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This might be a trivial question, but I am trying to prove equipment-coerciveness of some family of functions on the space of Probability measures on some space. I could reduce the problem to showing that $$\{\nu:\mathcal{W}_2^2(\mu, \nu)\le t\}$$ is compact (or is at least contained in some compact subset of $\mathcal{P}(\mathbb{R})$.)

The space of probability measures on $\mathbb{R}$ is equipped with weak topology. Now, I know from Banach Alaglou theorem unit ball in weak topology is compact. But here I am taking the ball in $\mathcal{W}_2$ metric. Can anyone tell me if this is correct or I am just wasting time?

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  • $\begingroup$ Do you mean "contained in some compact subset of the space of probability measures", or do you mean "contained in some compact subset of the space of probability measures for which $\cal W_2$ is defined"? $\endgroup$ – user95282 Jan 8 at 14:59
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Yes, it is true. It follows from Prokhorov's theorem that in order to prove (pre-)compactness, it suffices to prove tightness. However, if we define $K$ to be the compact set such that $\mu(\mathbb{R}\setminus K)<\varepsilon$, and $K_T:=\{x\in \mathbb{R}:\mathrm{dist}(K,x)\leq T\}$, then $\nu(\mathbb{R}\setminus K_T)>2\varepsilon$ implies that $\mathcal{W}_2^2(\mu,\nu)>\varepsilon T^2$ (since you have to move a mass $\geq\varepsilon$ over a distance $\geq T$), and so it is impossible for $\nu$ in your set provided that $\varepsilon T^2>t$. This proves tightness.

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Since we care about probability measures, a sufficient condition for compactness is that the supports of the respective probability measures are compact. Here is the reasoning:

  1. Let $X$ be a compact subset of $\mathbb{R}^d$. Denote by $C_0^\ast(\mathbb{R}^d)$ the space of all continuous functions on $\mathbb{R}^d$ that vanish at infinity. Then the Banach-Alaoglu theorem implies that the unit ball of $C^\ast_0(\mathbb{R}^d)$ is compact in the weak$^\ast$-topology. This implies that the set of probability measures is compact in the weak$^\ast$ topology.

  2. In general, the weak$^\ast$ and the weak topology do not coincide for measures on $\mathbb{R}^d$, but they do for measures on the compact $X$, as then $C_0^\ast(X)=C_b^\ast(X)$, where $C_b(X)$ is the space of all bounded and continuous functions on $X$. This means that the set $\mathcal{M}(X)$ of all probability measures on $X$ equipped with the total variation norm is weak$^*$- and therefore weakly compact.

  3. On compact sets the $p$-Wasserstein distance (for $p\in[1,\infty)$) metrizes weak convergence (Theorem 5.10 in Santambrogio 2015), from which it follows that the set you defined is compact since it is closed.

In my opinion, a great reference for these sorts of questions is:

Santambrogio, F (2015): "Optimal Transport for Applied Mathematicians", Birkhäuser

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