TheoremBase

The lower bound integrates the kernel bound; translation invariance is a change of variables. For closed sublevel sets, product measures converge weakly, truncated kernels pass to the limit, an atom would force the truncated energies to blow up, and monotone convergence removes the truncation; lower semicontinuity follows.

Proof

Each result cited below is universally quantified over the data in its own statement, and is applied to the data named at the point of use. The rules for adding, multiplying and comparing inequalities between real numbers in Elementary Order Arithmetic in an Ordered Field and Elementary Arithmetic in an Ordered Field, and Properties of the Absolute Value in an Ordered Field, are used without further mention. As in One-Dimensional Test Functions: Scalars, Derivatives, and the Difference Quotient of the Derivative, a point of R2\mathbb{R}^{2} is written (x,y)=ι(x,y)(x,y)=\iota(x,y), and ∥s∥=∣s∣\lVert s\rVert=|s|, ∥s∥2=s2\lVert s\rVert^{2}=s^{2} for s∈Rs\in\mathbb{R} by One-Dimensional Test Functions: Scalars, Derivatives, and the Difference Quotient of the Derivative (i); in particular M2(ν)=∫Rx2 ν(dx)M_{2}(\nu)=\int_{\mathbb{R}}x^{2}\,\nu(dx) for ν∈P(R)\nu\in\mathcal{P}(\mathbb{R}) (The Second Moment of a Probability Measure on Euclidean Space and the Probability Measures with Finite Second Moment (i)). The projections pr1,pr2:R2→R\mathrm{pr}_{1},\mathrm{pr}_{2}:\mathbb{R}^{2}\to\mathbb{R} satisfy pr1(x,y)=x\mathrm{pr}_{1}(x,y)=x, pr2(x,y)=y\mathrm{pr}_{2}(x,y)=y and are Borel (Pairs of Euclidean Points: Coordinate Projections, Pairings, the Product Measure on a Euclidean Space, Borel Norm Functions and Finite Sets (i)); ℓ\ell is the logarithmic kernel, Borel by The Logarithmic Kernel on the Real Line: Borel Measurability, a Linear Lower Bound, and the Null Diagonal of an Atomless Measure (i), and Δ\Delta the diagonal of that lemma, a Borel set by the same clause. Two consequences of Pairs of Euclidean Points: Coordinate Projections, Pairings, the Product Measure on a Euclidean Space, Borel Norm Functions and Finite Sets (iii) and the Tonelli part of Tonelli's and Fubini's Theorems are used throughout: for ν,ν′∈P(R)\nu,\nu'\in\mathcal{P}(\mathbb{R}) and Borel F:R2→[0,∞]F:\mathbb{R}^{2}\to[0,\infty], each section y↦F(x,y)y\mapsto F(x,y) is Borel, x↦∫F(x,y) ν(dy)x\mapsto\int F(x,y)\,\nu(dy) is Borel, and

∫R2F d(ν′⊠ν)=∫R(∫RF(x,y) ν(dy))ν′(dx),(T)\int_{\mathbb{R}^{2}}F\,d(\nu'\boxtimes\nu)=\int_{\mathbb{R}}\Bigl(\int_{\mathbb{R}}F(x,y)\,\nu(dy)\Bigr)\nu'(dx),\tag{T}

also with the order of integration reversed; and, the images of ν⊠ν\nu\boxtimes\nu under pr1\mathrm{pr}_{1} and pr2\mathrm{pr}_{2} being ν\nu (Pairs of Euclidean Points: Coordinate Projections, Pairings, the Product Measure on a Euclidean Space, Borel Norm Functions and Finite Sets (iii)), ∫u∘pri d(ν⊠ν)=∫u dν\int u\circ\mathrm{pr}_{i}\,d(\nu\boxtimes\nu)=\int u\,d\nu for i=1,2i=1,2 and every Borel u:R→[0,∞]u:\mathbb{R}\to[0,\infty], by Probability Measures on Euclidean Space and Random Vectors: Standing Notation (iv).

