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I'm reading section 3.4 Existence of Maximisers to the Dual Problem in this lecture notes. The proof is quite involved and requires a complicated approximation argument.

Below is my straightforward approach which is so naive that I'm not sure if it's correct. Could you have a check on my attempt?


Let $X,Y$ be Polish spaces and $c:X \times Y \to \mathbb [0, +\infty)$. We fix Borel probability measures (b.p.m.) $\mu \in \mathcal P(X)$ and $\nu \in \mathcal P(Y)$.

  • Let $\Phi_c$ be the collection of $(\varphi: X \to \mathbb R, \psi: Y \to \mathbb R) \in L_1(\mu) \times L_1(\nu)$ such that $\varphi(x)+\psi(y) \le c(x,y)$ for $\mu$-a.e. $x\in X$ and $\nu$-a.e. $y\in Y$.

  • Let $$ J (\varphi, \psi) := \int_X \varphi d \mu + \int \psi d \nu \quad \forall (\varphi, \psi) \in \Phi_c. $$

  • We assume a regularity condition that there are $c_X: X \to \mathbb R$ and $c_Y: Y \to \mathbb R$ such that $c_X \in L_1(\mu), c_Y \in L_1 (\nu)$, and $c (x, y) \le c_X(x)+c_Y(y)$ for $\mu$-a.e. $x\in X$ and $\nu$-a.e. $y\in Y$.

Then the maximization $$ \sup_{(\varphi, \psi) \in \Phi_c} J (\varphi, \psi) $$ has a solution.


My attempt: We need the following essential lemma.

Lemma: For each $(\varphi, \psi) \in \Phi_c$, there is an improved pair $(\overline \varphi, \overline\psi) \in \Phi_c$ such that

  • $J (\varphi, \psi) = J (\overline \varphi, \overline\psi)$.
  • $\varphi (x) \le c_X (x)$ and $\psi (y) \le c_Y (y)$ for $\mu$-a.e. $x\in X$ and $\nu$-a.e. $y\in Y$.

Let $(\varphi_n, \psi_n) \subset \Phi_c$ be a maximizing sequence. Let $(\overline \varphi_n, \overline\psi_n) \in \Phi_c$ be the improved pair of $(\varphi_n, \psi_n)$ as in the Lemma, i.e.,

  • $J (\varphi_n, \psi_n) = J (\overline \varphi_n, \overline\psi_n)$.
  • $\overline \varphi_n (x) \le c_X (x)$ and $\overline \psi_n (y) \le c_Y (y)$ for $\mu$-a.e. $x\in X$ and $\nu$-a.e. $y\in Y$.

Let $$ \varphi := \limsup_n \overline\varphi_n \quad \text{and} \quad \psi := \limsup_n \overline \psi. $$

Then $\varphi$ is $\mu$-measurable and $\psi$ is $\nu$-measurable. For every $n \in \mathbb N$, we have

  • $\overline \varphi_n (x) \le \varphi (x) \le c_X (x)$ for all $\mu$-a.e. $x\in X$.
  • $\overline \psi (y) \le \psi (y) \le c_Y (y)$ for all $\nu$-a.e. $y \in Y$.

This means $\varphi, \psi$ are bounded by $\mu$-integrable and $\nu$-integrable functions respectively, so $\varphi \in L_1(\mu)$ and $\psi \in L_1 (\nu)$. Clearly, $$ J(\varphi_n, \psi_n) \le J(\varphi, \psi) \quad \forall n\in \mathbb N. $$

Hence $$ \sup_{(\varphi, \psi) \in \Phi_c} J (\varphi, \psi) \le J(\varphi, \psi). $$

It remains to show that $\varphi (x)+ \psi(y) \le c(x,y)$ for $\mu$-a.e. $x\in X$ and $\nu$-a.e. $y \in Y$. For each $n \in \mathbb N$, $$ \overline \varphi_n (x)+ \overline\psi_n(y) \le c(x,y) $$ for $\mu$-a.e. $x\in X$ and $\nu$-a.e. $y \in Y$. Notice that the countable union of null sets is again a null set. Then $$ \limsup_n \overline \varphi_n (x)+ \limsup_n \overline\psi_n(y) \le c(x,y) $$ for $\mu$-a.e. $x\in X$ and $\nu$-a.e. $y \in Y$. This completes the proof.

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1 Answer 1

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I have realized that I made a stupid mistake in claiming

$$\limsup_n \overline \varphi_n (x)+ \limsup_n \overline\psi_n(y) \le \limsup_n [\overline \varphi_n (x)+ \overline\psi_n(y)].$$

The correct proof by the author is as follows.


