We establish upper bounds for the convolution operator acting between interpolation spaces. This will provide several examples of Young Inequalities in different families of function spaces. We use this result to prove a bilinear interpolation theorem and we show applications to the study of bilinear multipliers.
IntroductionThe real interpolation method introduced by Lions and Peetre in 1964, see [38], has proved to be a very useful tool in many areas of analysis such as harmonic analysis, partial differential equations, approximation theory, operator theory or functional analysis. See the monographs by Butzer and Berens [11], Bergh and Löfström [5], Triebel [48, 49, 50], Beauzamy [2], König [33], Bennett Sharpley [4], Tartar [47] or the monographs by Connes [14], and Amrein, Boutet de Monvel and Geourgescu [1] for applications to other areas.However the classical version of this method fails to identify the endpoint spaces of the interpolation scales it generates. As an example, let us recall that the classical real method does not produce Lorentz-Zygmund spaces from the couple (L 1 , L ∞ ). In order to do so, we need to introduce limiting interpolation methods such as logarithmic methods. The papers by Evans and Opic [18] and also Evans, Opic and Pick [19], where the authors study logarithmic interpolation methods, inspired the appearance of the some other limiting methods defined by means of slowly varying functions and rearrangement invariant (r.i.) spaces. These have been studied by T. Signes and one the the present authors in [20,21,22,23,24, 25] and allow to produce limit spaces that are not in the classical real interpolation scale.On the other hand, several papers that study bilinear interpolation theorems have been recently published. See for example Mastylo [39] or Cobos and Segurado [13] where we can find bilinear interpolation theorems for logarithmic methods. Here, we extend the study of bilinear interpolation theorems to the methods defined by slowly varying functions and r.i. spaces. The main obstacle for our approach is the lack of a Young type inequality for r.i. spaces. For this reason, in a first stage we establish a general Young inequality in the context of r.i. spaces that will be used to prove subsequent bilinear interpolation theorems. In order to be more precise, let the measure space (Ω, µ) be R with the Lebesgue measure or Z with the counting 1991 Mathematics Subject Classification. Primary 46B70, 47B07; Secondary 46E30. This work was supported by the Spanish Ministerio de Economía y Competitividad (MTM2013-42220-P) and Fundación Séneca de la Región de Murcia 19378/PI/14. E . Now, apply Thm. 2.1 to obtain that. This completes the proof.Also, we can establish a bilinear interpolation theorem for J-spaces. Theorem 3.5. Let 0 ≤ θ ≤ 1, ϕ and slowly varying function and E and r.i. space. Then, for any interpolation functor F, T : A J θ,ϕ,E × B J θ,mϕ,F (L 1 ,E ′ ) −→ C J θ,ϕ,F (E,L ∞ )is a bounded bilinear operator with norm no greater than T = max{ T 0 , T 1 }.