carleson’s theorem, variations and applications christoph thiele kiel, 2010

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Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

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Page 1: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

Carleson’s Theorem,Variations and Applications

Christoph Thiele

Kiel, 2010

Page 2: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

x

Page 3: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010
Page 4: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010
Page 5: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010
Page 6: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010
Page 7: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010
Page 8: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010
Page 9: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

• Translation in horizontal direction

• Dilation

• Rotation by 90 degrees

• Translation in vertical direction

)()( yxfxfTy

2/1/)/()( xfxfD

dxexff ix 2)()(ˆ

ixexfxfM 2)()(

Page 10: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

Carleson Operator

( identity op, Cauchy projection)

Translation/Dilation/Modulation symmetry.

Carleson-Hunt theorem (1966/1968):

defxfC ix2)(ˆsup)(

pppfcfC

p1

0

Page 11: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010
Page 12: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010
Page 13: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010
Page 14: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010
Page 15: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010
Page 16: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010
Page 17: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010
Page 18: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010
Page 19: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010
Page 20: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010
Page 21: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

Multiplier Norm

- norm of a function f is the operator normof its Fourier multiplier operator acting on

- norm is the same as supremum norm

qM

)(1 FgfFg

)(RLq

)(sup2

fff

M

2M

Page 22: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

-Carleson operator

Theorem: (Oberlin, Seeger, Tao, T. Wright ’10)

provided

qM

)(

2 ||)(ˆ||)(

qq M

xi

MdefxfC

pqpp

MfcfC

q,

qp /1|2/1/1|

Page 23: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

Redefine Carleson Operator

Truncated Carleson operator

tdtetxfvpxCf txi /)(..sup)( )(

tdtetxfxfCc

txi /)(sup)(],[

)(

Page 24: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

Truncated Carleson as average

tdttetxfR

txi /)/()(sup )(

tdtdeetxfR R

titxi /)(ˆ)(sup )(

dtdteetxf

R R

titxi /)(sup)(ˆ )(

Page 25: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

Maximal Multiplier Norm

-norm of a family of functions is the

operator norm of the maximal operator on

No easy alternative description for

)(sup 1 FgfFg

)(RLp

pM f

2M

Page 26: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

-Carleson operator

Theorem: (Demeter,Lacey,Tao,T. ’07)

Conjectured extension to , range of p ?

Non-singular variant with by Demeter 09’.

2M

)(],[

)(*2

*2

||/)(||)(

M

txi

MtdtetxfxfC

c

pppM

fcfC *2

pMpM

Page 27: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

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 .

)(2 XL

)(1

lim1

xTfN

N

n

n

N

f

Page 28: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

Harmonic analysis with …

Compare

With max. operator

With Hardy Littlewood

With Lebesgue Differentiation

…and no Schwartz functions

)(1

lim1

xTfN

N

n

n

N

)(1

sup1

xTfN

N

n

n

N

00

)(1

lim dttxf

0

)(1

sup dttxf

Page 29: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

Weighted Birkhoff

A weight sequence is called “good” if the

weighted Birkhoff holds: For all X,T,

Exists for almost every x.

na

)(1

lim1

xTfaN

nN

nnN

)(2 XLf

Page 30: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

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 .

)(2 YLg)( ySga n

n

)(YLg p

*2M

C

Page 31: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

Hilbert Transform / Vector Fields

Lipshitz,

Stein conjecture:

Also of interest are a) values other than p=2, b) maximal operator along vector field (Zygmund

conjecture) or maximal truncated singular integral

1

1

/))(()( tdttxvxfxfHv

22: RRv yxCyvxv )()(

22fCfH vv

Page 32: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

Coifman: VF depends on 1 vrbl

Other values of p: Lacey-Li/ Bateman

Open: range of p near 1, maximal operator

),(2

/))(,(yxLR

tdttxvytxf

),(

)(

2

/),(ˆ

yxLR

txiv

R

iy dtdtetxfe

2),(),(

)(2

2

),(ˆ/),(ˆ fxftdtetxfxL

xLR

txiv

Page 33: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

Application of -Carleson (C. Demeter)

Vector field v depends on one variable and f

is an elementary tensor f(x,y)=a(x)b(y), then

in an open range of p around 2.

pM

ppv fCxfH )(

),(

)( /)()(ˆ

yxLR

txiv

R

iy

P

dtdtetxabe

Page 34: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

Application of Carleson

Maximal truncation of HT along vectorfield

Under same assumptions as before

Carried out for Hardy Littlewood maximal operatoralong vector field by Demeter.

