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| In [[mathematical analysis]], '''Lipschitz continuity''', named after [[Rudolf Lipschitz]], is a strong form of [[uniform continuity]] for [[function (mathematics)|function]]s. Intuitively, a Lipschitz [[continuous function]] is limited in how fast it can change: for every pair of points on the graph of this function, the absolute value of the slope of the line connecting them is no greater than a definite real number; this bound is called the function's "Lipschitz constant" (or "[[modulus of continuity|modulus of uniform continuity]]").
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| In the theory of [[differential equation]]s, Lipschitz continuity is the central condition of the [[Picard–Lindelöf theorem]] which guarantees the existence and uniqueness of the solution to an [[initial value problem]]. A special type of Lipschitz continuity, called [[contraction mapping|contraction]], is used in the [[Banach fixed point theorem]].
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| The concept of Lipschitz continuity is well-defined on [[metric space]]s. A generalization of Lipschitz continuity is called [[Hölder continuity]].
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| == Definitions ==
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| [[Image:Lipschitz continuity.png|thumb|For a Lipschitz continuous function, there is a double cone (shown in white) whose vertex can be translated along the graph, so that the graph always remains entirely outside the cone.]]
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| Given two [[metric space]]s (''X'', ''d''<sub>''X''</sub>) and (''Y'', ''d''<sub>''Y''</sub>), where ''d''<sub>''X''</sub> denotes the [[metric (mathematics)|metric]] on the set ''X'' and ''d''<sub>''Y''</sub> is the metric on set ''Y'' (for example, ''Y'' might be the set of [[real number]]s '''R''' with the metric ''d''<sub>''Y''</sub>(''x'', ''y'') = |''x'' − ''y''|, and ''X'' might be a subset of '''R'''), a function ''f'' : ''X'' → ''Y'' is called '''Lipschitz continuous''' if there exists a real constant ''K'' ≥ 0 such that, for all ''x''<sub>1</sub> and ''x''<sub>2</sub> in ''X'',
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| :<math> d_Y(f(x_1), f(x_2)) \le K d_X(x_1, x_2).</math><ref>{{Citation | last1=Searcóid | first1=Mícheál Ó | title=Metric spaces | url=http://books.google.de/books?id=aP37I4QWFRcC | publisher=[[Springer-Verlag]] | location=Berlin, New York | series=Springer undergraduate mathematics series | isbn=978-1-84628-369-7 | year=2006}}, section 9.4</ref>
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| Any such ''K'' is referred to as '''a Lipschitz constant''' for the function ''f''. The smallest constant is sometimes called '''the (best) Lipschitz constant'''; however in most cases the latter notion is less relevant. If ''K'' = 1 the function is called a '''[[short map]]''', and if 0 ≤ ''K'' < 1 the function is called a '''[[contraction mapping|contraction]]'''.
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| The inequality is (trivially) satisfied if ''x''<sub>1</sub> = ''x''<sub>2</sub>. Otherwise, one can equivalently define a function to be Lipschitz continuous [[if and only if]] there exists a constant ''K'' ≥ 0 such that, for all ''x''<sub>1</sub> ≠ ''x''<sub>2</sub>,
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| :<math>\frac{d_Y(f(x_1),f(x_2))}{d_X(x_1,x_2)}\le K.</math>
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| For real-valued functions of several real variables, this holds if and only if the absolute value of the slopes of all secant lines are bounded by ''K''. The set of lines of slope ''K'' passing through a point on the graph of the function forms a circular cone, and a function is Lipschitz if and only if the graph of the function everywhere lies completely outside of this cone (see figure).
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| A function is called '''locally Lipschitz continuous''' if for every ''x'' in ''X'' there exists a [[neighborhood (mathematics)|neighborhood]] ''U'' of ''x'' such that ''f'' restricted to ''U'' is Lipschitz continuous. Equivalently, if ''X'' is a [[locally compact]] metric space, then ''f'' is locally Lipschitz if and only if it is Lipschitz continuous on every compact subset of ''X''. In spaces that are not locally compact, this is a necessary but not a sufficient condition.
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| More generally, a function ''f'' defined on ''X'' is said to be '''Hölder continuous''' or to satisfy a '''[[Hölder condition]]''' of order α > 0 on ''X'' if there exists a constant ''M'' > 0 such that
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| :<math>d_Y(f(x), f(y)) \leq M d_X(x, y)^{\alpha}</math>
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| for all ''x'' and ''y'' in ''X''. Sometimes a Hölder condition of order α is also called a '''uniform Lipschitz condition of order''' α > 0.
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| If there exists a ''K'' ≥ 1 with
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| :<math>\frac{1}{K}d_X(x_1,x_2) \le d_Y(f(x_1), f(x_2)) \le K d_X(x_1, x_2)</math>
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| then ''f'' is called '''bilipschitz''' (also written '''bi-Lipschitz'''). A bilipschitz mapping is [[injective function|injective]], and is in fact a [[homeomorphism]] onto its image. A bilipschitz function is the same thing as an injective Lipschitz function whose [[inverse function]] is also Lipschitz. Surjective bilipschitz functions are exactly the isomorphisms of metric spaces.
