Symmetrization methods
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Comment: The first paragraph sounds more like a journal or report rather than a formal encyclopedia article and also needs better information for viewers unfamiliar with the subject. This could also use any more available sources overall. Cheers, SwisterTwister talk 23:51, 17 November 2015 (UTC)
In mathematics the symmetrization methods are algorithms of transforming a set to a ball with . These algorithms show up in solving the following types of problems: The classical isoperimetric inequality problem asks: Given all shapes of a given area, which of them has the minimal perimeter (for details see Isoperimetric inequality). The conjectured answer was the disk and Steiner in 1838 showed this to be true using the Steiner symmetrization method (described below). From this many other isoperimetric problems sprung and other symmetrization algorithms. For example, Rayleigh's conjecture is that the first eigenvalue of the Dirichlet problem is minimized for the ball (see Rayleigh–Faber–Krahn inequality for details). Another problem is that electrostatic capacity is minimized by the ball and this was proved by Polya and G. Szego (1951) using circular symmetrization (described below).
Symmetrization
Let be measurable, then we denote by the symmetrized version of i.e. a ball such that . We denote by the symmetric decreasing rearrangement of nonnegative measurable function f and define it as . The following methods have been proved to transform to i.e. given a sequence of symmetrization transformations we have , where is the Hausdorff distance (for discussion see Burchard (2009) )
Steiner Symmetrization

Steiner symmetrization was introduced by Steiner (1838) to solve the isoperimetric theorem stated above. Let be a hyperplane through the origin. Rotate space so that is the hyperplane. For each let the perpendicular line through be . Then by replacing each by a line centered at H and with length we obtain the Steiner symmetrized version.
We denote by the Steiner symmetrization wrt to hyperplane of nonnegative measurable function and for fixed define it as
Circular Symmetrization

A popular method for symmetrization in the plane is Polya's circular symmetrization. After we will describe its generalization to higher dimensions. Let be a domain then we define its circular symmetrization wrt to the positive real axis as follows: Let
i.e. contain the arcs of radius t contained in . So we define
- If is the full circle, then .
- If the length is , then .
- iff .
In higher dimensions , we define its spherical symmetrization wrt to positive axis of as follows: Let i.e. contain the caps of radius r contained in . Also, for the first coordinate let if . So as above
- If is the full cap, then .
- If the surface area is , then and where is picked so that its surface area is . In words, is a cap symmetric around the positive axis with the same area as the intersection .
- iff .
Polarization

Let be a domain and be a hyperplane through the origin. Denote the reflection across that plane to the positive halfspace as or just when it is clear from the context. Also, we denote the reflected across hyperplane H as . Then, we denote the polarized as and define it as follows
- If , then .
- If , then .
- If , then .
In words, we simply reflect to the halfspace .
References
- Morgan, Frank (2009). "Symmetrization". Retrieved November 2015.
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(help) - Burchard, Almut (2009). "A Short Course on Rearrangement Inequalities" (PDF). Retrieved November 2015.
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- Kojar, Tomas (2015). "Brownian Motion and Symmetrization". Retrieved November 2015.
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