Let $(\varphi_n, \psi_n) \subset \Phi_c$ be a maximizing sequence. WLOG, we assume $$ J (\varphi_n, \psi_n) \ge 0 \quad \forall n \in \mathbb N. $$

Let $(\overline \varphi_n, \overline\psi_n) \in \Phi_c$ be the improved pair of $(\varphi_n, \psi_n)$ as in the Lemma, i.e.,

  • $J (\varphi_n, \psi_n) = J (\overline \varphi_n, \overline\psi_n)$.
  • $\overline \varphi_n (x) \le c_X (x)$ and $\overline \psi_n (y) \le c_Y (y)$ for $\mu$-a.e. $x\in X$ and $\nu$-a.e. $y\in Y$.

For $(m, n)\in \mathbb N^2$, let $$ \alpha_{m,n} : =\min \{c_X-\overline \varphi_n, m\} \quad \text{and} \quad \beta_{m,n} : =\min \{c_Y-\overline \psi_n, m\} . $$

  • Then $0 \le \alpha_{m,n} \le m$ and $0 \le \beta_{m,n} \le m$ for all $n \in \mathbb N$.
  • This implies the sequences $(\alpha_{m,n})_{n \in \mathbb N}$ and $(\beta_{m,n})_{n \in \mathbb N}$ are bounded in $L_2(\mu)$ and $L_2(\nu)$ respectively.
  • Notice that $L_2(\mu)$ and $L_2(\nu)$ are reflexive. Hence $\overline{(\alpha_{m,n})_{n \in \mathbb N}}^{L_2(\mu)}$ and $\overline{(\beta_{m,n})_{n \in \mathbb N}}^{L_2(\nu)}$ are weakly compact. By Tychonoff theorem, $$ \Pi_{m \in \mathbb N} \overline{(\alpha_{m,n})_{n \in \mathbb N}}^{L_2(\mu)} \times \Pi_{m \in \mathbb N} \overline{(\beta_{m,n})_{n \in \mathbb N}}^{L_2(\nu)} $$ is compact in the product of weak topologies.
  • Hence there are $\alpha_1, \alpha_2, \ldots \in L_2(\mu)$ and $\beta_1, \beta_2, \ldots \in L_2(\nu)$ and a subsequence $\lambda \in \mathbb N^\mathbb N$ such that for all $m$, we have $\alpha_{m,\lambda(n)} \rightharpoonup \alpha_m$ and $\beta_{m,\lambda(n)} \rightharpoonup \beta_m$ weakly as $n \to \infty$.
  • WLOG, we assume $\lambda$ is the identity map, i.e., $\lambda(n)=n$ for all $n \in \mathbb N$.
  • Also, $0 \le \alpha_{m,n} \le \alpha_{m+1,n}$ and $0 \le \beta_{m,n} \le \beta_{m+1,n}$ for all $n \in \mathbb N$. Weak convergence preserves pointwise inequalities, so $$ 0 \le \alpha_m \le \alpha_{m+1} \le m+1 \quad \text{and} \quad 0 \le \beta_m \le \beta_{m+1} \le m+1 \quad \forall m \in \mathbb N. $$

Let $$ \alpha := \lim_m \alpha_m \quad \text{and} \quad \beta := \lim_m \beta_m. $$

Above limits are well-defined by the monotonicity of $(\alpha_m)$ and $(\beta_m)$. Clearly, $\alpha$ is $\mu$-measurable and $\beta$ is $\nu$-measurable. Also, $0 \le \alpha$ and $0 \le \beta$. Let's prove that $\alpha \in L_1(\mu)$ and $\beta \in L_1 (\nu)$. Clearly, $$ 0 \le \int \alpha d \mu \le +\infty \quad \text{and} \quad 0 \le \int \beta d \nu \le +\infty. $$

We have $$ \begin{align*} & \int \alpha d \mu + \int \beta d \nu \\ =&\lim_m \int \alpha_m d \mu + \lim_m \int \beta_m d \nu \quad \text{by monotone convergence} \\ =&\lim_m \left (\int \alpha_m d \mu + \int \beta_m d \nu \right ) \end{align*} $$

