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Uniform continuity

From Wikipedia, the free encyclopedia
Uniform restraint of the change in functions
As the center of the blue window, with real height2εR>0{\displaystyle 2\varepsilon \in \mathbb {R} _{>0}} and real width2δR>0{\displaystyle 2\delta \in \mathbb {R} _{>0}}, moves over the graph off(x)=1x{\displaystyle f(x)={\tfrac {1}{x}}} in the direction ofx=0{\displaystyle x=0}, there comes a point at which the graph off{\displaystyle f} penetrates the (interior of the) top and/or bottom of that window. This means thatf{\displaystyle f} ranges over an interval larger than or equal toε{\displaystyle \varepsilon } over anx{\displaystyle x}-interval smaller thanδ{\displaystyle \delta }. If there existed a window whereof top and/or bottom is never penetrated by the graph off{\displaystyle f} as the window moves along it over its domain, then that window's width would need to be infinitesimally small (nonreal), meaning thatf(x){\displaystyle f(x)} isnot uniformly continuous. The functiong(x)=x{\displaystyle g(x)={\sqrt {x}}}, on the other hand,is uniformly continuous.

Inmathematics, a realfunctionf{\displaystyle f} of real numbers is said to beuniformly continuous if there is a positive real numberδ{\displaystyle \delta } such that function values over any function domain interval of the sizeδ{\displaystyle \delta } are as close to each other as we want. In other words, for a uniformly continuous real function of real numbers, if we want function value differences to be less than any positive real numberε{\displaystyle \varepsilon }, then there is a positive real numberδ{\displaystyle \delta } such that|f(x)f(y)|<ε{\displaystyle |f(x)-f(y)|<\varepsilon } for anyx{\displaystyle x} andy{\displaystyle y} in any interval of lengthδ{\displaystyle \delta } within the domain off{\displaystyle f}.

The difference between uniform continuity and (ordinary)continuity is that in uniform continuity there is aglobally applicableδ{\displaystyle \delta } (the size of a function domain interval over which function value differences are less thanε{\displaystyle \varepsilon }) that depends on onlyε{\displaystyle \varepsilon }, while in (ordinary) continuity there is alocally applicableδ{\displaystyle \delta } that depends on bothε{\displaystyle \varepsilon } andx{\displaystyle x}. So uniform continuity is a stronger continuity condition than continuity; a function that is uniformly continuous is continuous but a function that is continuous is not necessarily uniformly continuous. The concepts of uniform continuity and continuity can be expanded to functions defined betweenmetric spaces.

Continuous functions can fail to be uniformly continuous if they are unbounded on a bounded domain, such asf(x)=1x{\displaystyle f(x)={\tfrac {1}{x}}} on(0,1){\displaystyle (0,1)}, or if their slopes become unbounded on an infinite domain, such asf(x)=x2{\displaystyle f(x)=x^{2}} on the real (number) line. However, anyLipschitz map between metric spaces is uniformly continuous, in particular anyisometry (distance-preserving map).

Although continuity can be defined for functions between general topological spaces, defining uniform continuity requires more structure. The concept relies on comparing the sizes ofneighbourhoods of distinct points, so it requires a metric space, or more generally auniform space.

Definition for functions on metric spaces

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For a functionf:XY{\displaystyle f:X\to Y} withmetric spaces(X,d1){\displaystyle (X,d_{1})} and(Y,d2){\displaystyle (Y,d_{2})}, the following definitions of uniform continuity and (ordinary) continuity hold.

Definition of uniform continuity

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Definition of (ordinary) continuity

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Local continuity versus global uniform continuity

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In the definitions, the difference between uniform continuity andcontinuity is that, in uniform continuity there is a globally applicableδ{\displaystyle \delta } (the size of a neighbourhood inX{\displaystyle X} over which values of the metric for function values inY{\displaystyle Y} are less thanε{\displaystyle \varepsilon }) that depends on onlyε{\displaystyle \varepsilon } while in continuity there is a locally applicableδ{\displaystyle \delta } that depends on the bothε{\displaystyle \varepsilon } andx{\displaystyle x}. Continuity is alocal property of a function — that is, a functionf{\displaystyle f} is continuous, or not, at a particular pointx{\displaystyle x} of the function domainX{\displaystyle X}, and this can be determined by looking at only the values of the function in an arbitrarily small neighbourhood of that point. When we speak of a function being continuous on aninterval, we mean that the function is continuous at every point of the interval. In contrast, uniform continuity is aglobal property off{\displaystyle f}, in the sense that the standard definition of uniform continuity refers to every point ofX{\displaystyle X}. On the other hand, it is possible to give a definition that islocal in terms of the natural extensionf{\displaystyle f^{*}}(the characteristics of which at nonstandard points are determined by the global properties off{\displaystyle f}), although it is not possible to give a local definition of uniform continuity for an arbitrary hyperreal-valued function, seebelow.

