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Lower semicontinuity of logarithmic potential and energy

Statement

Let K⊆C be nonempty compact and let μn,μ be Borel probability measures on K with μn⇒μ. With the Borel kernel k(z,w)=log⁡1∣z−w∣ assigned +∞ on the diagonal, the extended integrals Uμ(z)=∫Ck(z,w) dμ(w) and I(μ)=∬C×Ck dμ⊗dμ of Logarithmic potential and energy of a positive compactly supported measure are unambiguous: for each fixed z, a Borel function of w that equals k(z,w) for μ-almost every w gives the same potential at z; a Borel kernel equal to k for (μ⊗μ)-almost every (z,w) gives the same energy. Moreover

Uμ(z)≤lim inf⁡n→∞Uμn(z)(z∈C),I(μ)≤lim inf⁡n→∞I(μn).

Finally, if μ({z})>0 for some z then Uμ(z)=+∞, so for atomic measures the diagonal value is not a free convention. No choice principle is required.

Facts & Assumptions

Given: a nonempty compact K⊆C, Borel probability measures μn,μ on K with μn⇒μ, and the kernel, potential and energy conventions of Logarithmic potential and energy of a positive compactly supported measure.

[F1]

On a compactly supported finite positive measure ν, the potential Uν(z)=∫k(z,w) dν(w) is the extended integral of the Borel kernel with diagonal value +∞, and for R>diam⁡supp⁡ν the energy satisfies I(ν)=∬kR dν⊗dν−ν(C)2log⁡R with kR=k+log⁡R (Logarithmic potential and energy of a positive compactly supported measure).

[F2]

For Borel probability measures on a metric space, μn⇒μ means ∫f dμn→∫f dμ for every bounded continuous real f (Weak convergence of borel probability measures).

[F3]

A Borel probability measure has total mass one (Probability measures and probability spaces).

[F4]

The integral over a measurable null set vanishes, and the nonnegative integral is additive (A nonnegative integral over a null set vanishes, Additivity of the nonnegative Lebesgue integral).

[F6]

Monotone convergence: for 0≤fM↑f pointwise measurable, ∫fM dμ↑∫f dμ (Monotone convergence for the integral).

[F7]

A unital point-separating subalgebra of C(K,R) on a nonempty compact metric space is uniformly dense (Real Stone--Weierstrass theorem for compact metric spaces).

[F8]

A finite product of nonempty compact spaces is compact (A product of finitely many compact spaces is compact in the product topology).

[F9]

For a product-integrable function the iterated and product integrals agree (Fubini's theorem for L^1 functions on a sigma-finite product).

[F10]

The product measure μ⊗μ is a measure on the product σ-algebra (The product measure of two sigma-finite measure spaces).

Proof

technique · direct
1.1F1F3given

Let K, μn, μ and ⇒ be as given, fix R>diam⁡K, and set k(z,w):=log⁡1∣z−w∣, kR:=k+log⁡R, Uν(z):=∫k(z,w) dν(w) and I(ν):=∬k dν⊗dν in the conventions of [F1]; then I(ν)=∬kR dν⊗dν−log⁡R for every Borel probability ν on K.

1.2F7F8algebra

The finite sums ∑ifi(z)hi(w) of continuous functions fi,hi on K form a unital subalgebra of C(K×K,R) separating points, so it is uniformly dense by [F7], since K×K is a nonempty compact metric space.

2.1step 1.1F1

The shifted kernel kR(z,w)=log⁡R∣z−w∣ is Borel, nonnegative on K×K, and equal to +∞ exactly on the diagonal.

2.2F4step 1.1algebra

If nonnegative measurable functions f,g agree off a null set E, then ∫f=∫X∖Ef+∫Ef=∫X∖Eg+0=∫g by [F4]; hence, for each fixed z, Borel functions of w agreeing with k(z,w) μ-almost everywhere produce the same value of Uμ(z), and Borel kernels agreeing with k (μ⊗μ)-almost everywhere produce the same energy.

2.3step 1.1F5algebra

Fix z∈C and choose Rz>sup⁡w∈K∣z−w∣; for M>0 the truncation φM(w):=min⁡{M,log⁡Rz∣z−w∣} is continuous on K and bounded by M, because it equals M near w=z and is a minimum of continuous functions elsewhere, and Uν(z)≥∫φM dν−log⁡Rz for every Borel probability ν on K.

2.4step 1.2F2F9F10algebra

For such a finite sum h=∑ifihi, [F9] and [F10] give ∬h dμn⊗dμn=∑i(∫fi dμn)(∫hi dμn)→∑i(∫fi dμ)(∫hi dμ)=∬h dμ⊗dμ.

3.1step 2.3F2algebra

Since φM is bounded and continuous, the weak convergence μn⇒μ gives ∫φM dμn→∫φM dμ, hence lim inf⁡nUμn(z)≥∫φM dμ−log⁡Rz for every M.

3.2step 2.1F5algebra

For M>0 put gM(z,w):=min⁡{M,kR(z,w)}; it is continuous on K×K, bounded by M, and I(ν)+log⁡R=∬kR dν⊗dν≥∬gM dν⊗dν for every Borel probability ν on K.

3.3step 1.2step 2.4algebra

Given ε>0, step 1.2 provides h with ∣gM−h∣≤ε on K×K and hence ∣∬gM dμn⊗dμn−∬gM dμ⊗dμ∣≤2ε+∣∬h dμn⊗dμn−∬h dμ⊗dμ∣, so step 2.4 makes the left side tend to 0: ∬gM dμn⊗dμn→∬gM dμ⊗dμ.

4.1step 3.1step 1.1F6algebra

As M→∞ one has φM↑log⁡Rz∣z−w∣ pointwise, so [F6] gives ∫φM dμ↑∫log⁡Rz∣z−w∣ dμ(w)=log⁡Rz+Uμ(z) in the extended sense; combining with step 3.1 yields Uμ(z)≤lim inf⁡nUμn(z) for every z∈C.

4.2step 3.2step 3.3step 1.1F6algebra

Therefore lim inf⁡n(I(μn)+log⁡R)≥∬gM dμ⊗dμ for every M; since gM↑kR pointwise, [F6] gives ∬gM dμ⊗dμ↑∬kR dμ⊗dμ=I(μ)+log⁡R, so I(μ)≤lim inf⁡nI(μn).

5.1step 1.1F1algebra∎

If μ({z})>0, the diagonal value of the kernel gives Uμ(z)≥k(z,z)μ({z})=+∞; for μ=δz, replacing k(z,z)=+∞ by a finite value c changes Uμ(z) from +∞ to c, so the diagonal value cannot be assigned freely for the class of atomic measures.

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