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# Bounded mean oscillation

In harmonic analysis, a function of bounded mean oscillation, also known as a BMO function, is a real-valued function whose mean oscillation is bounded (finite). The space of functions of bounded mean oscillation (BMO), is a function space that, in some precise sense, plays the same role in the theory of Hardy spaces Hp that the space L of essentially bounded functions plays in the theory of Lp-spaces: it is also called John–Nirenberg space, after Fritz John and Louis Nirenberg who introduced and studied it for the first time.

## Historical note

According to Nirenberg (1985, p. 703 and p. 707), the space of functions of bounded mean oscillation was introduced by John (1961, pp. 410–411) in connection with his studies of mappings from a bounded set Ω belonging to ℝn into ℝn and the corresponding problems arising from elasticity theory, precisely from the concept of elastic strain: the basic notation was introduced in a closely following paper by John & Nirenberg (1961), where several properties of this function spaces were proved. The next important step in the development of the theory was the proof by Charles Fefferman of the duality between BMO and the Hardy space H1, in the noted paper Fefferman & Stein 1972: a constructive proof of this result, introducing new methods and starting a further development of the theory, was given by Akihito Uchiyama.

## Definition

Definition 1. The mean oscillation of a locally integrable function u (i.e. a function belonging to $L^1_{\textrm{loc}}(\mathbb{R}^n)$) over a hypercube Q in n is defined as the following integral: $\frac{1}{|Q|}\int_{Q}|u(y)-u_Q|\,\mathrm{d}y$

where

• |Q| is the volume of Q, i.e. its Lebesgue measure
• uQ is the average value of u on the cube Q, i.e. $u_Q=\frac{1}{|Q|}\int_{Q} u(y)\,\mathrm{d}y$.

Definition 2. A BMO function is any function u belonging to $L^1_{\textrm{loc}}(\mathbb{R}^n)$ whose mean oscillation has a finite supremum over the set of all cubes Q contained in n.

Note. The use of cubes Q in n as the integration domains on which the mean oscillation is calculated, is not mandatory: Wiegerinck (2001) uses balls instead and, as remarked by Stein (1993, p. 140), in doing so a perfectly equivalent of definition of functions of bounded mean oscillation arises.

## Basic properties

### BMO functions are locally p–integrable

BMO functions are locally Lp if 0 < p < ∞ , but need not be locally bounded.

### BMO is a Banach space

The supremum of the mean oscillation is called the BMO norm of u and is denoted by ||u||BMO (and in some instances it is also denoted ||u||*). The function ||u||BMO becomes a norm on BMO functions after quotienting out by the constant functions (which have BMO norm 0).

### Averages of adjacent cubes are comparable

As the name suggests, the mean or average of a function in BMO shouldn't oscillate very much when computing it over cubes close to each other in position and scale. To be more precise, if Q and R are dyadic cubes such that their boundaries touch and the sidelength of Q is no less than one-half the sidelength of R, then $|f_{R}-f_{Q}|\leq C||f||_{BMO}$

where C>0 is some universal constant. This property is, in fact, equivalent to f being in BMO, that is, if f is a locally integrable function such that |fR-fQ|≤C for all dyadic cubes Q and R adjacent in the sense described above, then f is in BMO and its BMO norm is proportional to the constant C.

### The John–Nirenberg Inequality

The John–Nirenberg Inequality is an estimate that governs how far a function of bounded mean oscillation may deviate from its average by a certain amount.

#### Statement

There are constants c1,c2 > 0 such that whenever f ∈ BMO(n), then for any cube Q in n, $|\{x\in Q: |f-f_{Q}|>\lambda\}|\leq c_{1}e^{-c_{2}\frac{\lambda}{||f||_{BMO}}}|Q|.$

Conversely, if this inequality holds over all cubes with some constant C in place of ||f||BMO, then f is in BMO with norm at most a constant times C.