A mathematical definition that a functionf{\displaystyle f} is continuous on an intervalI{\displaystyle I} and a definition thatf{\displaystyle f} is uniformly continuous onI{\displaystyle I} are structurally similar as shown in the following.

Continuity of a functionf:XY{\displaystyle f:X\to Y} formetric spaces(X,d1){\displaystyle (X,d_{1})} and(Y,d2){\displaystyle (Y,d_{2})} at every pointx{\displaystyle x} of an intervalIX{\displaystyle I\subseteq X} (i.e., continuity off{\displaystyle f} on the intervalI{\displaystyle I}) is expressed by a formula starting withquantifications

xIε>0δ>0yI:d1(x,y)<δd2(f(x),f(y))<ε{\displaystyle \forall x\in I\;\forall \varepsilon >0\;\exists \delta >0\;\forall y\in I:\,d_{1}(x,y)<\delta \,\Rightarrow \,d_{2}(f(x),f(y))<\varepsilon },

(metricsd1(x,y){\displaystyle d_{1}(x,y)} andd2(f(x),f(y)){\displaystyle d_{2}(f(x),f(y))} are|xy|{\displaystyle |x-y|} and|f(x)f(y)|{\displaystyle |f(x)-f(y)|} forf:RR{\displaystyle f:\mathbb {R} \to \mathbb {R} } forthe set of real numbersR{\displaystyle \mathbb {R} }).

For uniform continuity, the order of the first, second, and thirdquantifications (xI{\displaystyle \forall x\in I},ε>0{\displaystyle \forall \varepsilon >0}, andδ>0{\displaystyle \exists \delta >0}) are rotated:

ε>0δ>0xIyI:d1(x,y)<δd2(f(x),f(y))<ε{\displaystyle \forall \varepsilon >0\;\exists \delta >0\;\forall x\in I\;\forall y\in I:\,d_{1}(x,y)<\delta \,\Rightarrow \,d_{2}(f(x),f(y))<\varepsilon }.

Thus for continuity on the interval, one takes an arbitrary pointx{\displaystyle x} of the interval, and then there must exist a distanceδ{\displaystyle \delta },

xδ,{\displaystyle \cdots \forall x\,\exists \delta \cdots ,}

while for uniform continuity, a singleδ{\displaystyle \delta } must work uniformly for all pointsx{\displaystyle x} of the interval,

δx.{\displaystyle \cdots \exists \delta \,\forall x\cdots .}

Properties

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Every uniformly continuous function iscontinuous, but the converse does not hold. Consider for instance the continuous functionf:RR,xx2{\displaystyle f\colon \mathbb {R} \rightarrow \mathbb {R} ,x\mapsto x^{2}} whereR{\displaystyle \mathbb {R} } isthe set of real numbers. Given a positive real numberε{\displaystyle \varepsilon }, uniform continuity requires the existence of a positive real numberδ{\displaystyle \delta } such that for allx1,x2R{\displaystyle x_{1},x_{2}\in \mathbb {R} } with|x1x2|<δ{\displaystyle |x_{1}-x_{2}|<\delta }, we have|f(x1)f(x2)|<ε{\displaystyle |f(x_{1})-f(x_{2})|<\varepsilon }. But

f(x+δ)f(x)=2xδ+δ2,{\displaystyle f\left(x+\delta \right)-f(x)=2x\cdot \delta +\delta ^{2},}

and asx{\displaystyle x} goes to be a higher and higher value,δ{\displaystyle \delta } needs to be lower and lower to satisfy|f(x+β)f(x)|<ε{\displaystyle |f(x+\beta )-f(x)|<\varepsilon } for positive real numbersβ<δ{\displaystyle \beta <\delta } and the givenε{\displaystyle \varepsilon }. This means that there is no specifiable (no matter how small it is) positive real numberδ{\displaystyle \delta } to satisfy the condition forf{\displaystyle f} to be uniformly continuous sof{\displaystyle f} is not uniformly continuous.

Anyabsolutely continuous function (over a compact interval) is uniformly continuous. On the other hand, theCantor function is uniformly continuous but not absolutely continuous.

The image of atotally bounded subset under a uniformly continuous function is totally bounded. However, the image of a bounded subset of an arbitrary metric space under a uniformly continuous function need not be bounded: as a counterexample, consider the identity function from the integers endowed with thediscrete metric to the integers endowed with the usualEuclidean metric.

TheHeine–Cantor theorem asserts thatevery continuous function on acompact set is uniformly continuous. In particular,if a function is continuous on aclosed bounded interval of the real line, it is uniformly continuous on that interval. TheDarboux integrability of continuous functions follows almost immediately from this theorem.

