Contraction mapping: Difference between revisions
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{{Short description|Function reducing distance between all points}} In [[mathematics]], a '''contraction mapping''', or '''contraction''' or '''contractor''', on a [[metric space]] (''M'', ''d'') is a [[Function (mathematics)|function]] ''f'' from ''M'' to itself, with the property that there is some [[real number]] <math>0 \leq k < 1</math> such that for all ''x'' and ''y'' in ''M'', | {{Short description|Function reducing distance between all points}} In [[mathematics]], a '''contraction mapping''', or '''contraction''' or '''contractor''', on a [[metric space]] (''M'', ''d'') is a [[Function (mathematics)|function]] ''f'' from ''M'' to itself, with the property that there is some [[real number]] <math>0 \leq k < 1</math> such that for all ''x'' and ''y'' in ''M'', | ||
<math display="block">d(f(x),f(y)) \leq k\,d(x,y).</math> | |||
The smallest such value of ''k'' is called the '''[[Lipschitz constant]]''' of ''f''. Contractive maps are sometimes called '''Lipschitzian maps'''. If the above condition is instead satisfied for | |||
The smallest such value of ''k'' is called the '''Lipschitz constant''' of ''f''. Contractive maps are sometimes called '''Lipschitzian maps'''. If the above condition is instead satisfied for | |||
''k'' ≤ 1, then the mapping is said to be a [[non-expansive map]]. | ''k'' ≤ 1, then the mapping is said to be a [[non-expansive map]]. | ||
More generally, the idea of a contractive mapping can be defined for maps between metric spaces. Thus, if (''M'', ''d'') and (''N'', ''d''') are two metric spaces, then <math>f:M \rightarrow N</math> is a contractive mapping if there is a constant <math>0 \leq k < 1</math> such that | More generally, the idea of a contractive mapping can be defined for maps between metric spaces. Thus, if (''M'', ''d'') and (''N'', ''d''') are two metric spaces, then <math>f:M \rightarrow N</math> is a contractive mapping if there is a constant <math>0 \leq k < 1</math> such that | ||
<math display="block">d'(f(x),f(y)) \leq k\,d(x,y)</math> | |||
for all ''x'' and ''y'' in ''M''. | for all ''x'' and ''y'' in ''M''. | ||
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==Firmly non-expansive mapping== | ==Firmly non-expansive mapping== | ||
A non-expansive mapping with <math>k=1</math> can be generalized to a '''firmly non-expansive mapping''' in a [[Hilbert space]] <math>\mathcal{H}</math> if the following holds for all ''x'' and ''y'' in <math>\mathcal{H}</math>: | A non-expansive mapping with <math>k=1</math> can be generalized to a '''firmly non-expansive mapping''' in a [[Hilbert space]] <math>\mathcal{H}</math> if the following holds for all ''x'' and ''y'' in <math>\mathcal{H}</math>: | ||
<math display="block">\|f(x)-f(y) \|^2 \leq \, \langle x-y, f(x) - f(y) \rangle,</math> | |||
where | where | ||
<math display="block">d(x,y) = \|x-y\|.</math> | |||
This is a special case of <math>\alpha</math> averaged nonexpansive operators with <math>\alpha = 1/2</math>.<ref>{{cite journal |title=Solving monotone inclusions via compositions of nonexpansive averaged operators |first=Patrick L. |last=Combettes |year=2004 |journal=[[Optimization (journal)|Optimization]] |volume=53 |issue=5–6 |pages=475–504 |doi=10.1080/02331930412331327157 |s2cid=219698493 }}</ref> A firmly non-expansive mapping is always non-expansive, via the [[Cauchy–Schwarz inequality]]. | This is a special case of <math>\alpha</math> averaged nonexpansive operators with <math>\alpha = 1/2</math>.<ref>{{cite journal |title=Solving monotone inclusions via compositions of nonexpansive averaged operators |first=Patrick L. |last=Combettes |year=2004 |journal=[[Optimization (journal)|Optimization]] |volume=53 |issue=5–6 |pages=475–504 |doi=10.1080/02331930412331327157 |s2cid=219698493 }}</ref> A firmly non-expansive mapping is always non-expansive, via the [[Cauchy–Schwarz inequality]]. | ||
