Math 2.0

Potential theory Definition

Robin constant

Builds on Compact setProbability measureEnergy of a measure

Definition

Let KK be a compact set in ℂ\C. For a Borel probability measure μ\mu on KK, let I(μ)=∫K∫Klog⁡1∣z−w∣ dμ(z) dμ(w)I(\mu) = \int_K \int_K \log \frac{1}{\abs{z - w}} \, d\mu(z) \, d\mu(w) be its logarithmic energy, with values in (−∞,∞](-\infty, \infty]. The Robin constant of KK is V(K)=inf⁡{I(μ):μ a Borel probability measure on K},V(K) = \inf \set{ I(\mu) : \mu \text{ a Borel probability measure on } K }, with V(K)=∞V(K) = \infty when I(μ)=∞I(\mu) = \infty for every such μ\mu.

Remarks

The logarithmic capacity of KK is cap⁡(K)=e−V(K)\operatorname{cap}(K) = e^{-V(K)}. If V(K)<∞V(K) < \infty and Ω\Omega is the unbounded component of ℂ^∖K\hat\C \setminus K, the Green function of Ω\Omega with pole at infinity satisfies gΩ(z,∞)=log⁡∣z∣+V(K)+o(1)g_\Omega(z, \infty) = \log \abs{z} + V(K) + o(1) as z→∞z \to \infty.

Example: let KK be the circle of radius rr centred at 00 and let μ\mu be normalized arc length on it. For ∣z∣=r\abs{z} = r the mean value of log⁡(1/∣z−w∣)\log(1/\abs{z - w}) over the circle is −log⁡r-\log r, so I(μ)=−log⁡rI(\mu) = -\log r. This μ\mu is the minimizer, so V(K)=−log⁡rV(K) = -\log r. The Green function log⁡(∣z∣/r)\log(\abs{z}/r) of the outside of the circle agrees with the expansion above.

Non-example of a finite value: for K={0}K = \set{0} the only probability measure is δ0\delta_0, and I(δ0)=log⁡(1/0)=∞I(\delta_0) = \log(1/0) = \infty, so V(K)=∞V(K) = \infty.

Some authors use the opposite sign or the energy kernel log⁡∣z−w∣\log \abs{z - w}, so that the Robin constant becomes log⁡cap⁡(K)\log \operatorname{cap}(K).

Reading path

To understand this page from the ground up, read these 4 pages in order. The foundations come first.

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  1. Compact set concept
  2. Energy of a measure concept
  3. Probability measure concept
  4. Robin constant definition

Further reading

  1. Web https://en.wikipedia.org/wiki/Conformal_radius
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MSC31A15, 30C85
DefinesRobin constant
UsesCompact set, Probability measure, Energy of a measure

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