Uniform convergence

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In the mathematical field of analysis, uniform convergence is a type of convergence stronger than pointwise convergence. A sequence {fn} of functions converges uniformly to a limiting function f if the speed of convergence of fn(x) to f(x) does not depend on x.

The concept is important because several properties of the functions fn, such as continuity and Riemann integrability, are transferred to the limit f if the convergence is uniform, but not necessarily if the convergence is not.

Uniform convergence to a function on a given interval can be defined in terms of the uniform norm.


In 1821 Augustin Louis Cauchy published a proof that a convergent sum of continuous functions is always continuous, to which Niels Henrik Abel in 1826 found purported counterexamples in the context of Fourier series, arguing that Cauchy's proof had to be incorrect. Completely standard notions of convergence did not exist at the time, and Cauchy handled convergence using infinitesimal methods. When put into the modern language, what Cauchy proved is that a uniformly convergent sequence of continuous functions has a continuous limit. The failure of a merely pointwise-convergent limit of continuous functions to converge to a continuous function illustrates the importance of distinguishing between different types of convergence when handling sequences of functions.[1]

The term uniform convergence was probably first used by Christoph Gudermann, in an 1838 paper on elliptic functions, where he employed the phrase "convergence in a uniform way" when the "mode of convergence" of a series \textstyle{\sum_{n=1}^\infty f_n(x,\phi,\psi)} is independent of the variables \phi and \psi. While he thought it a "remarkable fact" when a series converged in this way, he did not give a formal definition, nor use the property in any of his proofs.[2]

Later Gudermann's pupil Karl Weierstrass, who attended his course on elliptic functions in 1839–1840, coined the term gleichmäßig konvergent (German: uniformly convergent) which he used in his 1841 paper Zur Theorie der Potenzreihen, published in 1894. Independently a similar concept was used by Philipp Ludwig von Seidel[3] and George Gabriel Stokes but without having any major impact on further development.[citation needed] G. H. Hardy compares the three definitions in his paper "Sir George Stokes and the concept of uniform convergence" and remarks: "Weierstrass's discovery was the earliest, and he alone fully realized its far-reaching importance as one of the fundamental ideas of analysis."

Under the influence of Weierstrass and Bernhard Riemann this concept and related questions were intensely studied at the end of the 19th century by Hermann Hankel, Paul du Bois-Reymond, Ulisse Dini, Cesare Arzelà and others.


Suppose S is a set and f_n: S \to \mathbb R is a real-valued function for every natural number  n . We say that the sequence (f_n)_{n \in \mathbb N} is uniformly convergent with limit  f: S \to \mathbb R if for every  \varepsilon > 0 , there exists a natural number  N such that for all  x \in S and all  n \geq N we have  |f_n(x) - f(x)| < \varepsilon .

Consider the sequence  a_n = \sup_x |f_n(x) - f(x) | where the supremum is taken over all  x \in S . Then  f_n converges to  f uniformly if and only if  a_n tends to 0.

The sequence  (f_n)_{n \in \mathbb N} is said to be locally uniformly convergent with limit  f if  S is a metric space and for every  x in  S , there exists an  r > 0 such that  (f_n) converges uniformly on  B(x,r) \cap S .


Note that interchanging the order of "there exists N" and "for all x" in the definition above results in a statement equivalent to the pointwise convergence of the sequence. That notion can be defined as follows: the sequence (fn) converges pointwise with limit f : SR if and only if

for every xS and every ε > 0, there exists a natural number N such that for all nN one has |fn(x) − f(x)| < ε.

Here the order of the universal quantifiers for x and for ε is not important, but the order of the former and the existential quantifier for N is.

In the case of uniform convergence, N can only depend on ε, while in the case of pointwise convergence N may depend on both ε and x. It is therefore plain that uniform convergence implies pointwise convergence. The converse is not true, as the following example shows: take S to be the unit interval [0,1] and define fn(x) = xn for every natural number n. Then (fn) converges pointwise to the function f defined by f(x) = 0 if x < 1 and f(1) = 1. This convergence is not uniform: for instance for ε = 1/4, there exists no N as required by the definition. This is because solving for n gives n > log ε / log x. This depends on x as well as on ε. Also note that it is impossible to find a suitable bound for n that does not depend on x because for any nonzero value of ε, log ε / log x grows without bounds as x tends to 1.


One may straightforwardly extend the concept to functions SM, where (M, d) is a metric space, by replacing |fn(x) − f(x)| with d(fn(x), f(x)).

