Large-data equicontinuity for the derivative NLS
Harrop-Griffiths B, Killip R, Vişan M. 2023. Large-data equicontinuity for the derivative NLS. International Mathematics Research Notices. 2023(6), 4601–4642.
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Author
Harrop-Griffiths, Benjamin;
Killip, Rowan;
Vişan, MonicaISTA
Abstract
We consider the derivative nonlinear Schrödinger equation in one spatial dimension, which is known to be completely integrable. We prove that the orbits of L^2 bounded and equicontinuous sets of initial data remain bounded and equicontinuous, not only under this flow, but also under the entire hierarchy. This allows us to remove the small-data restriction from prior conservation laws and global well-posedness results.
Publishing Year
Date Published
2023-03-01
Journal Title
International Mathematics Research Notices
Publisher
Oxford University Press
Volume
2023
Issue
6
Page
4601-4642
ISSN
eISSN
IST-REx-ID
Cite this
Harrop-Griffiths B, Killip R, Vişan M. Large-data equicontinuity for the derivative NLS. International Mathematics Research Notices. 2023;2023(6):4601-4642. doi:10.1093/imrn/rnab374
Harrop-Griffiths, B., Killip, R., & Vişan, M. (2023). Large-data equicontinuity for the derivative NLS. International Mathematics Research Notices. Oxford University Press. https://doi.org/10.1093/imrn/rnab374
Harrop-Griffiths, Benjamin, Rowan Killip, and Monica Vişan. “Large-Data Equicontinuity for the Derivative NLS.” International Mathematics Research Notices. Oxford University Press, 2023. https://doi.org/10.1093/imrn/rnab374.
B. Harrop-Griffiths, R. Killip, and M. Vişan, “Large-data equicontinuity for the derivative NLS,” International Mathematics Research Notices, vol. 2023, no. 6. Oxford University Press, pp. 4601–4642, 2023.
Harrop-Griffiths B, Killip R, Vişan M. 2023. Large-data equicontinuity for the derivative NLS. International Mathematics Research Notices. 2023(6), 4601–4642.
Harrop-Griffiths, Benjamin, et al. “Large-Data Equicontinuity for the Derivative NLS.” International Mathematics Research Notices, vol. 2023, no. 6, Oxford University Press, 2023, pp. 4601–42, doi:10.1093/imrn/rnab374.
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