Step 0 (A quadratic minorant of the kernel). Define q:R2→Rq:\mathbb{R}^{2}\to\mathbb{R} by q(z)=1+12(pr1(z)2+pr2(z)2)q(z)=1+\tfrac12\bigl(\mathrm{pr}_{1}(z)^{2}+\mathrm{pr}_{2}(z)^{2}\bigr); it is Borel by claims 1 to 3 of Arithmetic of Measurable Real- and [0,∞]-Valued Maps and continuous by Continuity of the Coordinate Projections and of the Quadratic Cost Function, and Passage of a Cost Bound to a Weak Limit (i) and claims 1, 2, 5 of Continuity of Sums and Products of Real-Valued Functions on a Metric Space. For real ss, 0≤(∣s∣−1)2=s2−2∣s∣+10\le(|s|-1)^{2}=s^{2}-2|s|+1 by Nonnegativity of Squares in an Ordered Field, so ∣s∣≤12(1+s2)|s|\le\tfrac12(1+s^{2}); hence ∣x∣+∣y∣≤q(x,y)|x|+|y|\le q(x,y) and, by The Logarithmic Kernel on the Real Line: Borel Measurability, a Linear Lower Bound, and the Null Diagonal of an Atomless Measure (ii),

−q(z)≤ℓ(z)(z∈R2).(Q)-q(z)\le\ell(z)\qquad(z\in\mathbb{R}^{2}).\tag{Q}

For ν∈P2(R)\nu\in\mathcal{P}_{2}(\mathbb{R}), the facts above and claim 1 of Linearity and Monotonicity of the Lebesgue Integral, and the Integrability Criterion give ∫q d(ν⊠ν)=1+M2(ν)<∞\int q\,d(\nu\boxtimes\nu)=1+M_{2}(\nu)<\infty, so qq is ν⊠ν\nu\boxtimes\nu-integrable (Integrable Functions and Their Lebesgue Integral).

Clause 1. Let μ∈Dlog⁡\mu\in\mathcal{D}_{\log}. Both ℓ\ell and −q-q are μ⊠μ\mu\boxtimes\mu-integrable, so (Q) and claim 2 of Linearity and Monotonicity of the Lebesgue Integral, and the Integrability Criterion give Elog⁡(μ)=∫ℓ d(μ⊠μ)≥−∫q d(μ⊠μ)=−(1+M2(μ))\mathcal{E}_{\log}(\mu)=\int\ell\,d(\mu\boxtimes\mu)\ge-\int q\,d(\mu\boxtimes\mu)=-(1+M_{2}(\mu)).

Clause 2. Let μ∈Dlog⁡\mu\in\mathcal{D}_{\log}, a∈Ra\in\mathbb{R} and ν=(τa)#μ\nu=(\tau_{a})_{\#}\mu, where τa(x)=x+a\tau_{a}(x)=x+a (The Wasserstein Space and Its Lift to Square-Integrable Random Vectors: Standing Notation (vi)). Since ∣τa(x)−τa(x′)∣=∣x−x′∣|\tau_{a}(x)-\tau_{a}(x')|=|x-x'|, τa\tau_{a} is Lipschitz, hence continuous (A Lipschitz Map is Uniformly Continuous and Continuous) and Borel (claims 3(a) and 5 of The Borel Sigma-Algebra of a Euclidean Space as a Product, and Measurability of Projections, Sequentially Continuous Maps, and Open and Closed Sets), and ν∈P(R)\nu\in\mathcal{P}(\mathbb{R}) by Probability Measures on Euclidean Space and Random Vectors: Standing Notation (iv). By the change of variables there and the inequality ∥x−y∥2≤2∥x∥2+2∥y∥2\lVert x-y\rVert^{2}\le2\lVert x\rVert^{2}+2\lVert y\rVert^{2} of Pairs of Euclidean Points: Coordinate Projections, Pairings, the Product Measure on a Euclidean Space, Borel Norm Functions and Finite Sets (iv) with y=−ay=-a, M2(ν)=∫(x+a)2 μ(dx)≤2M2(μ)+2a2<∞M_{2}(\nu)=\int(x+a)^{2}\,\mu(dx)\le2M_{2}(\mu)+2a^{2}<\infty. For b∈Rb\in\mathbb{R}, ν({b})=μ(τa−1({b}))=μ({b−a})=0\nu(\{b\})=\mu(\tau_{a}^{-1}(\{b\}))=\mu(\{b-a\})=0. Now let F:R2→[0,∞]F:\mathbb{R}^{2}\to[0,\infty] be Borel with F(x+a,y+a)=F(x,y)F(x+a,y+a)=F(x,y) for all x,yx,y. By (T), the change of variables of Probability Measures on Euclidean Space and Random Vectors: Standing Notation (iv) applied first to the inner integrand y↦F(x,y)y\mapsto F(x,y) and then to the Borel function x↦∫F(x,y) ν(dy)x\mapsto\int F(x,y)\,\nu(dy), and (T) again,

