In mathematical analysis, the RieszâÂÂThorin theorem, often referred to as the RieszâÂÂThorin interpolation theorem or the RieszâÂÂThorin convexity theorem, is a result about interpolation of operators. It is named after Marcel Riesz and his student G. Olof Thorin.
This theorem bounds the norms of linear maps acting between spaces. Its usefulness stems from the fact that some of these spaces have rather simpler structure than others. Usually that refers to which is a Hilbert space, or to and . Therefore one may prove theorems about the more complicated cases by proving them in two simple cases and then using the RieszâÂÂThorin theorem to pass from the simple cases to the complicated cases. The Marcinkiewicz theorem is similar but applies also to a class of non-linear maps.
First we need the following definition:
By splitting up the function in as the product and applying Hölder's inequality to its power, we obtain the following result, foundational in the study of -spaces:
This result, whose name derives from the convexity of the map on , implies that .
On the other hand, if we take the layer-cake decomposition , then we see that and , whence we obtain the following result:
In particular, the above result implies that is included in , the sumset of and in the space of all measurable functions. Therefore, we have the following chain of inclusions:
In practice, we often encounter operators defined on the sumset . For example, the RiemannâÂÂLebesgue lemma shows that the Fourier transform maps boundedly into , and Plancherel's theorem shows that the Fourier transform maps boundedly into itself, hence the Fourier transform extends to by setting
for all and . It is therefore natural to investigate the behavior of such operators on the intermediate subspaces .
To this end, we go back to our example and note that the Fourier transform on the sumset was obtained by taking the sum of two instantiations of the same operator, namely
These really are the same operator, in the sense that they agree on the subspace . Since the intersection contains simple functions, it is dense in both and . Densely defined continuous operators admit unique extensions, and so we are justified in considering and to be the same.
Therefore, the problem of studying operators on the sumset essentially reduces to the study of operators that map two natural domain spaces, and , boundedly to two target spaces: and , respectively. Since such operators map the sumset space to , it is natural to expect that these operators map the intermediate space to the corresponding intermediate space .
There are several ways to state the RieszâÂÂThorin interpolation theorem; to be consistent with the notations in the previous section, we shall use the sumset formulation.
In other words, if is simultaneously of type and of type , then is of type for all . In this manner, the interpolation theorem lends itself to a pictorial description. Indeed, the Riesz diagram of is the collection of all points in the unit square such that is of type . The interpolation theorem states that the Riesz diagram of is a convex set: given two points in the Riesz diagram, the line segment that connects them will also be in the diagram.
The interpolation theorem was originally stated and proved by Marcel Riesz in 1927. The 1927 paper establishes the theorem only for the lower triangle of the Riesz diagram, viz., with the restriction that and . Olof Thorin extended the interpolation theorem to the entire square, removing the lower-triangle restriction. The proof of Thorin was originally published in 1938 and was subsequently expanded upon in his 1948 thesis.
We will first prove the result for simple functions and eventually show how the argument can be extended by density to all measurable functions.
By symmetry, let us assume (the case trivially follows from ()). Let be a simple function, that is for some finite , and , . Similarly, let denote a simple function , namely for some finite , and , .
Note that, since we are assuming and to be -finite metric spaces, and for all . Then, by proper normalization, we can assume and , with and with , as defined by the theorem statement.
Next, we define the two complex functions Note that, for , and . We then extend and to depend on a complex parameter as follows: so that and . Here, we are implicitly excluding the case , which yields : In that case, one can simply take , independently of , and the following argument will only require minor adaptations.
Let us now introduce the function where are constants independent of . We readily see that is an entire function, bounded on the strip . Then, in order to prove (), we only need to show that for all and as constructed above. Indeed, if () holds true, by Hadamard three-lines theorem, for all and . This means, by fixing , that where the supremum is taken with respect to all simple functions with . The left-hand side can be rewritten by means of the following lemma.
In our case, the lemmaÃÂ above implies for all simple function with . Equivalently, for a generic simple function,
Let us now prove that our claim () is indeed certain. The sequence consists of disjoint subsets in and, thus, each belongs to (at most) one of them, say . Then, for , which implies that . With a parallel argument, each belongs to (at most) one of the sets supporting , say , and
We can now bound : By applying HölderâÂÂs inequality with conjugate exponents and , we have
We can repeat the same process for to obtain , and, finally,
So far, we have proven that when is a simple function. As already mentioned, the inequality holds true for all by the density of simple functions in .
Formally, let and let be a sequence of simple functions such that , for all , and pointwise. Let and define , , and . Note that, since we are assuming , and, equivalently, and .
