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Marcinkiewicz interpolation theorem

In mathematics, the Marcinkiewicz interpolation theorem, discovered by Józef Marcinkiewicz (1939), is a result bounding the norms of non-linear operators acting on Lp spaces.

Marcinkiewicz' theorem is similar to the Riesz–Thorin theorem about linear operators, but also applies to non-linear operators.

Preliminaries edit

Let f be a measurable function with real or complex values, defined on a measure space (XF, ω). The distribution function of f is defined by

 

Then f is called weak   if there exists a constant C such that the distribution function of f satisfies the following inequality for all t > 0:

 

The smallest constant C in the inequality above is called the weak   norm and is usually denoted by   or   Similarly the space is usually denoted by L1,w or L1,∞.

(Note: This terminology is a bit misleading since the weak norm does not satisfy the triangle inequality as one can see by considering the sum of the functions on   given by   and  , which has norm 4 not 2.)

Any   function belongs to L1,w and in addition one has the inequality

 

This is nothing but Markov's inequality (aka Chebyshev's Inequality). The converse is not true. For example, the function 1/x belongs to L1,w but not to L1.

Similarly, one may define the weak   space as the space of all functions f such that   belong to L1,w, and the weak   norm using

 

More directly, the Lp,w norm is defined as the best constant C in the inequality

 

for all t > 0.

Formulation edit

Informally, Marcinkiewicz's theorem is

Theorem. Let T be a bounded linear operator from   to   and at the same time from   to  . Then T is also a bounded operator from   to   for any r between p and q.

In other words, even if one only requires weak boundedness on the extremes p and q, regular boundedness still holds. To make this more formal, one has to explain that T is bounded only on a dense subset and can be completed. See Riesz-Thorin theorem for these details.

Where Marcinkiewicz's theorem is weaker than the Riesz-Thorin theorem is in the estimates of the norm. The theorem gives bounds for the   norm of T but this bound increases to infinity as r converges to either p or q. Specifically (DiBenedetto 2002, Theorem VIII.9.2), suppose that

 
 

so that the operator norm of T from Lp to Lp,w is at most Np, and the operator norm of T from Lq to Lq,w is at most Nq. Then the following interpolation inequality holds for all r between p and q and all f ∈ Lr:

 

where

 

and

 

The constants δ and γ can also be given for q = ∞ by passing to the limit.

A version of the theorem also holds more generally if T is only assumed to be a quasilinear operator in the following sense: there exists a constant C > 0 such that T satisfies

 

for almost every x. The theorem holds precisely as stated, except with γ replaced by

 

An operator T (possibly quasilinear) satisfying an estimate of the form

 

is said to be of weak type (p,q). An operator is simply of type (p,q) if T is a bounded transformation from Lp to Lq:

 

A more general formulation of the interpolation theorem is as follows:

  • If T is a quasilinear operator of weak type (p0, q0) and of weak type (p1, q1) where q0 ≠ q1, then for each θ ∈ (0,1), T is of type (p,q), for p and q with pq of the form
 

The latter formulation follows from the former through an application of Hölder's inequality and a duality argument.[citation needed]

Applications and examples edit

A famous application example is the Hilbert transform. Viewed as a multiplier, the Hilbert transform of a function f can be computed by first taking the Fourier transform of f, then multiplying by the sign function, and finally applying the inverse Fourier transform.

Hence Parseval's theorem easily shows that the Hilbert transform is bounded from   to  . A much less obvious fact is that it is bounded from   to  . Hence Marcinkiewicz's theorem shows that it is bounded from   to   for any 1 < p < 2. Duality arguments show that it is also bounded for 2 < p < ∞. In fact, the Hilbert transform is really unbounded for p equal to 1 or ∞.

Another famous example is the Hardy–Littlewood maximal function, which is only sublinear operator rather than linear. While   to   bounds can be derived immediately from the   to weak   estimate by a clever change of variables, Marcinkiewicz interpolation is a more intuitive approach. Since the Hardy–Littlewood Maximal Function is trivially bounded from   to  , strong boundedness for all   follows immediately from the weak (1,1) estimate and interpolation. The weak (1,1) estimate can be obtained from the Vitali covering lemma.

History edit

The theorem was first announced by Marcinkiewicz (1939), who showed this result to Antoni Zygmund shortly before he died in World War II. The theorem was almost forgotten by Zygmund, and was absent from his original works on the theory of singular integral operators. Later Zygmund (1956) realized that Marcinkiewicz's result could greatly simplify his work, at which time he published his former student's theorem together with a generalization of his own.