∫F d(ν⊠ν)=∫(∫F(x,y+a) μ(dy))ν(dx)=∫(∫F(x+a,y+a) μ(dy))μ(dx)=∫F d(μ⊠μ).\int F\,d(\nu\boxtimes\nu)=\int\Bigl(\int F(x,y+a)\,\mu(dy)\Bigr)\nu(dx)=\int\Bigl(\int F(x+a,y+a)\,\mu(dy)\Bigr)\mu(dx)=\int F\,d(\mu\boxtimes\mu).

Since (x+a)−(y+a)=x−y(x+a)-(y+a)=x-y, ℓ(x+a,y+a)=ℓ(x,y)\ell(x+a,y+a)=\ell(x,y) for all x,yx,y, so this applies to the positive and negative parts ℓ+,ℓ−\ell^{+},\ell^{-} of ℓ\ell, which are Borel (Integrable Functions and Their Lebesgue Integral). Both integrals are finite for μ⊠μ\mu\boxtimes\mu because ℓ\ell is μ⊠μ\mu\boxtimes\mu-integrable; hence ℓ\ell is ν⊠ν\nu\boxtimes\nu-integrable and ∫ℓ d(ν⊠ν)=∫ℓ+d(ν⊠ν)−∫ℓ−d(ν⊠ν)=Elog⁡(μ)\int\ell\,d(\nu\boxtimes\nu)=\int\ell^{+}d(\nu\boxtimes\nu)-\int\ell^{-}d(\nu\boxtimes\nu)=\mathcal{E}_{\log}(\mu). By The Logarithmic Energy of a Probability Measure on the Real Line (i), ν∈Dlog⁡\nu\in\mathcal{D}_{\log} and Elog⁡(ν)=Elog⁡(μ)\mathcal{E}_{\log}(\nu)=\mathcal{E}_{\log}(\mu).

Clause 3. Let (μn)n(\mu_{n})_{n}, μ\mu and cc be as in clause 3.

Step 1 (Truncated kernels). Write ρ(z)=∣pr1(z)−pr2(z)∣\rho(z)=|\mathrm{pr}_{1}(z)-\mathrm{pr}_{2}(z)|, so Δ={ρ=0}\Delta=\{\rho=0\}. For k∈Nk\in\mathbb{N} put sk=exp⁡(−k)>0s_{k}=\exp(-k)>0 and ℓk(z)=−log⁡(max⁡{ρ(z),sk})\ell_{k}(z)=-\log\bigl(\max\{\rho(z),s_{k}\}\bigr), where exp⁡\exp and log⁡\log are as in The Natural Logarithm. From that definition and claims 1, 2 and 4 of Basic Properties of the Exponential Function: log⁡(exp⁡u)=u\log(\exp u)=u, log⁡(st)=log⁡s+log⁡t\log(st)=\log s+\log t, 1/sk=exp⁡(k)1/s_{k}=\exp(k); log⁡\log is nondecreasing and log⁡s<log⁡t\log s<\log t for 0<s<t0<s<t (else t=exp⁡(log⁡t)≤exp⁡(log⁡s)=st=\exp(\log t)\le\exp(\log s)=s); and for sk≤t≤ss_{k}\le t\le s, with v=log⁡(s/t)≥0v=\log(s/t)\ge0, s/t=exp⁡(v)≥1+vs/t=\exp(v)\ge1+v, whence 0≤log⁡s−log⁡t=v≤(s−t)/t≤exp⁡(k)(s−t)0\le\log s-\log t=v\le(s-t)/t\le\exp(k)(s-t).