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| ==Examples==
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| ;Lipschitz continuous functions
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| * The function ''f''(''x'') = {{radic|''x''<sup>2</sup> + 5}} defined for all real numbers is Lipschitz continuous with the Lipschitz constant ''K'' = 1, because it is everywhere [[differentiable]] and the absolute value of the derivative is bounded above by 1.
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| * Likewise, the [[sine]] function is Lipschitz continuous because its derivative, the cosine function, is bounded above by 1 in absolute value.
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| * The function ''f''(''x'') = |''x''| defined on the reals is Lipschitz continuous with the Lipschitz constant equal to 1, by the [[reverse triangle inequality]]. This is an example of a Lipschitz continuous function that is not differentiable. More generally, a [[norm (mathematics)|norm]] on a vector space is Lipschitz continuous with respect to the associated metric, with the Lipschitz constant equal to 1.
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| ;Continuous functions that are not (globally) Lipschitz continuous:
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| * The function ''f''(''x'') = {{radic|''x''}} defined on [0, 1] is ''not'' Lipschitz continuous. This function becomes infinitely steep as ''x'' approaches 0 since its derivative becomes infinite. However, it is uniformly continuous<ref>{{Citation | last1=Robbin | first1=Joel W. | title=Continuity and Uniform Continuity | url=http://www.math.wisc.edu/~robbin/521dir/cont.pdf}}</ref> as well as [[Hölder continuity|Hölder continuous]] of class ''C''<sup>0, α</sup> for α ≤ 1/2.
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| ;Differentiable functions that are not (globally) Lipschitz continuous:
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| * The function ''f''(''x'') = ''x''<sup>3/2</sup>sin(1/''x'') where ''x'' ≠ 0 and ''f''(0) = 0, restricted on [0, 1], gives an example of a function that is differentiable on a compact set while not locally Lipschitz because its derivative function is not bounded. See also the first property below.
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| ;Analytic functions that are not (globally) Lipschitz continuous:
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| * The [[exponential function]] becomes arbitrarily steep as ''x'' → ∞, and therefore is ''not'' globally Lipschitz continuous, despite being an [[analytic function]].
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| * The function ''f''(''x'') = ''x''<sup>2</sup> with domain all real numbers is ''not'' Lipschitz continuous. This function becomes arbitrarily steep as ''x'' approaches infinity. It is however locally Lipschitz continuous.
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| ==Properties==
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| *An everywhere differentiable function ''g'' : '''R''' → '''R''' is Lipschitz continuous (with ''K'' = sup |''g''′(''x'')|) if and only if it has bounded [[first derivative]]; one direction follows from the [[mean value theorem]]. In particular, any continuously differentiable function is locally Lipschitz, as continuous functions are locally bounded so its gradient is locally bounded as well.
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| *A Lipschitz function ''g'' : '''R''' → '''R''' is [[absolutely continuous]] and therefore is differentiable [[almost everywhere]], that is, differentiable at every point outside a set of [[Lebesgue measure]] zero. Its derivative is [[essentially bounded]] in magnitude by the Lipschitz constant, and for ''a'' < ''b'', the difference ''g''(''b'') − ''g''(''a'') is equal to the integral of the derivative ''g''′ on the interval [''a'', ''b''].
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| **Conversely, if ''f'' : ''I'' → '''R''' is absolutely continuous and thus differentiable almost everywhere, and satisfies |''f′''(''x'')| ≤ ''K'' for almost all ''x'' in ''I'', then ''f'' is Lipschitz continuous with Lipschitz constant at most ''K''.
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| **More generally, [[Rademacher's theorem]] extends the differentiability result to Lipschitz mappings between Euclidean spaces: a Lipschitz map ''f'' : ''U'' → '''R'''<sup>''m''</sup>, where ''U'' is an open set in '''R'''<sup>''n''</sup>, is [[almost everywhere]] [[derivative|differentiable]]. Moreover, if ''K'' is the best Lipschitz constant of ''f'', then <math>\|Df(x)\|\le K</math> whenever the [[total derivative]] ''Df'' exists.
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| *For a differentiable Lipschitz map ''f'' : ''U'' → '''R'''<sup>''m''</sup> the inequality <math>\|Df\|_{\infty,U}\le K</math> holds for the best Lipschitz constant of f, and it turns out to be an equality if the domain U is convex.