In 1964 Richard A. Hunt and Guido Weiss published a new proof of the Marcinkiewicz interpolation theorem.[1]

See also edit

References edit

  1. ^ Hunt, Richard A.; Weiss, Guido (1964). "The Marcinkiewicz interpolation theorem". Proceedings of the American Mathematical Society. 15 (6): 996–998. doi:10.1090/S0002-9939-1964-0169038-4. ISSN 0002-9939.

marcinkiewicz, interpolation, theorem, mathematics, discovered, józef, marcinkiewicz, 1939, result, bounding, norms, linear, operators, acting, spaces, marcinkiewicz, theorem, similar, riesz, thorin, theorem, about, linear, operators, also, applies, linear, op. In mathematics the Marcinkiewicz interpolation theorem discovered by Jozef Marcinkiewicz 1939 is a result bounding the norms of non linear operators acting on Lp spaces Marcinkiewicz theorem is similar to the Riesz Thorin theorem about linear operators but also applies to non linear operators Contents 1 Preliminaries 2 Formulation 3 Applications and examples 4 History 5 See also 6 ReferencesPreliminaries editLet f be a measurable function with real or complex values defined on a measure space X F w The distribution function of f is defined by lf t w x X f x gt t displaystyle lambda f t omega left x in X mid f x gt t right nbsp Then f is called weak L1 displaystyle L 1 nbsp if there exists a constant C such that the distribution function of f satisfies the following inequality for all t gt 0 lf t Ct displaystyle lambda f t leq frac C t nbsp The smallest constant C in the inequality above is called the weak L1 displaystyle L 1 nbsp norm and is usually denoted by f 1 w displaystyle f 1 w nbsp or f 1 displaystyle f 1 infty nbsp Similarly the space is usually denoted by L1 w or L1 Note This terminology is a bit misleading since the weak norm does not satisfy the triangle inequality as one can see by considering the sum of the functions on 0 1 displaystyle 0 1 nbsp given by 1 x displaystyle 1 x nbsp and 1 1 x displaystyle 1 1 x nbsp which has norm 4 not 2 Any L1 displaystyle L 1 nbsp function belongs to L1 w and in addition one has the inequality f 1 w f 1 displaystyle f 1 w leq f 1 nbsp This is nothing but Markov s inequality aka Chebyshev s Inequality The converse is not true For example the function 1 x belongs to L1 w but not to L1 Similarly one may define the weak Lp displaystyle L p nbsp space as the space of all functions f such that f p displaystyle f p nbsp belong to L1 w and the weak Lp displaystyle L p nbsp norm using f p w f p 1 w1p displaystyle f p w left f p right 1 w frac 1 p nbsp More directly the Lp w norm is defined as the best constant C in the inequality lf t Cptp displaystyle lambda f t leq frac C p t p nbsp for all t gt 0 Formulation editInformally Marcinkiewicz s theorem is Theorem Let T be a bounded linear operator from Lp displaystyle L p nbsp to Lp w displaystyle L p w nbsp and at the same time from Lq displaystyle L q nbsp to Lq w displaystyle L q w nbsp Then T is also a bounded operator from Lr displaystyle L r nbsp to Lr displaystyle L r nbsp for any r between p and q In other words even if one only requires weak boundedness on the extremes p and q regular boundedness still holds To make this more formal one has to explain that T is bounded only on a dense subset and can be completed See Riesz Thorin theorem for these details Where Marcinkiewicz s theorem is weaker than the Riesz Thorin theorem is in the estimates of the norm The theorem gives bounds for the Lr displaystyle L r nbsp norm of T but this bound increases to infinity as r converges to either p or q Specifically DiBenedetto 2002 Theorem VIII 9 2 suppose that Tf p w Np f p displaystyle Tf p w leq N p f p nbsp Tf q w Nq f q displaystyle Tf q w leq N q f q nbsp so that the operator norm of T from Lp to Lp w is at most Np and the operator norm of T from Lq to Lq w is at most Nq Then the following interpolation inequality holds for all r between p and q and all f Lr Tf r gNpdNq1 d f r displaystyle Tf r leq gamma N p delta N q 1 delta f r nbsp where d p q r r q p displaystyle delta frac p q r r q p nbsp and g 2 r q p r p q r 1 r displaystyle gamma 2 left frac r q p r p q r right 1 r nbsp The constants d and g can also be given for q by passing to the limit A version of the theorem