(i) For z,z′∈R2z,z'\in\mathbb{R}^{2} the last estimate, applied to the larger and the smaller of max⁡{ρ(z),sk}\max\{\rho(z),s_{k}\} and max⁡{ρ(z′),sk}\max\{\rho(z'),s_{k}\}, together with ∣max⁡{ρ(z),sk}−max⁡{ρ(z′),sk}∣≤∣ρ(z)−ρ(z′)∣|\max\{\rho(z),s_{k}\}-\max\{\rho(z'),s_{k}\}|\le|\rho(z)-\rho(z')| (a case check using claim 2 of Elementary Properties of the Maximum of Two Elements) and ∣ρ(z)−ρ(z′)∣≤∣pr1(z)−pr1(z′)∣+∣pr2(z)−pr2(z′)∣≤2∥z−z′∥|\rho(z)-\rho(z')|\le|\mathrm{pr}_{1}(z)-\mathrm{pr}_{1}(z')|+|\mathrm{pr}_{2}(z)-\mathrm{pr}_{2}(z')|\le2\lVert z-z'\rVert (claims 7, 5 of Properties of the Absolute Value in an Ordered Field and Continuity of the Coordinate Projections and of the Quadratic Cost Function, and Passage of a Cost Bound to a Weak Limit (i)), gives ∣ℓk(z)−ℓk(z′)∣≤2exp⁡(k)∥z−z′∥|\ell_{k}(z)-\ell_{k}(z')|\le2\exp(k)\lVert z-z'\rVert. So ℓk\ell_{k} is continuous (A Lipschitz Map is Uniformly Continuous and Continuous) and Borel (claims 3(a), 5 of The Borel Sigma-Algebra of a Euclidean Space as a Product, and Measurability of Projections, Sequentially Continuous Maps, and Open and Closed Sets).

(ii) On Δ\Delta, ℓk=−log⁡sk=k\ell_{k}=-\log s_{k}=k. Off Δ\Delta, ρ(z)>0\rho(z)>0 and ℓ(z)=−log⁡ρ(z)\ell(z)=-\log\rho(z); if ρ(z)≥sk\rho(z)\ge s_{k} then ℓk(z)=ℓ(z)≤k\ell_{k}(z)=\ell(z)\le k, and if ρ(z)<sk\rho(z)<s_{k} then ℓk(z)=k<ℓ(z)\ell_{k}(z)=k<\ell(z); so ℓk=min⁡{ℓ,k}\ell_{k}=\min\{\ell,k\} off Δ\Delta.

(iii) Put gk=ℓk+qg_{k}=\ell_{k}+q, a continuous Borel function. By (Q) and 0≤k0\le k, gk≥0g_{k}\ge0 everywhere: off Δ\Delta both ℓ\ell and kk are at least −q-q, and on Δ\Delta, gk=k+q≥0g_{k}=k+q\ge0. Also gk≤ℓ+qg_{k}\le\ell+q off Δ\Delta, and ℓ+q≥0\ell+q\ge0 everywhere by (Q).

Step 2 (Weak convergence of the product measures). We show that (μn⊠μn)n(\mu_{n}\boxtimes\mu_{n})_{n} converges weakly to μ⊠μ\mu\boxtimes\mu on (R2,dE)(\mathbb{R}^{2},d_{E}). For each nn let πn∈Π(μn,μ)\pi_{n}\in\Pi(\mu_{n},\mu) be an optimal coupling, I(πn)=W2(μn,μ)2I(\pi_{n})=W_{2}(\mu_{n},\mu)^{2}, given by Existence of an Optimal Coupling of Two Probability Measures with Finite Second Moment. Let F:R2→RF:\mathbb{R}^{2}\to\mathbb{R} be bounded, with bound BB, and Lipschitz with constant Λ\Lambda; it is continuous, hence Borel, as in Step 1(i). By claim 4 of Concatenation Identifies a Product of Euclidean Spaces with a Euclidean Space and claim 3 of Monotonicity of Squaring on the Nonnegative Elements of an Ordered Field, dE((x,y),(x,y′))=∣y−y′∣d_{E}((x,y),(x,y'))=|y-y'| and dE((x,y),(x′,y))=∣x−x′∣d_{E}((x,y),(x',y))=|x-x'|. Hence for each xx the function Fx(y)=F(x,y)+BF^{x}(y)=F(x,y)+B is bounded, nonnegative and Lipschitz with constant Λ\Lambda, and by Couplings on Euclidean Space: Product Coupling, Swap, Finiteness of the Cost, Push-Forward Couplings, Modifying One Marginal, Quantisation, Gluing over a Finitely Supported Measure, and the Lipschitz Bound (viii) (with d=1d=1 and πn\pi_{n})