If a real-valued functionf{\displaystyle f} is continuous on[0,){\displaystyle [0,\infty )} andlimxf(x){\displaystyle \lim _{x\to \infty }f(x)} exists (and is finite), thenf{\displaystyle f} is uniformly continuous. In particular, every element ofC0(R){\displaystyle C_{0}(\mathbb {R} )}, the space of continuous functions onR{\displaystyle \mathbb {R} } that vanish at infinity, is uniformly continuous. This is a generalization of the Heine-Cantor theorem mentioned above, sinceCc(R)C0(R){\displaystyle C_{c}(\mathbb {R} )\subset C_{0}(\mathbb {R} )}.

Examples and nonexamples

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Examples

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Nonexamples

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Visualization

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For a uniformly continuous function, for every positive real numberε>0{\displaystyle \varepsilon >0} there is a positive real numberδ>0{\displaystyle \delta >0} such that two function valuesf(x){\displaystyle f(x)} andf(y){\displaystyle f(y)} have the maximum distanceε{\displaystyle \varepsilon } wheneverx{\displaystyle x} andy{\displaystyle y} are within the maximum distanceδ{\displaystyle \delta }. Thus at each point(x,f(x)){\displaystyle (x,f(x))} of the graph, if we draw a rectangle with a height slightly less than2ε{\displaystyle 2\varepsilon } and width a slightly less than2δ{\displaystyle 2\delta } around that point, then the graph lies completely within the height of the rectangle, i.e., the graph do not pass through the top or the bottom side of the rectangle. For functions that are not uniformly continuous, this isn't possible; for these functions, the graph might lie inside the height of the rectangle at some point on the graph but there is a point on the graph where the graph lies above or below the rectangle. (the graph penetrates the top or bottom side of the rectangle.)

History

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The first published definition of uniform continuity was byHeine in 1870, and in 1872 he published a proof that a continuous function on an open interval need not be uniformly continuous. The proofs are almost verbatim given byDirichlet in his lectures on definite integrals in 1854. The definition of uniform continuity appears earlier in the work of Bolzano where he also proved that continuous functions on an open interval do not need to be uniformly continuous. In addition he also states that a continuous function on a closed interval is uniformly continuous, but he does not give a complete proof.[1]

Other characterizations

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Non-standard analysis

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Innon-standard analysis, a real-valued functionf{\displaystyle f} of a real variable ismicrocontinuous at a pointa{\displaystyle a} precisely if the differencef(a+δ)f(a){\displaystyle f^{*}(a+\delta )-f^{*}(a)} is infinitesimal wheneverδ{\displaystyle \delta } is infinitesimal. Thusf{\displaystyle f} is continuous on a setA{\displaystyle A} inR{\displaystyle \mathbb {R} } precisely iff{\displaystyle f^{*}} is microcontinuous at every real pointaA{\displaystyle a\in A}. Uniform continuity can be expressed as the condition that (the natural extension of)f{\displaystyle f} is microcontinuous not only at real points inA{\displaystyle A}, but at all points in its non-standard counterpart (natural extension)A{\displaystyle ^{*}A} inR{\displaystyle ^{*}\mathbb {R} }. Note that there exist hyperreal-valued functions which meet this criterion but are not uniformly continuous, as well as uniformly continuous hyperreal-valued functions which do not meet this criterion, however, such functions cannot be expressed in the formf{\displaystyle f^{*}} for any real-valued functionf{\displaystyle f}. (seenon-standard calculus for more details and examples).

Cauchy continuity

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For a function between metric spaces, uniform continuity impliesCauchy continuity (Fitzpatrick 2006). More specifically, letA{\displaystyle A} be a subset ofRn{\displaystyle \mathbb {R} ^{n}}. If a functionf:ARn{\displaystyle f:A\to \mathbb {R} ^{n}} is uniformly continuous then for every pair of sequencesxn{\displaystyle x_{n}} andyn{\displaystyle y_{n}} such that

limn|xnyn|=0{\displaystyle \lim _{n\to \infty }|x_{n}-y_{n}|=0}

we have

limn|f(xn)f(yn)|=0.{\displaystyle \lim _{n\to \infty }|f(x_{n})-f(y_{n})|=0.}

Relations with the extension problem

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LetX{\displaystyle X} be a metric space,S{\displaystyle S} a subset ofX{\displaystyle X},R{\displaystyle R} a complete metric space, andf:SR{\displaystyle f:S\rightarrow R} a continuous function. A question to answer:When canf{\displaystyle f} be extended to a continuous function on all ofX{\displaystyle X}?