The most general setting is the uniform convergence of nets of functions SX, where X is a uniform space. We say that the net (fα) converges uniformly with limit f : SX if and only if

for every entourage V in X, there exists an α0, such that for every x in S and every α ≥ α0: (fα(x), f(x)) is in V.

The above-mentioned theorem, stating that the uniform limit of continuous functions is continuous, remains correct in these settings.

Definition in a hyperreal setting[edit]

Uniform convergence admits a simplified definition in a hyperreal setting. Thus, a sequence f_n converges to f uniformly if for all x in the domain of f* and all infinite n, f_n^*(x) is infinitely close to f^*(x) (see microcontinuity for a similar definition of uniform continuity).


Given a topological space X, we can equip the space of bounded real or complex-valued functions over X with the uniform norm topology. Then uniform convergence simply means convergence in the uniform norm topology.

The sequence  f_n:[0,1]\rightarrow [0,1] with  f_n(x):=x^n converges pointwise but not uniformly:

\lim_{n\rightarrow \infty} f_n(x) = \begin{cases} 0, & x \in [0,1) \\ 1, & x=1. \end{cases}

In this example one can easily see that pointwise convergence does not preserve differentiability or continuity. While each function of the sequence is smooth, that is to say that for all n, f_n\in C^{\infty}([0,1]), the limit \lim_{n\rightarrow \infty}f_n is not even continuous.

Exponential function[edit]

The series expansion of the exponential function can be shown to be uniformly convergent on any bounded subset S of \mathbb{C} using the Weierstrass M-test.

Here is the series:


Any bounded subset is a subset of some disc D_R of radius R, centered on the origin in the complex plane. The Weierstrass M-test requires us to find an upper bound M_n on the terms of the series, with M_n independent of the position in the disc:

\left| \frac{z^n}{n!}\right|\le M_n     , \forall z\in D_R.

This is trivial:

\left| \frac{z^n}{n!}\right| \le \frac{\left| z\right|^n}{n!} \le \frac{R^n}{n!}
\Rightarrow M_n=\frac{R^n}{n!}.

If \sum_{n=0}^{\infty}M_n is convergent, then the M-test asserts that the original series is uniformly convergent.

The ratio test can be used here:

\lim_{n \to \infty}\frac{M_{n+1}}{M_n}=\lim_{n \to \infty}\frac{R^{n+1}}{R^n}\frac{n!}{(n+1)!}=\lim_{n \to \infty}\frac{R}{n+1}=0

which means the series over M_n is convergent. Thus the original series converges uniformly for all z\in D_R, and since S\subset D_R, the series is also uniformly convergent on S.


  • Every uniformly convergent sequence is locally uniformly convergent.
  • Every locally uniformly convergent sequence is compactly convergent.
  • For locally compact spaces local uniform convergence and compact convergence coincide.
  • A sequence of continuous functions on metric spaces, with the image metric space being complete, is uniformly convergent if and only if it is uniformly Cauchy.
  • If S is a compact interval (or in general a compact topological space), and  (f_n) is a monotone increasing sequence (meaning  f_n(x) \leq f_{n+1}(x) for all n and x) of continuous functions with a pointwise limit  f which is also continuous, then the convergence is necessarily uniform (Dini's theorem). Uniform convergence is also guaranteed if  S is a compact interval and (f_n) is an equicontinuous sequence that converges pointwise.


To continuity[edit]

Main article: Uniform limit theorem
Counterexample to a strengthening of the uniform convergence theorem, in which pointwise convergence, rather than uniform convergence, is assumed. The continuous green functions \sin^n(x) converge to the non-continuous red function. This can happen only if convergence is not uniform.

If I is a real interval (or indeed any topological space), we can talk about the continuity of the functions fn and f. The following is the more important result about uniform convergence:

Uniform convergence theorem. If (fn) is a sequence of continuous functions all of which are defined on the interval I which converges uniformly towards the function f on an interval I, then f is continuous on I as well.

This theorem is proved by the "ε/3 trick", and is the archetypal example of this trick: to prove a given inequality (ε), one uses the definitions of continuity and uniform convergence to produce 3 inequalities (ε/3), and then combines them via the triangle inequality to produce the desired inequality.

This theorem is important, since pointwise convergence of continuous functions is not enough to guarantee continuity of the limit function as the image illustrates.

More precisely, this theorem states that the uniform limit of uniformly continuous functions is uniformly continuous; for a locally compact space, continuity is equivalent to local uniform continuity, and thus the uniform limit of continuous functions is continuous.

