Every P-convex subset of \({\mathbb{R}^2}\) is already strongly P-convex

Abstract

A classical result of Malgrange says that for a polynomial P and an open subset Ω of \({\mathbb{R}^d}\) the differential operator P(D) is surjective on C (Ω) if and only if Ω is P-convex. Hörmander showed that P(D) is surjective as an operator on \({\fancyscript{D}'(\Omega)}\) if and only if Ω is strongly P-convex. It is well known that the natural question whether these two notions coincide has to be answered in the negative in general. However, Trèves conjectured that in the case of d = 2 P-convexity and strong P-convexity are equivalent. A proof of this conjecture is given in this note.

This is a preview of subscription content, access via your institution.

References

  1. 1

    Frerick L., Kalmes T.: Some results on surjectivity of augmented semi-elliptic differential operators. Math. Ann. 347, 81–94 (2010)

    MathSciNet  MATH  Article  Google Scholar 

  2. 2

    Hörmander L.: On the range of convolution operators. Ann. Math. 76, 148–170 (1962)

    MATH  Article  Google Scholar 

  3. 3

    Hörmander L.: The Analysis of Linear Partial Differential Operators I and II. Springer, Berlin (1983)

    Google Scholar 

  4. 4

    Malgrange B.: Existence et approximation des solutions des équations aux dérivées partielles et des équations de convolution. Ann. Inst. Fourier Grenoble 6, 271–355 (1955)

    MathSciNet  Article  Google Scholar 

  5. 5

    Trèves F.: Linear Partial Differential Operators with Constant Coefficients. Mathematics and its Applications, vol. 6. Gordon & Breach, New York (1966)

    Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to T. Kalmes.

Additional information

Dedicated to the memory of Susanne Dierolf.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Kalmes, T. Every P-convex subset of \({\mathbb{R}^2}\) is already strongly P-convex. Math. Z. 269, 721–731 (2011). https://doi.org/10.1007/s00209-010-0765-7

Download citation

Keywords

  • Convex Cone
  • Principal Part
  • Subspace Versus
  • Minimum Principle
  • Dual Cone