Let us see what happens in the limit for . Since , and , by the dominated convergence theorem one readily has Similarly, , and imply and, by the linearity of as an operator of types and (we have not proven yet that it is of type for a generic )
It is now easy to prove that and in measure: For any , ChebyshevâÂÂs inequality yields and similarly for . Then, and a.e.àfor some subsequence and, in turn, a.e. Then, by FatouâÂÂs lemma and recalling that () holds true for simple functions,
The proof outline presented in the above section readily generalizes to the case in which the operator is allowed to vary analytically. In fact, an analogous proof can be carried out to establish a bound on the entire function
from which we obtain the following theorem of Elias Stein, published in his 1956 thesis:
The theory of real Hardy spaces and the space of bounded mean oscillations permits us to wield the Stein interpolation theorem argument in dealing with operators on the Hardy space and the space of bounded mean oscillations; this is a result of Charles Fefferman and Elias Stein.
It has been shown in the first section that the Fourier transform maps boundedly into and into itself. A similar argument shows that the Fourier series operator, which transforms periodic functions into functions whose values are the Fourier coefficients
maps boundedly into and into . The RieszâÂÂThorin interpolation theorem now implies the following:
where and . This is the HausdorffâÂÂYoung inequality.
The HausdorffâÂÂYoung inequality can also be established for the Fourier transform on locally compact Abelian groups. The norm estimate of 1 is not optimal. See the main article for references.
Let be a fixed integrable function and let be the operator of convolution with , i.e., for each function we have .
It follows from Fubini's theorem that is bounded from to and it is trivial that it is bounded from to (both bounds are by ). Therefore the RieszâÂÂThorin theorem gives
We take this inequality and switch the role of the operator and the operand, or in other words, we think of as the operator of convolution with , and get that is bounded from to L<sup>p</sup>. Further, since is in we get, in view of Hölder's inequality, that is bounded from to , where again . So interpolating we get
where the connection between p, r and s is
The Hilbert transform of is given by
where p.v. indicates the Cauchy principal value of the integral. The Hilbert transform is a Fourier multiplier operator with a particularly simple multiplier:
It follows from the Plancherel theorem that the Hilbert transform maps boundedly into itself.
Nevertheless, the Hilbert transform is not bounded on or , and so we cannot use the RieszâÂÂThorin interpolation theorem directly. To see why we do not have these endpoint bounds, it suffices to compute the Hilbert transform of the simple functions and . We can show, however, that
for all Schwartz functions , and this identity can be used in conjunction with the CauchyâÂÂSchwarz inequality to show that the Hilbert transform maps boundedly into itself for all . Interpolation now establishes the bound
for all , and the self-adjointness of the Hilbert transform can be used to carry over these bounds to the case.
While the RieszâÂÂThorin interpolation theorem and its variants are powerful tools that yield a clean estimate on the interpolated operator norms, they suffer from numerous defects: some minor, some more severe. Note first that the complex-analytic nature of the proof of the RieszâÂÂThorin interpolation theorem forces the scalar field to be . For extended-real-valued functions, this restriction can be bypassed by redefining the function to be finite everywhereâÂÂpossible, as every integrable function must be finite almost everywhere. A more serious disadvantage is that, in practice, many operators, such as the HardyâÂÂLittlewood maximal operator and the CalderónâÂÂZygmund operators, do not have good endpoint estimates. In the case of the Hilbert transform in the previous section, we were able to bypass this problem by explicitly computing the norm estimates at several midway points. This is cumbersome and is often not possible in more general scenarios. Since many such operators satisfy the weak-type estimates
real interpolation theorems such as the Marcinkiewicz interpolation theorem are better-suited for them. Furthermore, a good number of important operators, such as the Hardy-Littlewood maximal operator, are only sublinear. This is not a hindrance to applying real interpolation methods, but complex interpolation methods are ill-equipped to handle non-linear operators. On the other hand, real interpolation methods, compared to complex interpolation methods, tend to produce worse estimates on the intermediate operator norms and do not behave as well off the diagonal in the Riesz diagram. The off-diagonal versions of the Marcinkiewicz interpolation theorem require the formalism of Lorentz spaces and do not necessarily produce norm estimates on the -spaces.
B. Mityagin extended the RieszâÂÂThorin theorem; this extension is formulated here in the special case of spaces of sequences with unconditional bases (cf. below).
Assume:
Then
for any unconditional Banach space of sequences , that is, for any and any , .
The proof is based on the KreinâÂÂMilman theorem.