∣∫Fx dμn−∫Fx dμ∣≤ΛI(πn)=Λ W2(μn,μ).\Bigl|\int F^{x}\,d\mu_{n}-\int F^{x}\,d\mu\Bigr|\le\Lambda\sqrt{I(\pi_{n})}=\Lambda\,W_{2}(\mu_{n},\mu).

Put Ψn(x)=∫Fx dμn\Psi_{n}(x)=\int F^{x}\,d\mu_{n} and Ψ(x)=∫Fx dμ\Psi(x)=\int F^{x}\,d\mu; they are Borel by (T), with values in [0,2B][0,2B], and ∣Ψ(x)−Ψ(x′)∣≤∫∣F(x,y)−F(x′,y)∣ μ(dy)≤Λ∣x−x′∣|\Psi(x)-\Psi(x')|\le\int|F(x,y)-F(x',y)|\,\mu(dy)\le\Lambda|x-x'| by claim 2 of Linearity and Monotonicity of the Lebesgue Integral, and the Integrability Criterion, so Ψ\Psi is bounded and Lipschitz with constant Λ\Lambda. By (T) applied to F+B≥0F+B\ge0 and claim 2 of Linearity and Monotonicity of the Lebesgue Integral, and the Integrability Criterion,

∣∫(F+B) d(μn⊠μn)−∫(F+B) d(μ⊠μ)∣≤∫∣Ψn−Ψ∣ dμn+∣∫Ψ dμn−∫Ψ dμ∣≤2Λ W2(μn,μ),\Bigl|\int(F+B)\,d(\mu_{n}\boxtimes\mu_{n})-\int(F+B)\,d(\mu\boxtimes\mu)\Bigr|\le\int|\Psi_{n}-\Psi|\,d\mu_{n}+\Bigl|\int\Psi\,d\mu_{n}-\int\Psi\,d\mu\Bigr|\le2\Lambda\,W_{2}(\mu_{n},\mu),

the second term by Couplings on Euclidean Space: Product Coupling, Swap, Finiteness of the Cost, Push-Forward Couplings, Modifying One Marginal, Quantisation, Gluing over a Finitely Supported Measure, and the Lipschitz Bound (viii) applied to Ψ\Psi. Since ∫(F+B) dλ=∫F dλ+B\int(F+B)\,d\lambda=\int F\,d\lambda+B for every probability measure λ\lambda on R2\mathbb{R}^{2}, and W2(μn,μ)→0W_{2}(\mu_{n},\mu)\to0, claim 3 of Order Properties of Limits of Real Sequences gives ∫F d(μn⊠μn)→∫F d(μ⊠μ)\int F\,d(\mu_{n}\boxtimes\mu_{n})\to\int F\,d(\mu\boxtimes\mu). As FF was an arbitrary bounded Lipschitz function, claim 1 of Portmanteau Theorem on a Metric Space gives the weak convergence.