To differentiability[edit]

If S is an interval and all the functions fn are differentiable and converge to a limit f, it is often desirable to differentiate the limit function f by taking the limit of the derivatives of fn. This is however in general not possible: even if the convergence is uniform, the limit function need not be differentiable, and even if it is differentiable, the derivative of the limit function need not be equal to the limit of the derivatives. Consider for instance f_n(x) = \frac1n \sin(nx) with uniform limit 0, but the derivatives do not approach 0. In order to ensure a connection between the limit of a sequence of differentiable functions and the limit of the sequence of derivatives, the uniform convergence of the sequence of derivatives plus the convergence of the sequence of functions at at least one point is required. The precise statement covering this situation is as follows:[4]

Suppose \scriptstyle {f_n} is a sequence of functions, differentiable on \scriptstyle [a, b], and such that \scriptstyle {f_n(x_0)} converges for some point  \scriptstyle x_0 on \scriptstyle [a, b]. If \scriptstyle f'_n converges uniformly on \scriptstyle [a, b], then \scriptstyle {f_n} converges uniformly to a function \scriptstyle f, and \scriptstyle  f'(x) = \lim_{n\to \infty} f'_n(x) for \scriptstyle x \in [a, b].

To integrability[edit]

Similarly, one often wants to exchange integrals and limit processes. For the Riemann integral, this can be done if uniform convergence is assumed:

If (f_n)_{n=1}^\infty is a sequence of Riemann integrable functions defined on a compact interval I which uniformly converge with limit  f, then  f is Riemann integrable and its integral can be computed as the limit of the integrals of the  f_n:
\int_I f = \lim_{n\to\infty}\int_I f_n.

In fact, for a uniformly convergent family of bounded functions on an interval, the upper and lower Riemann integrals converge to the upper and lower Riemann integrals of the limit function. This follows because, for n sufficiently large, the graph of f_n is within ε of the graph of f, and so the upper sum and lower sum of f_n are each within \varepsilon |I| of the value of the upper and lower sums of f, respectively.

Much stronger theorems in this respect, which require not much more than pointwise convergence, can be obtained if one abandons the Riemann integral and uses the Lebesgue integral instead.

To analyticity[edit]

If a sequence of analytic functions converges uniformly in a region S of the complex plane, then the limit is analytic in S. This demonstrates an example that complex functions are more well-behaved than real functions, since the uniform limit of analytic functions on a real interval need not even be differentiable (see Weierstrass function).

To series[edit]

We say that \textstyle\sum_{n=1}^\infty f_n converges:

i) pointwise on E if and only if the sequence sn converges where sn(x) is the sequence of partial sums.

ii) uniformly on E if and only if sn(x) converges uniformly as n goes to infinity.

iii) absolutely on E if and only if \textstyle\sum_{n=1}^\infty |f_n| converges for each x in E.

With this definition comes the following result: Theorem: Let x0 be contained in the set E and for each fn is continuous at x0. If f = \textstyle\sum_{n=1}^\infty f_n converges uniformly on E then f is continuous at x0 in E. Suppose that E = [a, b] and each fn is integrable on [a, b]. If \textstyle\sum_{n=1}^\infty f_n converges uniformly on [a, b] then f is integrable on [a, b] and the series of integrals of fn is equal to integral of the series of fn. This is known as term by term integration.

Almost uniform convergence[edit]

If the domain of the functions is a measure space E then the related notion of almost uniform convergence can be defined. We say a sequence of functions (f_n) converges almost uniformly on E if for every \delta > 0 there exists a measurable set E_\delta with measure less than \delta such that the sequence of functions (f_n) converges uniformly on E \setminus E_\delta. In other words, almost uniform convergence means there are sets of arbitrarily small measure for which the sequence of functions converges uniformly on their complement.

Note that almost uniform convergence of a sequence does not mean that the sequence converges uniformly almost everywhere as might be inferred from the name.

Egorov's theorem guarantees that on a finite measure space, a sequence of functions that converges almost everywhere also converges almost uniformly on the same set.

Almost uniform convergence implies almost everywhere convergence and convergence in measure.

See also[edit]


  1. ^ "Exceptions and counterexamples: Understanding Abel's comment on Cauchy's Theorem". Historia Mathematica 32: 453–480. doi:10.1016/j.hm.2004.11.010. 
  2. ^ Jahnke, Hans Niels (2003). "6.7 The Foundation of Analysis in the 19th Century: Weierstrass". A history of analysis. AMS Bookstore. ISBN 978-0-8218-2623-2, p. 184. 
  3. ^ Lakatos, Imre (1976). Proofs and Refutations. Cambridge University Press. p. 141. ISBN 0-521-21078-X. 
  4. ^ Rudin, Walter. Principles of Mathematical Analysis Third edition. 1976. McGraw-Hill International editions.


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