SHARP DIMENSION FREE QUANTITATIVE ESTIMATES FOR THE GAUSSIAN ISOPERIMETRIC INEQUALITY
Marco Barchiesi, See Profile, Marco Barchiesi, Alessio Brancolini, Vesa Julin
Abstract
Marco Barchiesi, See Profile, Marco Barchiesi, Alessio Brancolini, Vesa Julin
Abstract
Abstract. We provide a full quantitative version of the Gaussian isoperimetric in-equality: the difference between the Gaussian perimeter of a given set and a half-space with the same mass controls the gap between the norms of the corresponding barycenters. In particular, it controls the Gaussian measure of the symmetric dif-ference between the set and the half-space oriented so to have the barycenter in the same direction of the set. Our estimate is independent of the dimension, sharp on the decay rate with respect to the gap and with optimal dependence on the mass. 2010 Mathematics Subject Class. 49Q20, 60E15. 1.
OpenAlex reports 52 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Abstract. We provide a full quantitative version of the Gaussian isoperimetric in-equality: the difference between the Gaussian perimeter of a given set and a half-space with the same mass controls the gap between the norms of the corresponding barycenters. In particular, it controls the Gaussian measure of the symmetric dif-ference between the set and the half-space oriented so to have the barycenter in the same direction of the set. Our estimate is independent of the dimension, sharp on the decay rate with respect to the gap and with optimal dependence on the mass. 2010 Mathematics Subject Class. 49Q20, 60E15. 1.
Key concepts: Isoperimetric inequality, Mathematics, Gaussian measure, Gaussian, Isoperimetric dimension, Dimension (graph theory), Measure (data warehouse), Mathematical analysis