Quadratic NLS: Difference between revisions

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====Quadratic NLS on <math>R^2</math>====
====Quadratic NLS on <math>R^2</math>====


* Scaling is s<sub>c</sub> = -1.
* Scaling <math>s_c = -1.\,</math>
* For any quadratic non-linearity one can obtain LWP for s <font face="Symbol">³</font> 0 [[Bibliography#CaWe1990|CaWe1990]], [[Bibliography#Ts1987|Ts1987]].
* For any quadratic non-linearity one can obtain LWP for <math>s>=0\,</math> [[Bibliography#CaWe1990|CaWe1990]], [[Bibliography#Ts1987|Ts1987]].
** In the Hamiltonian case (|u| u) this is sharp by Gallilean invariance considerations [KnPoVe-p]
** In the Hamiltonian case (<math>|u| u\,</math>) this is sharp by Gallilean invariance considerations [KnPoVe-p]
* If the quadratic non-linearity is of <u>u</u> <u>u</u> or u u type then one can push LWP to s > -3/4. [[Bibliography#St1997|St1997]], [[references:CoDeKnSt-p CoDeKnSt-p]].
* If the quadratic non-linearity is of <math>\underline{uu}\,</math> or <math>u u\,</math> type then one can push LWP to <math>s > -3/4.\,</math> [[Bibliography#St1997|St1997]], [[references:CoDeKnSt-p CoDeKnSt-p]].
** This can be improved to the Besov space B^{-3/4}_{2,1} [MurTao-p].
** This can be improved to the Besov space <math>B^{-3/4}_{2,1}\,</math> [MurTao-p].
* If the quadratic non-linearity is of u <u>u</u> type then one can push LWP to s > -1/4. [[references:Ta-p2 Ta-p2]].
* If the quadratic non-linearity is of <math>u \underline{u}\,</math> type then one can push LWP to <math>s > -1/4.\,</math> [[references:Ta-p2 Ta-p2]].
* In the Hamiltonian case (a non-linearity of type |u| u) we have GWP for s <font face="Symbol">³</font> 0 by L<sup>2</sup> conservation. In the other cases it is not clear whether there is any reasonable GWP result, except possibly for very small data.
* In the Hamiltonian case (a non-linearity of type <math>|u| u\,</math>) we have GWP for <math>s>= 0\,</math> by <math>L^2\,</math> conservation. In the other cases it is not clear whether there is any reasonable GWP result, except possibly for very small data.
** Below L^2 we have ill-posedness by Gallilean invariance considerations in both the focusing [KnPoVe-p] and defocusing [CtCoTa-p2] cases.
** Below <math>L^2\,</math> we have ill-posedness by Gallilean invariance considerations in both the focusing [KnPoVe-p] and defocusing [CtCoTa-p2] cases.


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[[Category:Equations]]
[[Category:Equations]]


====Quadratic NLS on T^2====
====Quadratic NLS on T^2====

Revision as of 20:43, 29 July 2006

Quadratic NLS

Equations of the form

Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://en.wikipedia.org/api/rest_v1/":): {\displaystyle i \partial_t u + \Delta u = Q(u, \overline{u})}

which Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://en.wikipedia.org/api/rest_v1/":): {\displaystyle Q(u, \overline{u})} a quadratic function of its arguments are quadratic nonlinear Schrodinger equations.


Quadratic NLS on R

  • Scaling is
  • For any quadratic non-linearity one can obtain LWP for CaWe1990, Ts1987.
  • If the quadratic non-linearity is of or type then one can push LWP to KnPoVe1996b.
    • This can be improved to the Besov space [MurTao-p]. The bilinear estimates fail for references:NaTkTs-p NaTkTs2001.
  • If the quadratic non-linearity is of type then one can push LWP to KnPoVe1996b.
  • Since these equations do not have conservation it is not clear whether there is any reasonable GWP result, except possibly for very small data.
  • If the non-linearity is then there is GWP in thanks to conservation, and ill-posedness below by Gallilean invariance considerations in both the focusing [KnPoVe-p] and defocusing [CtCoTa-p2] cases.

Quadratic NLS on

  • For any quadratic non-linearity one can obtain LWP for Bo1993. In the Hamiltonian case () this is sharp by Gallilean invariance considerations [KnPoVe-p]
  • If the quadratic non-linearity is of or type then one can push LWP to KnPoVe1996b.
  • In the Hamiltonian case (a non-linearity of type ) we have GWP for by conservation. In the other cases it is not clear whether there is any reasonable GWP result, except possibly for very small data.

Quadratic NLS on

  • Scaling
  • For any quadratic non-linearity one can obtain LWP for CaWe1990, Ts1987.
    • In the Hamiltonian case () this is sharp by Gallilean invariance considerations [KnPoVe-p]
  • If the quadratic non-linearity is of or type then one can push LWP to St1997, references:CoDeKnSt-p CoDeKnSt-p.
    • This can be improved to the Besov space [MurTao-p].
  • If the quadratic non-linearity is of type then one can push LWP to references:Ta-p2 Ta-p2.
  • In the Hamiltonian case (a non-linearity of type ) we have GWP for by conservation. In the other cases it is not clear whether there is any reasonable GWP result, except possibly for very small data.
    • Below we have ill-posedness by Gallilean invariance considerations in both the focusing [KnPoVe-p] and defocusing [CtCoTa-p2] cases.

Quadratic NLS on T^2


Quadratic NLS on

  • Scaling is sc = -1/2.
  • For any quadratic non-linearity one can obtain LWP for s ³ 0 CaWe1990, Ts1987.
  • If the quadratic non-linearity is of u u or u u type then one can push LWP to s > -1/2. St1997, references:CoDeKnSt-p CoDeKnSt-p.
  • If the quadratic non-linearity is of u u type then one can push LWP to s > -1/4. references:Ta-p2 Ta-p2.
  • In the Hamiltonian case (a non-linearity of type |u| u) we have GWP for s ³ 0 by L2 conservation. In the other cases it is not clear whether there is any reasonable GWP result, except possibly for very small data.
    • Below L^2 we have ill-posedness by Gallilean invariance considerations in both the focusing [KnPoVe-p] and defocusing [CtCoTa-p2] cases.

Quadratic NLS on Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://en.wikipedia.org/api/rest_v1/":): {\displaystyle T^3}