IfS{\displaystyle S} is closed inX{\displaystyle X}, the answer is given by theTietze extension theorem. So it is necessary and sufficient to extendf{\displaystyle f} to the closure ofS{\displaystyle S} inX{\displaystyle X}: that is, we may assume without loss of generality thatS{\displaystyle S} is dense inX{\displaystyle X}, and this has the further pleasant consequence that if the extension exists, it is unique. A sufficient condition forf{\displaystyle f} to extend to a continuous functionf:XR{\displaystyle f:X\rightarrow R} is that it isCauchy-continuous, i.e., the image underf{\displaystyle f} of a Cauchy sequence remains Cauchy. IfX{\displaystyle X} is complete (and thus the completion ofS{\displaystyle S}), then every continuous function fromX{\displaystyle X} to a metric spaceY{\displaystyle Y} is Cauchy-continuous. Therefore whenX{\displaystyle X} is complete,f{\displaystyle f} extends to a continuous functionf:XR{\displaystyle f:X\rightarrow R} if and only iff{\displaystyle f} is Cauchy-continuous.

It is easy to see that every uniformly continuous function is Cauchy-continuous and thus extends toX{\displaystyle X}. The converse does not hold, since the functionf:RR,xx2{\displaystyle f:R\rightarrow R,x\mapsto x^{2}} is, as seen above, not uniformly continuous, but it is continuous and thus Cauchy continuous. In general, for functions defined on unbounded spaces likeR{\displaystyle R}, uniform continuity is a rather strong condition. It is desirable to have a weaker condition from which to deduce extendability.

For example, supposea>1{\displaystyle a>1} is a real number. At the precalculus level, the functionf:xax{\displaystyle f:x\mapsto a^{x}} can be given a precise definition only for rational values ofx{\displaystyle x} (assuming the existence of qth roots of positive real numbers, an application of theIntermediate Value Theorem). One would like to extendf{\displaystyle f} to a function defined on all ofR{\displaystyle R}. The identity

f(x+δ)f(x)=ax(aδ1){\displaystyle f(x+\delta )-f(x)=a^{x}\left(a^{\delta }-1\right)}

shows thatf{\displaystyle f} is not uniformly continuous on the setQ{\displaystyle Q} of all rational numbers; however for any bounded intervalI{\displaystyle I} the restriction off{\displaystyle f} toQI{\displaystyle Q\cap I} is uniformly continuous, hence Cauchy-continuous, hencef{\displaystyle f} extends to a continuous function onI{\displaystyle I}. But since this holds for everyI{\displaystyle I}, there is then a unique extension off{\displaystyle f} to a continuous function on all ofR{\displaystyle R}.

More generally, a continuous functionf:SR{\displaystyle f:S\rightarrow R} whose restriction to every bounded subset ofS{\displaystyle S} is uniformly continuous is extendable toX{\displaystyle X}, and the converse holds ifX{\displaystyle X} islocally compact.

A typical application of the extendability of a uniformly continuous function is the proof of the inverseFourier transformation formula. We first prove that the formula is true for test functions, there are densely many of them. We then extend the inverse map to the whole space using the fact that linear map is continuous; thus, uniformly continuous.

Generalization to topological vector spaces

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In the special case of twotopological vector spacesV{\displaystyle V} andW{\displaystyle W}, the notion of uniform continuity of a mapf:VW{\displaystyle f:V\to W} becomes: for any neighborhoodB{\displaystyle B} of zero inW{\displaystyle W}, there exists a neighborhoodA{\displaystyle A} of zero inV{\displaystyle V} such thatv1v2A{\displaystyle v_{1}-v_{2}\in A} impliesf(v1)f(v2)B.{\displaystyle f(v_{1})-f(v_{2})\in B.}

Forlinear transformationsf:VW{\displaystyle f:V\to W}, uniform continuity is equivalent to continuity. This fact is frequently used implicitly infunctional analysis to extend a linear map off a dense subspace of aBanach space.

Generalization to uniform spaces

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Just as the most natural and general setting for continuity istopological spaces, the most natural and general setting for the study ofuniform continuity are theuniform spaces. A functionf:XY{\displaystyle f:X\to Y} between uniform spaces is calleduniformly continuous if for everyentourageV{\displaystyle V} inY{\displaystyle Y} there exists an entourageU{\displaystyle U} inX{\displaystyle X} such that for every(x1,x2){\displaystyle (x_{1},x_{2})} inU{\displaystyle U} we have(f(x1),f(x2)){\displaystyle (f(x_{1}),f(x_{2}))} inV{\displaystyle V}.

In this setting, it is also true that uniformly continuous maps transform Cauchy sequences into Cauchy sequences.

Eachcompact Hausdorff space possesses exactly one uniform structure compatible with the topology. A consequence is a generalization of the Heine-Cantor theorem: each continuous function from a compact Hausdorff space to a uniform space is uniformly continuous.

See also

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References

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  1. ^Rusnock & Kerr-Lawson 2005.

Further reading

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Basic concepts
Main results
Maps
Types of
metric spaces
Sets
Examples
Manifolds
Functional analysis
andMeasure theory
General topology
Related
Generalizations
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