English

Gain/Loss of derivatives for complex vector fields

Complex Variables 2014-06-13 v2

Abstract

In \Cz×Rt\C_z\times\R_t we consider the function g=g(z)g=g(z), set g1=\dizgg_1=\di_z g, g11ˉ=\diz\dibzgg_{1\bar 1}=\di_z\dib_zg and define the operator Lg=\diz+ig1\ditL_g=\di_z+ig_1\di_t. We discuss estimates with loss of derivatives, in the sense of Kohn, for the system (Lˉg,fkLg)(\bar L_g,f^kL_g) where (Lˉg,Lg)(\bar L_g,L_g) is 12m\frac1{2m} subelliptic at 0 and f(0)=0,df(0)0f(0)=0,\,\,df(0)\neq0. We prove estimates with a loss l=k12ml=\frac{k-1}{2m} if the "multiplier" condition f\simgeqg11ˉ12(m1)|f|\simgeq |g_{1\bar 1}|^{\frac1{2(m-1)}} is fulfilled. (For estimates without cut-off, subellipticity can be weakened to compactness and this results in a loss of l=[2(m1)l=\frac [{2(m-1)}.) For the choice (g,fk)=(z2m,zˉk)(g,f^k)=(|z|^{2m},\bar z^k) this result was obtained by Kohn and Bove-Derridj-Kohn-Tartakoff for m=1m=1 and m1m\geq1 respectively. Also, the loss l=k12ml=\frac{k-1}{2m} was proven to be optimal. We show that it remains optimal for the model (g,fk)=(x2m,xk)(g,f^k)=(x^{2m},x^k). Instead, for the model (g,fk)=(z2m,xk)(g,f^k)=(|z|^{2m},x^k), in which the multiplier condition is violated, the loss is not lowered by the type and must be k12\geq \frac{k-1}2.

Cite

@article{arxiv.1208.5938,
  title  = {Gain/Loss of derivatives for complex vector fields},
  author = {Luca Baracco and Giuseppe Zampieri},
  journal= {arXiv preprint arXiv:1208.5938},
  year   = {2014}
}

Comments

The paper contains an error in the proof of Theorem 2.5: estimate (2.16) (a) is incorrect. This misses the proof of the optimality of the loss of derivatives which was a major point of the submission

R2 v1 2026-06-21T21:56:52.826Z