering for any fixed <math> y </math> the function <math> u(x,y) \in C_0(X \times Y) </math> as a function of <math> x </math>. Note that such extension is supported at infinity! This will allow us to first write the two functions:
To prove this we want to apply what we have seen in the previous section. Lets consider the function <math> u(x,y) \in C_0(X \times Y) </math>: for fixed <math> x </math> we can see this function as a function of <math> y </math> i,e, let <math> \hat{u}(y)=u(x,y) </math>. Noticing that <math>\hat{u} \in  C_0(Y) </math>, so we can assign a limit at infinity, <math> l </math>, to <math>\hat{u} </math> and then extend it to all <math>\phi \in  C_b(Y) </math> following the construction of <math>L</math> in the precious section. Similarly we will consider for any fixed <math> y </math> the function <math> u(x,y) \in C_0(X \times Y) </math> as a function of <math> x </math>. Note that such an extension is supported at infinity! This will allow us to first write the two functions:


:<math> u_1(x,\infty)= l(\hat{u}(y)), u_2(\infty,y)=l(\hat{u}(x)) </math>.
:<math> u_1(x,\infty)= l(\hat{u}(y)), u_2(\infty,y)=l(\hat{u}(x)) </math>.
Since we are only considering functions that vanishing at infinity we can conclude that our <math> u_1 \in C_b(X) </math>  and <math> u_2 \in C_b(Y) </math> satisfy the following:  
Since we are only considering functions that vanish at infinity we can conclude that our <math> u_1 \in C_b(X) </math>  and <math> u_2 \in C_b(Y) </math> satisfy the following:  
:<math>  <l, u_1+u_2 >= \int_{X}u_1(x,\infty) d\mu (x) + \int_{Y}u_2(\infty,y) d\nu(y)    </math>.
:<math>  <l, u_1+u_2 >= \int_{X}u_1(x,\infty) d\mu (x) + \int_{Y}u_2(\infty,y) d\nu(y)    </math>.


Where <math> l </math>, with a slightly abuse of notation, is  the simultaneously assignment of limit at infinity in <math>  C_b(Y) </math> and <math>  C_b(X) </math>. The simultaneously extension <math> L </math>, again with a little abuse of notation, will be a bounded linear functional on <math> C_{b}(X\times Y)</math>and it will satisfy <math> \bigstar</math> when restricted to <math> C_{0}(X)\times C_{0}(Y) </math>. By construction, shown in the previous section, <math> L </math> is supported at infinity which means that when restricted to <math> C_{0}(X \times Y) </math>, it acts like the <math> 0 </math> map. This means that we can't conclude easily that <math> L </math> can be represented as an element of <math> \Pi(\mu,\nu)</math>.
Here <math> l </math>, with a slightly abuse of notation, is  the simultaneous assignment of the limit at infinity in <math>  C_b(X) </math> and <math>  C_b(Y) </math>. The simultaneous extension <math> L </math>, again with a little abuse of notation, will be a bounded linear functional on <math> C_{b}(X\times Y)</math>and it will satisfy <math> \bigstar</math> when restricted to <math> C_{0}(X)\times C_{0}(Y) </math>. By construction, shown in the previous section, <math> L </math> is supported at infinity which means that when restricted to <math> C_{0}(X \times Y) </math>, it acts like the <math> 0 </math> map. This means that we can't conclude easily that <math> L </math> can be represented as an element of <math> \Pi(\mu,\nu)</math>.


It turns out that in our hypothesis we can have the decomposition <math> L = \pi +R </math> where <math> R </math> is a continuous linear functional supported at infinity works and that <math> L  </math> can be indeed represented as an element of <math> \Pi(\mu,\nu)</math>, we will write: <math> L \in \Pi(\mu,\nu) </math>. The key idea to prove this is to use the identity <math> <L,1>=1 </math>. The detailed proof can be found again in Villani lemma 1.25 <ref>Villani, Cedric.  Topics In Optimal Transportation. American Mathematical Soc., 2003.</ref>.
It turns out that in our hypothesis we can have the decomposition <math> L = \pi +R </math> where <math> R </math> is a continuous linear functional supported at infinity and then <math> L  </math> can be indeed represented as an element of <math> \Pi(\mu,\nu)</math>; we will write: <math> L \in \Pi(\mu,\nu) </math>. The key idea to prove this is to use the identity <math> <L,1>=1 </math>. The detailed proof can be found again in Villani lemma 1.25 <ref>Villani, Cedric.  Topics In Optimal Transportation. American Mathematical Soc., 2003.</ref>.

Latest revision as of 04:38, 28 February 2022

Introduction

In the case that the space is compact then all continuous functions belong to as we will show in the next section. On the other hand if the space is not compact, we always have the inclusion , but there may be some continuous functions that do not belong to . Some of them may even even be bounded and still not belong to , which motivates us to consider the dual space of and the dual space of .

