Riemann–Lebesgue Lemma
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In
mathematics Mathematics is a field of study that discovers and organizes methods, Mathematical theory, theories and theorems that are developed and Mathematical proof, proved for the needs of empirical sciences and mathematics itself. There are many ar ...
, the Riemann–Lebesgue lemma, named after
Bernhard Riemann Georg Friedrich Bernhard Riemann (; ; 17September 182620July 1866) was a German mathematician who made profound contributions to analysis, number theory, and differential geometry. In the field of real analysis, he is mostly known for the f ...
and
Henri Lebesgue Henri Léon Lebesgue (; ; June 28, 1875 – July 26, 1941) was a French mathematician known for his Lebesgue integration, theory of integration, which was a generalization of the 17th-century concept of integration—summing the area between an ...
, states that the
Fourier transform In mathematics, the Fourier transform (FT) is an integral transform that takes a function as input then outputs another function that describes the extent to which various frequencies are present in the original function. The output of the tr ...
or
Laplace transform In mathematics, the Laplace transform, named after Pierre-Simon Laplace (), is an integral transform that converts a Function (mathematics), function of a Real number, real Variable (mathematics), variable (usually t, in the ''time domain'') to a f ...
of an ''L''1 function vanishes at infinity. It is of importance in
harmonic analysis Harmonic analysis is a branch of mathematics concerned with investigating the connections between a function and its representation in frequency. The frequency representation is found by using the Fourier transform for functions on unbounded do ...
and
asymptotic analysis In mathematical analysis, asymptotic analysis, also known as asymptotics, is a method of describing Limit (mathematics), limiting behavior. As an illustration, suppose that we are interested in the properties of a function as becomes very larg ...
.


Statement

Let f\in L^1(\R^n) be an integrable function, i.e. f\colon\R^n \rightarrow \C is a
measurable function In mathematics, and in particular measure theory, a measurable function is a function between the underlying sets of two measurable spaces that preserves the structure of the spaces: the preimage of any measurable set is measurable. This is in ...
such that :\, f\, _ = \int_ , f(x), \mathrmx < \infty, and let \hat be the Fourier transform of f, i.e. :\hat\colon\R^n \rightarrow \C, \ \xi\mapsto \int_ f(x) \mathrm^\mathrmx. Then \hat vanishes at infinity: , \hat(\xi), \to 0 as , \xi, \to\infty . Because the Fourier transform of an integrable function is continuous, the Fourier transform \hat is a continuous function vanishing at infinity. If C_0(\R^n) denotes the vector space of continuous functions vanishing at infinity, the Riemann–Lebesgue lemma may be formulated as follows: The Fourier transformation maps L^1(\R^n) to C_0(\R^n).


Proof

We will focus on the one-dimensional case n=1, the proof in higher dimensions is similar. First, suppose that f is continuous and
compactly supported In mathematics, the support of a real-valued function f is the subset of the function domain of elements that are not mapped to zero. If the domain of f is a topological space, then the support of f is instead defined as the smallest closed set ...
. For \xi \neq 0, the substitution \textstyle x\to x+\frac leads to :\hat(\xi) = \int_ f(x) \mathrm^\mathrmx = \int_ f\left(x+\frac\right) \mathrm^ \mathrm^ \mathrmx = -\int_ f\left(x+\frac\right) \mathrm^ \mathrmx . This gives a second formula for \hat(\xi). Taking the mean of both formulas, we arrive at the following estimate: :, \hat(\xi), \le \frac\int_ \left, f(x)-f\left(x+\frac\right)\\mathrmx. Because f is continuous, \left, f(x)-f\left(x+\tfrac\right)\ converges to 0 as , \xi, \to \infty for all x \in \R. Thus, , \hat(\xi), converges to 0 as , \xi, \to \infty due to the
dominated convergence theorem In measure theory, Lebesgue's dominated convergence theorem gives a mild sufficient condition under which limits and integrals of a sequence of functions can be interchanged. More technically it says that if a sequence of functions is bounded i ...
. If f is an arbitrary integrable function, it may be approximated in the L^1 norm by a compactly supported continuous function. For \varepsilon > 0, pick a compactly supported continuous function g such that \, f-g\, _ \leq \varepsilon. Then : \limsup_ , \hat(\xi), \leq \limsup_ \left, \int (f(x)-g(x))\mathrm^ \, \mathrmx\ + \limsup_ \left, \int g(x)\mathrm^ \, \mathrmx\ \leq \varepsilon + 0 = \varepsilon. Because this holds for any \varepsilon > 0, it follows that , \hat(\xi), \to 0 as , \xi, \to\infty .


Other versions

The Riemann–Lebesgue lemma holds in a variety of other situations. * If f \in L^1 z, \to \infty within the half-plane \mathrm(z) \geq 0. * A version holds for
Fourier coefficients A Fourier series () is an Series expansion, expansion of a periodic function into a sum of trigonometric functions. The Fourier series is an example of a trigonometric series. By expressing a function as a sum of sines and cosines, many problems ...
\hat_k of f tend to 0 as k \to \pm \infty . This follows by extending f by zero outside the interval, and then applying the version of the Riemann–Lebesgue lemma on the entire real line. * However, the Riemann–Lebesgue lemma does not hold for arbitrary distributions. For example, the Dirac delta function distribution formally has a finite integral over the real line, but its Fourier transform is a constant and does not vanish at infinity.


Applications

The Riemann–Lebesgue lemma can be used to prove the validity of asymptotic approximations for integrals. Rigorous treatments of the method of steepest descent and the method of stationary phase, amongst others, are based on the Riemann–Lebesgue lemma.


References

* * {{DEFAULTSORT:Riemann-Lebesgue lemma Asymptotic analysis Harmonic analysis Lemmas in mathematical analysis Theorems in mathematical analysis Theorems in harmonic analysis Bernhard Riemann