Uniform convergence


In the mathematical field of analysis, uniform convergence is a mode of convergence of functions stronger than pointwise convergence, in the sense that the convergence is uniform[disambiguation needed] over the domain. A sequence of functions converges uniformly to a limiting function on a set as the function domain if, given any arbitrarily small positive number , a number can be found such that each of the functions differs from by no more than at every point in . Described in an informal way, if converges to uniformly, then how quickly the functions approach is "uniform" throughout in the following sense: in order to guarantee that differs from by less than a chosen distance , we only need to make sure that is larger than or equal to a certain , which we can find without knowing the value of in advance. In other words, there exists a number that could depend on but is independent of , such that choosing will ensure that for all . In contrast, pointwise convergence of to merely guarantees that for any given in advance, we can find (i.e., could depend on the values of both and ) such that, for that particular , falls within of whenever (and a different may require a different, larger for to guarantee that ).

A sequence of functions (fₙ) converges uniformly to f when for arbitrary small ε there is an index N such that the graph of fₙ is in the ε-tube around f whenever n ≥ N.

The difference between uniform convergence and pointwise convergence was not fully appreciated early in the history of calculus, leading to instances of faulty reasoning. The concept, which was first formalized by Karl Weierstrass, is important because several properties of the functions , such as continuity, Riemann integrability, and, with additional hypotheses, differentiability, are transferred to the limit if the convergence is uniform, but not necessarily if the convergence is not uniform.

History edit

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   is independent of the variables   and   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, similar concepts were articulated by Philipp Ludwig von Seidel[3] and George Gabriel Stokes. 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.

Definition edit

We first define uniform convergence for real-valued functions, although the concept is readily generalized to functions mapping to metric spaces and, more generally, uniform spaces (see below).

Suppose   is a set and   is a sequence of real-valued functions on it. We say the sequence   is uniformly convergent on   with limit   if for every   there exists a natural number   such that for all   and for all  


The notation for uniform convergence of   to   is not quite standardized and different authors have used a variety of symbols, including (in roughly decreasing order of popularity):


Frequently, no special symbol is used, and authors simply write


to indicate that convergence is uniform. (In contrast, the expression   on   without an adverb is taken to mean pointwise convergence on  : for all  ,   as  .)

Since   is a complete metric space, the Cauchy criterion can be used to give an equivalent alternative formulation for uniform convergence:   converges uniformly on   (in the previous sense) if and only if for every  , there exists a natural number   such that


In yet another equivalent formulation, if we define


then   converges to   uniformly if and only if   as  . Thus, we can characterize uniform convergence of   on   as (simple) convergence of   in the function space   with respect to the uniform metric (also called the supremum metric), defined by




The sequence   is said to be locally uniformly convergent with limit   if   is a metric space and for every  , there exists an   such that   converges uniformly on   It is clear that uniform convergence implies local uniform convergence, which implies pointwise convergence.

Notes edit

Intuitively, a sequence of functions   converges uniformly to   if, given an arbitrarily small  , we can find an   so that the functions   with   all fall within a "tube" of width   centered around   (i.e., between   and  ) for the entire domain of the function.

Note that interchanging the order of quantifiers in the definition of uniform convergence by moving "for all  " in front of "there exists a natural number  " results in a definition of pointwise convergence of the sequence. To make this difference explicit, in the case of uniform convergence,   can only depend on  , and the choice of   has to work for all  , for a specific value of   that is given. In contrast, in the case of pointwise convergence,   may depend on both   and  , and the choice of   only has to work for the specific values of   and   that are given. Thus uniform convergence implies pointwise convergence, however the converse is not true, as the example in the section below illustrates.

Generalizations edit

One may straightforwardly extend the concept to functions EM, where (M, d) is a metric space, by replacing   with  .

The most general setting is the uniform convergence of nets of functions EX, where X is a uniform space. We say that the net   converges uniformly with limit f : EX if and only if for every entourage V in X, there exists an  , such that for every x in E and every  ,   is in V. In this situation, uniform limit of continuous functions remains continuous.

Definition in a hyperreal setting edit

Uniform convergence admits a simplified definition in a hyperreal setting. Thus, a sequence   converges to f uniformly if for all hyperreal x in the domain of   and all infinite n,   is infinitely close to   (see microcontinuity for a similar definition of uniform continuity). In contrast, pointwise continuity requires this only for real x.

Examples edit

For  , a basic example of uniform convergence can be illustrated as follows: the sequence   converges uniformly, while   does not. Specifically, assume  . Each function   is less than or equal to   when  , regardless of the value of  . On the other hand,   is only less than or equal to   at ever increasing values of   when values of   are selected closer and closer to 1 (explained more in depth further below).

Given a topological space X, we can equip the space of bounded real or complex-valued functions over X with the uniform norm topology, with the uniform metric defined by


Then uniform convergence simply means convergence in the uniform norm topology:


The sequence of functions  


is a classic example of a sequence of functions that converges to a function   pointwise but not uniformly. To show this, we first observe that the pointwise limit of   as   is the function  , given by


Pointwise convergence: Convergence is trivial for   and  , since   and  , for all  . For   and given  , we can ensure that   whenever   by choosing  , which is the minimum integer exponent of   that allows it to reach or dip below   (here the upper square brackets indicate rounding up, see ceiling function). Hence,   pointwise for all  . Note that the choice of   depends on the value of   and  . Moreover, for a fixed choice of  ,   (which cannot be defined to be smaller) grows without bound as   approaches 1. These observations preclude the possibility of uniform convergence.