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| *Suppose that {''f<sub>n</sub>''} is a sequence of Lipschitz continuous mappings between two metric spaces, and that all ''f<sub>n</sub>'' have Lipschitz constant bounded by some ''K''. If ''f<sub>n</sub>'' converges to a mapping ''f'' [[uniform convergence|uniformly]], then ''f'' is also Lipschitz, with Lipschitz constant bounded by the same ''K''. In particular, this implies that the set of real-valued functions on a compact metric space with a particular bound for the Lipschitz constant is a closed and convex subset of the [[Banach space]] of continuous functions. This result does not hold for sequences in which the functions may have ''unbounded'' Lipschitz constants, however. In fact, the space of all Lipschitz functions on a compact metric space is dense in the Banach space of continuous functions, an elementary consequence of the [[Stone–Weierstrass theorem]].
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| *Every Lipschitz continuous map is [[uniformly continuous]], and hence ''[[a fortiori]]'' [[continuous function|continuous]]. More generally, a set of functions with bounded Lipschitz constant forms an [[equicontinuous]] set. The [[Arzelà–Ascoli theorem]] implies that if {''f<sub>n</sub>''} is a [[uniformly bounded]] sequence of functions with bounded Lipschitz constant, then it has a convergent subsequence. By the result of the previous paragraph, the limit function is also Lipschitz, with the same bound for the Lipschitz constant. In particular the set of all real-valued Lipschitz functions on a compact metric space ''X'' having Lipschitz constant ≤ ''K''  is a [[Locally compact space|locally compact]] convex subset of the Banach space ''C''(''X'').
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| *For a family of Lipschitz continuous functions ''f''<sub>α</sub> with common constant, the function <math>\sup_\alpha f_\alpha</math> (and <math>\inf_\alpha f_\alpha</math>) is Lipschitz continuous as well, with the same Lipschitz constant, provided it assumes a finite value at least at a point.
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| *If ''U'' is a subset of the metric space ''M'' and ''f'' : ''U'' → '''R''' is a Lipschitz continuous function, there always exist Lipschitz continuous maps ''M'' → '''R''' which extend ''f'' and have the same Lipschitz constant as ''f'' (see also [[Kirszbraun theorem]]). An extension is provided by
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| ::<math>\tilde f(x):=\inf_{u\in U}\{ f(u)+k\, d(x,u)\},</math>
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| :where ''k'' is a Lipschitz constant for ''f'' on ''U''.
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| ==Lipschitz manifolds==
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| Let ''U'' and ''V'' be two open sets in '''R'''<sup>''n''</sup>. A function ''T'' : ''U'' → ''V'' is called '''bi-Lipschitz''' if it is a Lipschitz homeomorphism onto its image, and its inverse is also Lipschitz.
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| Using bi-Lipschitz mappings, it is possible to define a Lipschitz structure on a [[topological manifold]], since there is a [[pseudogroup]] structure on bi-Lipschitz homeomorphisms. This structure is intermediate between that of a [[piecewise-linear manifold]] and a [[smooth manifold]]. In fact a PL structure gives rise to a unique Lipschitz structure;<ref>SpringerLink: [http://eom.springer.de/T/t093230.htm Topology of manifolds]</ref> it can in that sense 'nearly' be smoothed.
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| ==One-sided Lipschitz== | |
| Let F(x) be an [[hemicontinuous|upper semi-continuous]] function of x, and that F(x) is a closed, convex set for all x. Then F is one-sided Lipschitz<ref>{{cite journal |last=Donchev |first=Tzanko |last2=Farkhi |first2=Elza |year=1998 |title=Stability and Euler Approximation of One-sided Lipschitz Differential Inclusions |journal=SIAM Journal on Control and Optimization |volume=36 |issue=2 |pages=780–796 |doi=10.1137/S0363012995293694 }}</ref> if
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| :<math>(x_1-x_2)^T(F(x_1)-F(x_2))\leq C\Vert x_1-x_2\Vert^2</math>
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| for some ''C'' for all ''x''<sub>1</sub> and ''x''<sub>2</sub>.
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| It is possible that the function F could have a very large Lipschitz constant but a moderately sized, or even negative, one-sided Lipschitz constant. For example the function
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| :<math>\begin{cases}
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| F:\mathbf{R}^2\to\mathbf{R},\\
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| F(x,y)=-50(y-cos(x))
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| \end{cases}</math>
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| has Lipschitz constant ''K'' = 50 and a one-sided Lipschitz constant ''C'' = 0.
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| ==See also==
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| *[[Dini continuity]]
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| *[[Modulus of continuity]]
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| ==References==
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| {{reflist}}
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| ==External links==
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| * [http://www.encyclopediaofmath.org/index.php/Lipschitz_condition Lipschitz condition] at [http://www.encyclopediaofmath.org/ Encyclopedia of Mathematics]
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| * [http://www.encyclopediaofmath.org/index.php/Lipschitz_constant Lipschitz constant] at [http://www.encyclopediaofmath.org/ Encyclopedia of Mathematics]
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| [[Category:Lipschitz maps| ]]
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| [[Category:Structures on manifolds]]
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