1 / 37

Carleson’s Theorem, Variations and Applications

This book explores Carleson's theorem, its variations, and its applications in harmonic analysis. It discusses the Bilinear Hilbert transform, symmetries, embedding theorems, convergence of Fourier series, operator norms, and other related topics.

bbrody
Download Presentation

Carleson’s Theorem, Variations and Applications

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Carleson’s Theorem,Variations and Applications Christoph Thiele Santander, September 2014

  2. Bilinear Hilbert transform Here is a unit vector perpendicular to (1,1,1), with no two components equal. 1)Translation symmetry 2)Dilation symmetry 3)Modulation symmetry with vector

  3. New embedding map Embedding map using orbit of entire group: Express bilinear Cauchy transform as

  4. Modified outer measure space For alpha, beta coming form vectors as above Tents: For small b depending on alpha, beta

  5. Embedding theorem Thm: For 2<p<infty As Corollary obtain bounds for BHT: Where and

  6. Carleson’s theorem On almost everywhere convergence of Fourier series (integrals for expository purpose): For almost every x. Assumptions is that f in Lp. May assume for simplicity that Fourier transform of f is integrable on half lines.

  7. Carleson’s Operator Closely related maximal operator Carleson-Hunt theorem (1966/1968): Can be thought as stepping stone to Carl. Thm

  8. Remarks on Carleson’s operator • Simple reflection symmetry and cut and paste arguments allow for two-sided truncations. • For we note the Cauchy projection • For arbitrary eta, we note modulated C. p.

  9. Equivalent variants Maximal modulated Hilbert transform Linearized maximal operators, to be estimated uniformly in all measurable functions eta

  10. Symmetries Dilation sym: inherited from Cauchy proj. Translation sym: inherited from Cauchy proj. Modulation symmetry:

  11. Carleson with embedding maps Old New Here phi has positive smooth FT with small support. Then

  12. Proof of representation Recall Calderon reproducing/Cauchy proj. Modulated Cauchy projection (fixed xi) Averaged version

  13. Proof of representation Write G explicitly as integral For Carleson, each z sees frequency eta(z) Change of variable xi, then integrate gamma

  14. Modified size Analoguous tent spaces for tile embedding Modified size: Recall old size

  15. Modified Embedding theorem Old Thm: For 2<p<infty New Thm. For 1<p<infty With that proof proceeds as before.

  16. Comparison BHT/Carleson • BHT has simpler proof since more symmetric and needs only on embedding theorem • Carleson appears more naturally in applications, since it has a more canonical modulation symmetry that does not depend on an ad hoc vector beta.

  17. Generalizations of Carleson Recall that Carleson reads as One way of strengthening of Carleson operator is to replace Linfty by larger norms. Then prove Lp bounds for these stronger operators.

  18. Variation Norm A strengthening of supremum norm. Note That finite variation implies convergence.

  19. Variation Norm Carleson Thm. (Oberlin, Seeger, Tao, T. Wright, ‘09)

  20. Multiplier Norm - norm of a function f is the operator norm of its Fourier multiplier operator acting on - norm is the same as supremum norm

  21. Coifman, R.d.F, Semmes Application of Rubio de Francia’s inequality: Variation norm controls multiplier norm Provided Hence variational Carleson implies - Carleson

  22. Truncated Carleson Operator

  23. Maximal Multiplier Norm -norm of a family of functions is the operator norm of the maximal operator on No easy alternative description for

  24. -Carleson operator Theorem: (Demeter,Lacey,Tao,T. ’07) Conjectured extension to , range of p ? Non-singular variant with by Demeter 09’.

  25. Birkhoff’s Ergodic Theorem X: probability space (measure space of mass 1). T: measure preserving transformation on X. : measurable function on X (say in ). Then exists for almost every x .

  26. Harmonic analysis with … Compare With max. operator With Hardy Littlewood With Lebesgue Differentiation

  27. Weighted Birkhoff A weight sequence is called “good” if the weighted Birkhoff holds: For all X,T, Exists for almost every x.

  28. Return Times Theorem (Bourgain, ‘88) Y probability space, S measure preserving transformation on Y, . Then is good for almost every y. Extended to , 1<p<2 by Demeter, Lacey,Tao,T. Transfer to harmonic analysis, take Fourier transform in f, recognize .

  29. Nonlinear theory Fourier sums as products (via exponential fct)

  30. Non-commutative theory Nonlinear Fourier transform, other choices of matrices lead to other models, AKNS systems

  31. Incarnations of NLFT • (One dimensional) Scattering theory • Integrable systems, KdV, NLS, inverse scattering method. • Riemann-Hilbert problems • Orthogonal polynomials • Schur algorithm • Random matrix theory

  32. Analogues of classical facts Nonlinear Plancherel (a = first entry of G) Nonlinear Hausdorff-Young (Christ-Kiselev) Nonlinear Riemann-Lebesgue (Gronwall)

  33. Conjectured analogues Nonlinear Carleson Uniform nonlinear Hausdorff Young Both OK in Walsh case, WNLUHY by Vjeko Kovac

  34. Picard iteration, exp series Scalar case: symmetrize, integrate over cubes

  35. Terry Lyons’ theory Etc. … If for one value of r>1 one controls all with n<r, then bounds for n>r follow automatically as well as a bound for the series.

  36. Lyons for AKNS, r<2, n=1 For 1<p<2 we obtain by interpolation between a trivial estimate ( ) and variational Carleson ( ) This implies nonlinear Hausdorff Young as well as variational and maximal versions of nonlinear HY. Barely fails to prove the nonlinear Carleson theorem because cannot choose

  37. Lyons for AKNS, 2<r<3, n=1,2 Now estimate for n=1 is fine by variational Carleson. Work in progress with C.Muscalu and Yen Do: Appears to work fine when . This puts an algebraic condition on AKNS which unfortunately is violated by NLFT as introduced above.

More Related