also holds more generally if T is only assumed to be a quasilinear operator in the following sense there exists a constant C gt 0 such that T satisfies T f g x C Tf x Tg x displaystyle T f g x leq C Tf x Tg x nbsp for almost every x The theorem holds precisely as stated except with g replaced by g 2C r q p r p q r 1 r displaystyle gamma 2C left frac r q p r p q r right 1 r nbsp An operator T possibly quasilinear satisfying an estimate of the form Tf q w C f p displaystyle Tf q w leq C f p nbsp is said to be of weak type p q An operator is simply of type p q if T is a bounded transformation from Lp to Lq Tf q C f p displaystyle Tf q leq C f p nbsp A more general formulation of the interpolation theorem is as follows If T is a quasilinear operator of weak type p0 q0 and of weak type p1 q1 where q0 q1 then for each 8 0 1 T is of type p q for p and q with p q of the form1p 1 8p0 8p1 1q 1 8q0 8q1 displaystyle frac 1 p frac 1 theta p 0 frac theta p 1 quad frac 1 q frac 1 theta q 0 frac theta q 1 nbsp dd The latter formulation follows from the former through an application of Holder s inequality and a duality argument citation needed Applications and examples editA famous application example is the Hilbert transform Viewed as a multiplier the Hilbert transform of a function f can be computed by first taking the Fourier transform of f then multiplying by the sign function and finally applying the inverse Fourier transform Hence Parseval s theorem easily shows that the Hilbert transform is bounded from L2 displaystyle L 2 nbsp to L2 displaystyle L 2 nbsp A much less obvious fact is that it is bounded from L1 displaystyle L 1 nbsp to L1 w displaystyle L 1 w nbsp Hence Marcinkiewicz s theorem shows that it is bounded from Lp displaystyle L p nbsp to Lp displaystyle L p nbsp for any 1 lt p lt 2 Duality arguments show that it is also bounded for 2 lt p lt In fact the Hilbert transform is really unbounded for p equal to 1 or Another famous example is the Hardy Littlewood maximal function which is only sublinear operator rather than linear While Lp displaystyle L p nbsp to Lp displaystyle L p nbsp bounds can be derived immediately from the L1 displaystyle L 1 nbsp to weak L1 displaystyle L 1 nbsp estimate by a clever change of variables Marcinkiewicz interpolation is a more intuitive approach Since the Hardy Littlewood Maximal Function is trivially bounded from L displaystyle L infty nbsp to L displaystyle L infty nbsp strong boundedness for all p gt 1 displaystyle p gt 1 nbsp follows immediately from the weak 1 1 estimate and interpolation The weak 1 1 estimate can be obtained from the Vitali covering lemma History editThe theorem was first announced by Marcinkiewicz 1939 who showed this result to Antoni Zygmund shortly before he died in World War II The theorem was almost forgotten by Zygmund and was absent from his original works on the theory of singular integral operators Later Zygmund 1956 realized that Marcinkiewicz s result could greatly simplify his work at which time he published his former student s theorem together with a generalization of his own In 1964 Richard A Hunt and Guido Weiss published a new proof of the Marcinkiewicz interpolation theorem 1 See also editInterpolation spaceReferences edit Hunt Richard A Weiss Guido 1964 The Marcinkiewicz interpolation theorem Proceedings of the American Mathematical Society 15 6 996 998 doi 10 1090 S0002 9939 1964 0169038 4 ISSN 0002 9939 DiBenedetto Emmanuele 2002 Real analysis Birkhauser ISBN 3 7643 4231 5 Gilbarg David Trudinger Neil S 2001 Elliptic partial differential equations of second order Springer Verlag ISBN 3 540 41160 7 Marcinkiewicz J 1939 Sur l interpolation d operations C R Acad Sci Paris 208 1272 1273 Stein Elias Weiss Guido 1971 Introduction to Fourier analysis on Euclidean spaces Princeton University Press ISBN 0 691 08078 X Zygmund A 1956 On a theorem of Marcinkiewicz concerning interpolation of operations Journal de Mathematiques Pures et Appliquees Neuvieme Serie 35 223 248 ISSN 0021 7824 MR 0080887 Retrieved from https en wikipedia org w index php title Marcinkiewicz interpolation theorem amp oldid 1150920960, wikipedia, wiki, book, books, library,

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