Symmetric Convex Sets with Minimal Gaussian Surface Area
Abstract
Let ⊂Rn+1 have minimal Gaussian surface area among all sets satisfying =- with fixed Gaussian volume. Let A=Ax be the second fundamental form of ∂ at x, i.e. A is the matrix of first order partial derivatives of the unit normal vector at x∈∂. For any x=(x1,…,xn+1)∈Rn+1, let γn(x)=(2π)-n/2e-(x12+·s+xn+12)/2. Let \|A\|2 be the sum of the squares of the entries of A, and let \|A\|2 2 denote the 2 operator norm of A. It is shown that if or c is convex, and if either ∫∂(\|Ax\|2-1)γn(x)dx>0or ∫∂(\|Ax\|2-1+2y∈∂\|Ay\|2 22)γn(x)dx<0, then ∂ must be a round cylinder. That is, except for the case that the average value of \|A\|2 is slightly less than 1, we resolve the convex case of a question of Barthe from 2001. The main tool is the Colding-Minicozzi theory for Gaussian minimal surfaces, which studies eigenfunctions of the Ornstein-Uhlenbeck type operator L= - x,∇ +\|A\|2+1 associated to the surface ∂. A key new ingredient is the use of a randomly chosen degree 2 polynomial in the second variation formula for the Gaussian surface area. Our actual results are a bit more general than the above statement. Also, some of our results hold without the assumption of convexity.