Background and Statement

Let equipped with the sup norm. In other words this is the space of continuous functions vanishing at infinity. When is compact we can choose in the previous definition, and since properties on the empty set are trivially true, we can conclude that . Let be the space of bounded continuous functions on together with the sup norm. Again when is compact we have not introduced a new space since every continuous function on a compact metric space is bounded, to see this assume on the contrary that there is a sequence such that as . By compactness there is a sub-sequence converging to a point . Therefore by continuity of we have , and this is our desired contradiction. We conclude that .

The rest of this discussion will consider the case where is not compact. Rather than equality of the three spaces, we have the inclusions:

The case of

The representation of the dual space of is a described by the following well known result in Functional Analysis (Riesz Representation Theorem 6.19 in Rudin [1]):

Let be a locally compact Hausdorff space For any bounded linear function , i.e. an element of the dual space , there is a unique complex Borel measure such that the following holds:

.

This allows us to identify with , the space of complex Borel measures. Moreover we can endow with the total variation norm: .

The case of

To describe the dual space of , we will focus on the behavior of functions at infinity, as in Exercise 1.23 of [2]. We first need a preliminary result: is a closed (vector) subspace of . In other words, contains all its limit points. Let be a convergent sequence in , where are continuous functions vanishing at infinity and let their limit then f is continuous since the uniform norm we are using provides uniform convergence. It remains to show that the limit vanishes at infinity: let be such that .Now since each vanishes at infinity, we can find such that for any . Then we can conclude by the triangle inequality that

.

That is, . This proves is a closed subspace of . We may now carefully specify the local property at infinity for .

We say that a function admits a limit at infinity, , if for any there exists a compact set such that implies . We can see this operation as a linear function 'limit at infinity'. Thanks to Hahn-Banach we can build a continuous extension of it for all of . This is another spectacular consequence of Axiom of Choice (Hahn-Banach theorem [1] in this case). Intuitively we can partition the space into equivalence classes of the equivalence relation of having the same limit at infinity. Then by to the axiom of choice we choose a representative for each class. The problem with this argument, however, is that we don't know yet that every function in admits such a limit. But this will not stop us from falling down the rabbit hole: note that every function in admits such a limit, let

,

Since the functions vanish at infinity this operation of assigning the limit at infinity is clearly a linear map. It's not hard to see that , i.e. a bounded linear operator on . We showed before that is a closed (vector) subspace of therefore we can extend to all of using the formulation of the Hahn Banach Theorem for normed spaces. Let be such extension, and on . Note that this functional is supported at infinity, in the sense that for any , we have .

Kantorovich Duality for

As it can be found in Villani, Proposition 1.22 [3] also ([2]), the following version of Kantorovich duality holds: let and be locally compact Polish spaces, let be a lower semi-continuous non negative function on and let and be two Borel probability measures on respectively, then,

,

Here is the set of all probability measures that satisfy and for any measurable set and any measurable set ; is the set of all measurable functions that satisfy for for almost all and for almost all .

As mentioned in Villani Section 1.3 pg. 39[4], if we try to extend the proof of the compact case we run into a problem since the dual of strictly contains . If we restrict to the closed subspace then any element in which acts continuously, as mentioned before, can be represented by a unique such that

.

We can then write where is a continuous linear functional supported at infinity, i.e. implies .

From what is discussed in the previous section, the behavior of some may not be clear at first glance as the following result shows in exercise 1.23 of [5].

Let and be two Borel probability measures on respectively There is a continuous linear functional on , supported at infinity, such that the following holds:

.

To prove this we want to apply what we have seen in the previous section. Lets consider the function : for fixed we can see this function as a function of i,e, let . Noticing that , so we can assign a limit at infinity, , to and then extend it to all following the construction of in the precious section. Similarly we will consider for any fixed the function as a function of . Note that such an extension is supported at infinity! This will allow us to first write the two functions:

.

Since we are only considering functions that vanish at infinity we can conclude that our and satisfy the following:

.

Here , with a slightly abuse of notation, is the simultaneous assignment of the limit at infinity in and . The simultaneous extension , again with a little abuse of notation, will be a bounded linear functional on and it will satisfy when restricted to . By construction, shown in the previous section, is supported at infinity which means that when restricted to , it acts like the map. This means that we can't conclude easily that can be represented as an element of .

It turns out that in our hypothesis we can have the decomposition where is a continuous linear functional supported at infinity and then can be indeed represented as an element of ; we will write: . The key idea to prove this is to use the identity . The detailed proof can be found again in Villani lemma 1.25 [6].

  1. Rudin, Walter. Real and Complex Analysis, 1966.
  2. Villani, Cedric. Topics In Optimal Transportation. American Mathematical Soc., 2003.
  3. Villani, Cedric. Topics In Optimal Transportation. American Mathematical Soc., 2003.
  4. Villani, Cedric. Topics In Optimal Transportation. American Mathematical Soc., 2003.
  5. Villani, Cedric. Topics In Optimal Transportation. American Mathematical Soc., 2003.
  6. Villani, Cedric. Topics In Optimal Transportation. American Mathematical Soc., 2003.