Maximizers for the Strichartz norm for small solutions of mass-critical NLS

Mathematics – Analysis of PDEs

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

To be published in Annali della Scuola Normale Superiore di Pisa

Scientific paper

Consider the mass-critical nonlinear Schr\"odinger equations in both focusing and defocusing cases for initial data in $L^2$ in space dimension N. By Strichartz inequality, solutions to the corresponding linear problem belong to a global $L^p$ space in the time and space variables, where $p=2+4/N$. In 1D and 2D, the best constant for the Strichartz inequality was computed by D.~Foschi who has also shown that the maximizers are the solutions with Gaussian initial data. Solutions to the nonlinear problem with small initial data in $L^2$ are globally defined and belong to the same global $L^p$ space. In this work we show that the maximum of the $L^p$ norm is attained for a given small mass. In addition, in 1D and 2D, we show that the maximizer is unique and obtain a precise estimate of the maximum. In order to prove this we show that the maximum for the linear problem in 1D and 2D is nondegenerated.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Maximizers for the Strichartz norm for small solutions of mass-critical NLS does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Maximizers for the Strichartz norm for small solutions of mass-critical NLS, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Maximizers for the Strichartz norm for small solutions of mass-critical NLS will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-727408

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.