Notice that $\alpha_{m,n} \rightharpoonup \alpha_m$ in the weak topology of $L_2(\mu)$ and that the map $$ L_2(\mu) \to \mathbb R, f \mapsto \int f d \mu $$ is linear continuous in the norm topology $\| \cdot \|_{L_2(\mu)}$. So $$ \int \alpha_m d\mu = \lim_n \int \alpha_{m,n} d\mu. $$

Similarly, $$ \int \beta_m d\nu = \lim_n \int \beta_{m,n} d\nu. $$

Hence $$ \begin{align*} & \int \alpha d \mu + \int \beta d \nu \\ =& \lim_m \left ( \lim_n \int \alpha_{m, n} d \mu + \lim_n \int \beta_{m, n} d \nu \right ) \\ =& \lim_m \lim_n \left ( \int \alpha_{m, n} d \mu + \int \beta_{m, n} d \nu \right ) \\ \le& \lim_m \lim_n \left ( \int (c_X-\overline \varphi_n) d \mu + \int (c_Y-\overline \psi_n) d \nu \right ) \\ =& \lim_n \left ( \int (c_X-\overline \varphi_n) d \mu + \int (c_Y-\overline \psi_n) d \nu \right ) \end{align*} $$

Notice that the integrals $\int c_X d \mu, \int \overline \varphi_n d \mu, \int c_Y d \nu, \int \overline \psi_n d \nu$ are finite, so $$ \begin{align*} & \int \alpha d \mu + \int \beta d \nu \\ \le& \lim_n \left ( \int c_X d \mu - \int \overline \varphi_n d \mu + \int c_Y d \nu - \int \overline \psi_n d \nu \right ) \\ =& \lim_n (J(c_X, c_Y)- J(\overline \varphi_n, \overline \psi_n)) \\ =& J(c_X, c_Y) - \lim_n J(\overline \varphi_n, \overline \psi_n) \\ \le& J(c_X, c_Y) < +\infty. \end{align*} $$

It follows that $$ \int \alpha d \mu < +\infty, \quad \int \beta d \nu < +\infty, \quad \lim_n J(\overline \varphi_n, \overline \psi_n) < +\infty. $$

So $\alpha \in L_1 (\mu)$ and $\beta \in L_1 (\nu)$. Let $$ \varphi := c_X - \alpha \quad \text{and} \quad \psi := c_Y-\beta. $$

Clearly, $\varphi \in L_1 (\mu)$ and $\psi \in L_1 (\nu)$. It follows from above inequality that $$ J(\varphi, \psi) = J(c_X, c_Y) - J(\alpha, \beta) \ge \lim_n J(\overline \varphi_n, \overline \psi_n). $$

We have $$ \begin{align*} & \varphi (x)+ \psi(y) \\ =& c_X(x)-\alpha(x) +c_Y(y)-\beta(y) \\ =& c_X(x) - \lim_m \alpha_m (x) + c_Y(y) - \lim_m \beta_m (y) \\ =& c_X(x) - \lim_m \lim_n \alpha_{m, n} (x) + c_Y(y) - \lim_m \lim_n \beta_{m,n}(y) \\ =& \lim_m \lim_n (c_{X} (x)-\alpha_{m, n} (x)) + \lim_m \lim_n (c_Y(y) - \beta_{m,n}(y)) \\ =& \lim_m \lim_n \left [ \max \{ \overline\varphi_n(x), c_X(x)-m\} + \max \{ \overline\psi_n(y), c_Y(y)-m\} \right ]. \end{align*} $$

We have $$ \begin{align*} & \max \{ \overline\varphi_n(x), c_X(x)-m\} + \max \{ \overline\psi_n(y), c_Y (y)-m\} \\ =& c_X(x) + c_Y(y)+\max \{ \overline\varphi_n(x) -c_X(x), -m\} + \max \{ \overline\psi_n(y) - c_Y (y), -m\} \\ \le & c_X(x) + c_Y(y)+\max \{ \overline\varphi_n(x) -c_X(x)+\overline\psi_n(y) - c_Y (y), -m\} \quad (\star)\\ \le & c_X(x) + c_Y(y)+\max \{ c(x,y)-c_X(x) - c_Y (y), -m\} \\ \end{align*} $$

Here $(\star)$ follows from this result. It follows that $$ \begin{align*} & \varphi (x)+ \psi(y) \\ \le & \lim_m \left [c_X(x) + c_Y(y)+\max \{ c(x,y) -c_X(x)- c_Y (y), -m\} \right ] \\ = & c_X(x) + c_Y(y) + [c(x,y)-c_X(x) - c_Y (y)] \\ = & c(x,y). \end{align*} $$

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