#### A consequence: the distance in BMO to L∞

The John-Nirenberg inequality can actually give more information than just the BMO norm of a function. For a locally integrable function f, let A(f) be the infimal A>0 for which $\sup_{Q\subseteq\mathbb{R}^{n}}\frac{1}{|Q|}\int_{Q}e^{\frac{|f-f_{Q}|}{A}}\mathrm{d}x<\infty.$

The John–Nirenberg inequality implies that A(f)≤C||f||BMO for some universal constant C. For an L function, however, the above inequality will hold for all A>0. In other words, A(f)=0 if f is in L. Hence the constant A(f) gives us a way of measuring how far a function in BMO is from the subspace L. This statement can be made more precise: there is a constant C, depending only on the dimension n, such that for any function f ∈ BMO(ℝn) the following two-sided inequality holds $\frac{1}{C}A(f)\leq \inf_{g\in L^{\infty}}||f-g||_{BMO}\leq CA(f).$

## Generalizations and extensions

### The spaces BMOH and BMOA

When the dimension of the ambient space is 1, the space BMO can be seen as a subspace of harmonic functions on the unit disk and plays a major role in the theory of Hardy spaces: by using definition 2, it is possible to define the BMO(T) space on the unit circle as the space of functions $f:T\rightarrow \mathbb{R}$ such that $\frac{1}{|I|}\int_{I}|f(y)-f_I|\,\mathrm{d}y < +\infty$

i.e. such that its mean oscillation over every arc I of the unit circle is bounded. Here as before fI is the mean value of f over the arc I.

Definition 3. An Analytic function on the unit disk is said to belong to the Harmonic BMO or in the BMOH space if and only if it is the Poisson integral of a BMO(T) function. Therefore BMOH is the space of all functions u with the form: $u(a)=\frac{1}{2\pi}\int_{\mathbb{T}}\frac{1-|a|^2}{|a-e^{i\theta}|^2}f(e^{i\theta})\,\mathrm{d}\theta$

equipped with the norm: $\|u\|_{BMOH}=\sup _ {|a|<1}\left\{\frac{1}{2\pi}\int_{\mathbb{T}}\frac{1-|a|^2}{|a-e^{i\theta}|^2}|f(e^{i\theta})-u(a)|\,\mathrm{d}\theta\right\}$

The subspace of analytic functions belonging BMOH is called the Analytic BMO space or the BMOA space.

#### BMOA as the dual space of H1(D)

Charles Fefferman in his original paper proved that the real BMO space is dual to the real valued harmonic Hardy space on the upper half-spacen× $\scriptstyle(0,+\infty]$ . Today in the theory of Complex and Harmonic analysis the following - modern - approach for analytic functions, is more often considered. Let Hp(D) be the Analytic Hardy space on the unit Disc. For p = 1 we identify (H1)* with BMOA by pairing f ∈H1(D) and g ∈ BMOA using the anti-linear transformation Tg $T_g(f)=\lim_{r \rightarrow 1}\int_{-\pi}^{\pi}\bar{g}(e^{i\theta})f(re^{i\theta}) \, \mathrm{d}\theta$

Notice that although the limit always exists for an H1 function f and Tg is an element of the dual space (H1)*, since the transformation is anti-linear, we don't have an isometric isomorphism between (H1)* and BMOA. However one can obtain an isometry if they consider a kind of space of conjugate BMOA functions.

### The space VMO

The space VMO of functions of vanishing mean oscillation is the closure in BMO of the continuous functions that vanish at infinity. It can also be defined as the space of functions whose "mean oscillations" on cubes Q are not only bounded, but also tend to zero uniformly as the radius of the cube Q tends to 0 or infinity. The space VMO is a sort of Hardy space analogue of the space of continuous functions vanishing at infinity, and in particular the real valued harmonic Hardy space H1 is the dual of VMO.

Let Δ denote the set of dyadic cubes in n. The space dyadic BMO, written BMOd is the space of functions satisfying the same inequality as for BMO functions, only that the supremum is over all dyadic cubes. This supremum is sometimes denoted ||•||BMOd.

This space is contained in but still distinct from BMO as it depends greatly on the position of the dyadic cubes. In particular, the function log(x)χ[0,∞) is a function that is in dyadic BMO but not in BMO. However, if a function f is such that ||f(•-x)||BMOd≤C for all x in n for some C>0, then by the one-third trick f is also in BMO.

Although dyadic BMO is a much narrower class than BMO, many theorems that are true for BMO are much simpler to prove for dyadic BMO, and in some cases one can recover the original BMO theorems by proving them first in the special dyadic case.

## Examples

Examples of BMO functions include the following:

• All bounded (measurable) functions. If f is in L, then ||f||BMO≤2||f||: however, the converse is not true as the following example shows.
• The function log(|P|) for any polynomial P that is not identically zero: in particular, this is true also for |P(x)|=|x|.
• If w is an A weight, then log(w) is BMO. Conversely, if f is BMO, then eδf is an A weight for δ>0 small enough: this fact is a consequence of the John-Nirenberg Inequality.

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