Non-uniformity of convergence: The convergence is not uniform, because we can find an   so that no matter how large we choose   there will be values of   and   such that   To see this, first observe that regardless of how large   becomes, there is always an   such that   Thus, if we choose   we can never find an   such that   for all   and  . Explicitly, whatever candidate we choose for  , consider the value of   at  . Since


the candidate fails because we have found an example of an   that "escaped" our attempt to "confine" each   to within   of   for all  . In fact, it is easy to see that


contrary to the requirement that   if  .

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,  , the limit   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   using the Weierstrass M-test.

Theorem (Weierstrass M-test). Let   be a sequence of functions   and let   be a sequence of positive real numbers such that   for all   and   If   converges, then   converges absolutely and uniformly on  .

The complex exponential function can be expressed as the series:


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


To do this, we notice


and take  

If   is convergent, then the M-test asserts that the original series is uniformly convergent.

The ratio test can be used here:


which means the series over   is convergent. Thus the original series converges uniformly for all   and since  , the series is also uniformly convergent on  

Properties edit

  • 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   is a compact interval (or in general a compact topological space), and   is a monotone increasing sequence (meaning   for all n and x) of continuous functions with a pointwise limit   which is also continuous, then the convergence is necessarily uniform (Dini's theorem). Uniform convergence is also guaranteed if   is a compact interval and   is an equicontinuous sequence that converges pointwise.

Applications edit

To continuity edit

Counterexample to a strengthening of the uniform convergence theorem, in which pointwise convergence, rather than uniform convergence, is assumed. The continuous green functions   converge to the non-continuous red function. This can happen only if convergence is not uniform.

If   and   are topological spaces, then it makes sense to talk about the continuity of the functions  . If we further assume that   is a metric space, then (uniform) convergence of the   to   is also well defined. The following result states that continuity is preserved by uniform convergence:

Uniform limit theorem — Suppose   is a topological space,   is a metric space, and   is a sequence of continuous functions  . If   on  , then   is also continuous.

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 an important one in the history of real and Fourier analysis, since many 18th century mathematicians had the intuitive understanding that a sequence of continuous functions always converges to a continuous function. The image above shows a counterexample, and many discontinuous functions could, in fact, be written as a Fourier series of continuous functions. The erroneous claim that the pointwise limit of a sequence of continuous functions is continuous (originally stated in terms of convergent series of continuous functions) is infamously known as "Cauchy's wrong theorem". The uniform limit theorem shows that a stronger form of convergence, uniform convergence, is needed to ensure the preservation of continuity in the limit function.

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   is an interval and all the functions   are differentiable and converge to a limit  , it is often desirable to determine the derivative function   by taking the limit of the sequence  . This is however in general not possible: even if the convergence is uniform, the limit function need not be differentiable (not even if the sequence consists of everywhere-analytic functions, see Weierstrass function), 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   with uniform limit  . Clearly,   is also identically zero. However, the derivatives of the sequence of functions are given by   and the sequence   does not converge to   or even to any function at all. 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:[4]

If   is a sequence of differentiable functions on   such that   exists (and is finite) for some   and the sequence   converges uniformly on  , then   converges uniformly to a function   on  , and   for  .

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   is a sequence of Riemann integrable functions defined on a compact interval   which uniformly converge with limit  , then   is Riemann integrable and its integral can be computed as the limit of the integrals of the  :

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   is within ε of the graph of f, and so the upper sum and lower sum of   are each within   of the value of the upper and lower sums of  , 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

Using Morera's Theorem, one can show that if a sequence of analytic functions converges uniformly in a region S of the complex plane, then the limit is analytic in S. This example demonstrates 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   converges:

  1. pointwise on E if and only if the sequence of partial sums   converges for every  .
  2. uniformly on E if and only if sn converges uniformly as  .
  3. absolutely on E if and only if   converges for every  .

With this definition comes the following result:

Let x0 be contained in the set E and each fn be continuous at x0. If   converges uniformly on E then f is continuous at x0 in E. Suppose that   and each fn is integrable on E. If   converges uniformly on E then f is integrable on E and the series of integrals of fn is equal to integral of the series of fn.

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   converges almost uniformly on E if for every   there exists a measurable set   with measure less than   such that the sequence of functions   converges uniformly on  . 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. However, Egorov's theorem does guarantee 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

Notes edit

  1. ^ Sørensen, Henrik Kragh (2005). "Exceptions and counterexamples: Understanding Abel's comment on Cauchy's Theorem". Historia Mathematica. 32 (4): 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. p. 184. ISBN 978-0-8218-2623-2.
  3. ^ Lakatos, Imre (1976). Proofs and Refutations. Cambridge University Press. pp. 141. ISBN 978-0-521-21078-2.
  4. ^ Rudin, Walter (1976). Principles of Mathematical Analysis 3rd edition, Theorem 7.17. McGraw-Hill: New York.

References edit

  • Konrad Knopp, Theory and Application of Infinite Series; Blackie and Son, London, 1954, reprinted by Dover Publications, ISBN 0-486-66165-2.
  • G. H. Hardy, Sir George Stokes and the concept of uniform convergence; Proceedings of the Cambridge Philosophical Society, 19, pp. 148–156 (1918)
  • Bourbaki; Elements of Mathematics: General Topology. Chapters 5–10 (paperback); ISBN 0-387-19374-X
  • Walter Rudin, Principles of Mathematical Analysis, 3rd ed., McGraw–Hill, 1976.
  • Gerald Folland, Real Analysis: Modern Techniques and Their Applications, Second Edition, John Wiley & Sons, Inc., 1999, ISBN 0-471-31716-0.
  • William Wade, An Introduction to Analysis, 3rd ed., Pearson, 2005

External links edit