Step 3 (A uniform bound). Put C1=c+1+M2(μ)C_{1}=c+1+M_{2}(\mu). By The Coordinate Fields of a Coupling, and the Second Moment as a Lipschitz Function of the Wasserstein Distance (ii), ∣M2(μn)−M2(μ)∣≤W2(μn,μ)|\sqrt{M_{2}(\mu_{n})}-\sqrt{M_{2}(\mu)}|\le W_{2}(\mu_{n},\mu), so M2(μn)→M2(μ)\sqrt{M_{2}(\mu_{n})}\to\sqrt{M_{2}(\mu)} by claim 3 of Order Properties of Limits of Real Sequences and M2(μn)→M2(μ)M_{2}(\mu_{n})\to M_{2}(\mu) by claim 2 of Arithmetic of Limits of Real Sequences. Let k,j∈Nk,j\in\mathbb{N} and fk,j=min⁡{gk,j}f_{k,j}=\min\{g_{k},j\}, which is continuous (claim 4 of Continuity of the Absolute Value, Maximum and Minimum of Real-Valued Functions on a Metric Space) with values in [0,j][0,j]. For each nn, μn∈Dlog⁡\mu_{n}\in\mathcal{D}_{\log} has no atoms, so (μn⊠μn)(Δ)=0(\mu_{n}\boxtimes\mu_{n})(\Delta)=0 by The Logarithmic Kernel on the Real Line: Borel Measurability, a Linear Lower Bound, and the Null Diagonal of an Atomless Measure (iii); by Step 1(iii), fk,j≤ℓ+qf_{k,j}\le\ell+q off Δ\Delta, so The Lebesgue Integral and Null Sets (iii) gives ∫fk,j d(μn⊠μn)≤∫(ℓ+q) d(μn⊠μn)\int f_{k,j}\,d(\mu_{n}\boxtimes\mu_{n})\le\int(\ell+q)\,d(\mu_{n}\boxtimes\mu_{n}), where the right side, the integral of a nonnegative integrable function, equals Elog⁡(μn)+1+M2(μn)≤c+1+M2(μn)\mathcal{E}_{\log}(\mu_{n})+1+M_{2}(\mu_{n})\le c+1+M_{2}(\mu_{n}) by Step 0 and claim 2 of Linearity and Monotonicity of the Lebesgue Integral, and the Integrability Criterion. By Step 2 and the definition of weak convergence, claim 1 of Order Properties of Limits of Real Sequences and claim 1 of Arithmetic of Limits of Real Sequences, ∫fk,j d(μ⊠μ)≤C1\int f_{k,j}\,d(\mu\boxtimes\mu)\le C_{1}. For fixed kk, (fk,j)j(f_{k,j})_{j} is nondecreasing with supremum gkg_{k} (claim 1 of The Archimedean Property of the Real Numbers), so Monotone Convergence Theorem gives

∫gk d(μ⊠μ)≤C1(k∈N).(B)\int g_{k}\,d(\mu\boxtimes\mu)\le C_{1}\qquad(k\in\mathbb{N}).\tag{B}

Step 4 (μ\mu has no atoms). Suppose p=μ({a})>0p=\mu(\{a\})>0 for some a∈Ra\in\mathbb{R}. The set S=ι({a}×{a})S=\iota(\{a\}\times\{a\}) is Borel with (μ⊠μ)(S)=p2>0(\mu\boxtimes\mu)(S)=p^{2}>0 (Pairs of Euclidean Points: Coordinate Projections, Pairings, the Product Measure on a Euclidean Space, Borel Norm Functions and Finite Sets (iii), Pairs of Euclidean Points: Coordinate Projections, Pairings, the Product Measure on a Euclidean Space, Borel Norm Functions and Finite Sets (v)), and S={(a,a)}⊆ΔS=\{(a,a)\}\subseteq\Delta, where gk(a,a)=k+q(a,a)≥kg_{k}(a,a)=k+q(a,a)\ge k by Step 1(ii). So gk≥k1Sg_{k}\ge k\mathbf{1}_{S} and (B) gives kp2≤C1kp^{2}\le C_{1} for every k∈Nk\in\mathbb{N}, contradicting claim 2 of The Archimedean Property of the Real Numbers. Hence μ({a})=0\mu(\{a\})=0 for every aa, and (μ⊠μ)(Δ)=0(\mu\boxtimes\mu)(\Delta)=0 by The Logarithmic Kernel on the Real Line: Borel Measurability, a Linear Lower Bound, and the Null Diagonal of an Atomless Measure (iii).