*pM

ppv fCxfH )(*

tdttxvxfxfHv /))((sup)(

1

*

Page 35: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

Variation Norm

rrnn

N

nxxxNV

xfxffN

r/1

11,...,,,

)|)()(|(sup||||10

Another strengthening of supremum norm

Page 36: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

Variation Norm Carleson

Thm. (Oberlin, Seeger, Tao, T. Wright, ‘09)

)(

2)(ˆ)(

r

r

V

ix

VdefxfC

ppVfCfC r

,1 p )',2max( pr

Page 37: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

Rubio de Francia’s inequality

Rubio de Francia’s square function, p>2,

Variational Carleson, p>2

p

xL

ixN

nNfCdef

p

n

nN

)(

)2/(122

1,...,,,)|)(ˆ|(sup

110

p

xL

ixN

nNfCdef

p

n

nN

)(

2/122

1,...,,,)|)(ˆ|(sup

110

Page 38: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

Coifman, R.d.F, Semmes

Application of Rubio de Francia’s inequality:Variation norm controls multiplier norm

Provided

Hence variational Carleson implies - Carleson

rp VM

mCm

rp /1|/12/1|

pM

Page 39: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

Nonlinear theory

Fourier sums as products (via exponential fct)

dxexfygy

ix

2)(exp)(

)()()(' 2 ygexfyg ix

1)( g

))(ˆexp()( fg

Page 40: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

Non-commutative theory

Nonlinear Fourier transform, other choices of matrices lead to other models, AKNS systems

)(0)(

)(0)('

2

2

yGexf

exfyG

ix

ix

10

01)(G

)()( fG

Page 41: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

Incarnations of NLFT

• (One dimensional) Scattering theory

• Integrable systems, KdV, NLS, inverse scattering method.

• Riemann-Hilbert problems

• Orthogonal polynomials

• Schur algorithm

• Random matrix theory

Page 42: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

Analogues of classical factsNonlinear Plancherel (a = first entry of G)

Nonlinear Hausdorff-Young (Christ-Kiselev)

Nonlinear Riemann-Lebesgue (Gronwall)

2)(2|)(|log fcaL

ppL

fcap

)('

|)(|log 21 p

1)(|)(|log fcaL

Page 43: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

Conjectured analogues

Nonlinear Carleson

Uniform nonlinear Hausdorff Young

Both OK in Walsh case, WNLUHY by Vjeko Kovac

2)(2

|)(|logsup

fcyaLy

ppfca

'|)(|log 21 p

Page 44: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

Picard iteration, exp series

Scalar case: symmetrize, integrate over cubes

idGxGxMxG )(),()()('

xy

dyyMidxGidxG )()(,)( 21

...)(!2

1)(1)(

2

xyxy

dyyMdyyMxG

...)()()()(12

1221 xyyxy

dydyyMyMdyyMidxG

Page 45: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

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.

rr

xyx

N

nxxxNr dyymV

nnN

/1

1,...,,,1, )|)(|(sup

110

rr

xyyx

N

nxxxNr dydyymymV

nnN

/22/1221

1,...,,,2, )|)()(|(sup

12110

nrV ,

Page 46: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

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

pp

L

pp

xyx

iyN

nxxxNfcdyeyf

pnnN

)(

)/(12

1,...,,,'1

10

)|)(|(sup

2L1L

22 r

Page 47: Carleson’s Theorem, Variations and Applications Christoph Thiele Kiel, 2010

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.

rr

xyyx

yyiN

nxxxNdyeyfyf

nnN

/22/)(221

1,...,,,)|)()(|(sup

121

2211

10

021