Optimal design for the planar Skorokhod embedding problem
Maher Boudabra

TL;DR
This paper introduces a variational framework for the planar Skorokhod embedding problem, identifying optimal domains that minimize area and boundary energy, and explores implications for Brownian symmetrization and geometric inequalities.
Contribution
It establishes a variational characterization of the Gross domain as area-minimizing among simply connected domains, linking it to fractional Sobolev spaces and optimal design.
Findings
Gross domain uniquely minimizes area among simply connected $oldsymbol{ extmu}$-domains.
Gross area is minimized by the shifted arcsine distribution within the Schlicht class.
Brownian symmetrization is area-nonincreasing and dominates Steiner symmetrization.
Abstract
We revisit the planar Skorokhod embedding problem introduced by Gross and developed further by Boudabra-Markowsky, and we place it in a fully variational framework. For a centered probability measure with finite second moment, we show that Gross' -domain uniquely minimizes the area among all simply connected -domains. Equivalently, minimizes a natural -type boundary energy, providing an optimal design interpretation of the planar Skorokhod embedding problem. The proof relies on the Fourier characterization of fractional Sobolev spaces on the circle, symmetric decreasing rearrangement of the quantile of , and a one-dimensional fractional inequality. Within the Schlicht class, we obtain a sharp model case: under a natural normalization of the quantile, the Gross area is uniquely minimized by the…
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Taxonomy
TopicsNonlinear Partial Differential Equations · Stochastic processes and statistical mechanics · Stochastic processes and financial applications