Step 5 (μ∈Dlog⁡\mu\in\mathcal{D}_{\log} and Elog⁡(μ)≤c\mathcal{E}_{\log}(\mu)\le c). Let uk=gk1R2∖Δu_{k}=g_{k}\mathbf{1}_{\mathbb{R}^{2}\setminus\Delta}. By Step 1(ii), off Δ\Delta, uk=min⁡{ℓ,k}+qu_{k}=\min\{\ell,k\}+q, which is nondecreasing in kk and equals ℓ+q\ell+q once k>ℓk>\ell (claim 1 of The Archimedean Property of the Real Numbers); on Δ\Delta, uk=0u_{k}=0. So (uk)k(u_{k})_{k} is nondecreasing with supremum v=(ℓ+q)1R2∖Δv=(\ell+q)\mathbf{1}_{\mathbb{R}^{2}\setminus\Delta}, and Monotone Convergence Theorem, uk≤gku_{k}\le g_{k} and (B) give ∫v d(μ⊠μ)≤C1\int v\,d(\mu\boxtimes\mu)\le C_{1}. As ℓ+q=v\ell+q=v off the null set Δ\Delta and both are nonnegative, The Lebesgue Integral and Null Sets (iii) gives ∫(ℓ+q) d(μ⊠μ)≤C1<∞\int(\ell+q)\,d(\mu\boxtimes\mu)\le C_{1}<\infty, so ℓ+q\ell+q is μ⊠μ\mu\boxtimes\mu-integrable (Integrable Functions and Their Lebesgue Integral). By Step 0 and claim 2 of Linearity and Monotonicity of the Lebesgue Integral, and the Integrability Criterion, ℓ=(ℓ+q)−q\ell=(\ell+q)-q is integrable with ∫ℓ d(μ⊠μ)≤C1−(1+M2(μ))=c\int\ell\,d(\mu\boxtimes\mu)\le C_{1}-(1+M_{2}(\mu))=c. Since μ∈P2(R)\mu\in\mathcal{P}_{2}(\mathbb{R}) and μ\mu has no atoms (Step 4), The Logarithmic Energy of a Probability Measure on the Real Line (i) gives μ∈Dlog⁡\mu\in\mathcal{D}_{\log} and Elog⁡(μ)≤c\mathcal{E}_{\log}(\mu)\le c.

Clause 4. Let μ∈Dlog⁡\mu\in\mathcal{D}_{\log} and ε>0\varepsilon>0, and suppose that no δ>0\delta>0 has the property required in Lower Semicontinuous Function on a Subset of a Metric Space. Then for every j∈Nj\in\mathbb{N} the set AjA_{j} of those ν∈Dlog⁡\nu\in\mathcal{D}_{\log} with W2(μ,ν)<1/(j+1)W_{2}(\mu,\nu)<1/(j+1) and Elog⁡(ν)≤Elog⁡(μ)−ε\mathcal{E}_{\log}(\nu)\le\mathcal{E}_{\log}(\mu)-\varepsilon is nonempty, the order of R\mathbb{R} being total. By Axiom of Countable Choice there are μj∈Aj\mu_{j}\in A_{j} for all jj. Given ε′>0\varepsilon'>0, claim 2 of The Archimedean Property of the Real Numbers gives NN with 1<Nε′1<N\varepsilon', so W2(μj,μ)=W2(μ,μj)<1/(j+1)<ε′W_{2}(\mu_{j},\mu)=W_{2}(\mu,\mu_{j})<1/(j+1)<\varepsilon' for j≥Nj\ge N (The Quadratic Wasserstein Distance is a Metric on the Wasserstein Space (i)); thus (W2(μj,μ))j(W_{2}(\mu_{j},\mu))_{j} has limit 00. Clause 3 with c=Elog⁡(μ)−εc=\mathcal{E}_{\log}(\mu)-\varepsilon gives Elog⁡(μ)≤Elog⁡(μ)−ε\mathcal{E}_{\log}(\mu)\le\mathcal{E}_{\log}(\mu)-\varepsilon, which contradicts ε>0\varepsilon>0. Hence Elog⁡\mathcal{E}_{\log} is lower semicontinuous at every μ∈Dlog⁡\mu\in\mathcal{D}_{\log} relative to Dlog⁡\mathcal{D}_{\log}, that is, lower semicontinuous on Dlog⁡\mathcal{D}_{\log}.

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