Large data local solutions for the derivative NLS equation

Ioan Bejenaru; Daniel Tataru

Journal of the European Mathematical Society (2008)

  • Volume: 010, Issue: 4, page 957-985
  • ISSN: 1435-9855

Abstract

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We consider the derivative NLS equation with general quadratic nonlinearities. In [2] the first author has proved a sharp small data local well-posedness result in Sobolev spaces with a decay structure at infinity in dimension n = 2 . Here we prove a similar result for large initial data in all dimensions n 2 .

How to cite

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Bejenaru, Ioan, and Tataru, Daniel. "Large data local solutions for the derivative NLS equation." Journal of the European Mathematical Society 010.4 (2008): 957-985. <http://eudml.org/doc/277672>.

@article{Bejenaru2008,
abstract = {We consider the derivative NLS equation with general quadratic nonlinearities. In [2] the first author has proved a sharp small data local well-posedness result in Sobolev spaces with a decay structure at infinity in dimension $n=2$. Here we prove a similar result for large initial data in all dimensions $n\ge 2$.},
author = {Bejenaru, Ioan, Tataru, Daniel},
journal = {Journal of the European Mathematical Society},
language = {eng},
number = {4},
pages = {957-985},
publisher = {European Mathematical Society Publishing House},
title = {Large data local solutions for the derivative NLS equation},
url = {http://eudml.org/doc/277672},
volume = {010},
year = {2008},
}

TY - JOUR
AU - Bejenaru, Ioan
AU - Tataru, Daniel
TI - Large data local solutions for the derivative NLS equation
JO - Journal of the European Mathematical Society
PY - 2008
PB - European Mathematical Society Publishing House
VL - 010
IS - 4
SP - 957
EP - 985
AB - We consider the derivative NLS equation with general quadratic nonlinearities. In [2] the first author has proved a sharp small data local well-posedness result in Sobolev spaces with a decay structure at infinity in dimension $n=2$. Here we prove a similar result for large initial data in all dimensions $n\ge 2$.
LA - eng
UR - http://eudml.org/doc/277672
ER -

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