The class of firmly non-expansive maps is closed under [[convex combination]]s, but not compositions.<ref name=":0">{{Cite book|title=Convex Analysis and Monotone Operator Theory in Hilbert Spaces|last=Bauschke|first=Heinz H.|publisher=Springer|year=2017|location=New York}}</ref> This class includes [[Proximal operator|proximal mappings]] of proper, convex, lower-semicontinuous functions, hence it also includes orthogonal [[Projection (mathematics)|projections]] onto non-empty closed [[convex set]]s. The class of firmly nonexpansive operators is equal to the set of resolvents of maximally [[Monotonic function#Monotonicity in functional analysis|monotone operators]].<ref>{{Cite journal|last=Combettes|first=Patrick L.|date=July 2018|title=Monotone operator theory in convex optimization|journal=Mathematical Programming|volume=B170|pages=177–206|arxiv=1802.02694|doi=10.1007/s10107-018-1303-3|bibcode=2018arXiv180202694C|s2cid=49409638}}</ref> Surprisingly, while iterating non-expansive maps has no guarantee to find a fixed point (e.g. multiplication by -1), firm non-expansiveness is sufficient to [[convergence proof techniques|guarantee global convergence]] to a fixed point, provided a fixed point exists. More precisely, if <math>\operatorname{Fix}f := \{x \in \mathcal{H} \ | \ f(x) = x\} \neq \varnothing</math> | The class of firmly non-expansive maps is closed under [[convex combination]]s, but not compositions.<ref name=":0">{{Cite book|title=Convex Analysis and Monotone Operator Theory in Hilbert Spaces|last=Bauschke|first=Heinz H.|publisher=Springer|year=2017|location=New York}}</ref> This class includes [[Proximal operator|proximal mappings]] of proper, convex, lower-semicontinuous functions, hence it also includes orthogonal [[Projection (mathematics)|projections]] onto non-empty closed [[convex set]]s. The class of firmly nonexpansive operators is equal to the set of resolvents of maximally [[Monotonic function#Monotonicity in functional analysis|monotone operators]].<ref>{{Cite journal|last=Combettes|first=Patrick L.|date=July 2018|title=Monotone operator theory in convex optimization|journal=Mathematical Programming|volume=B170|pages=177–206|arxiv=1802.02694|doi=10.1007/s10107-018-1303-3|bibcode=2018arXiv180202694C|s2cid=49409638}}</ref> Surprisingly, while iterating non-expansive maps has no guarantee to find a fixed point (e.g. multiplication by -1), firm non-expansiveness is sufficient to [[convergence proof techniques|guarantee global convergence]] to a fixed point, provided a fixed point exists. More precisely, if | ||
<math display="block">\operatorname{Fix}f := \{x \in \mathcal{H} \ | \ f(x) = x\} \neq \varnothing,</math> | |||
<math> (\forall n \in \mathbb{N} | then for any initial point <math>x_0 \in \mathcal{H}</math>, iterating | ||
<math display="block"> x_{n+1} = f(x_n), \quad \forall n \in \mathbb{N}</math> | |||
yields convergence to a fixed point <math> x_n \to z \in \operatorname{Fix} f</math>. This convergence might be [[Weak convergence (Hilbert space)|weak]] in an infinite-dimensional setting.<ref name=":0" /> | yields convergence to a fixed point <math> x_n \to z \in \operatorname{Fix} f</math>. This convergence might be [[Weak convergence (Hilbert space)|weak]] in an infinite-dimensional setting.<ref name=":0" /> | ||
==Subcontraction map== | ==Subcontraction map== | ||
A '''subcontraction map''' or '''subcontractor''' is a map ''f'' on a metric space (''M'', ''d'') such that | A '''subcontraction map''' or '''subcontractor''' is a map ''f'' on a metric space (''M'', ''d'') such that | ||
<math display="block"> d(f(x), f(y)) \leq d(x,y);</math> | |||
<math display="block">d(f(f(x)),f(x)) < d(f(x),x) \quad \text{unless} \quad x = f(x).</math> | |||
If the [[Image (mathematics)|image]] of a subcontractor ''f'' is [[Compact space|compact]], then ''f'' has a fixed point.<ref name=Gold17>{{cite book | last=Goldstein | first=A.A. | title=Constructive real analysis | zbl=0189.49703 | series=Harper's Series in Modern Mathematics | location=New York-Evanston-London | publisher=Harper and Row | year=1967 |page=17 }}</ref> | If the [[Image (mathematics)|image]] of a subcontractor ''f'' is [[Compact space|compact]], then ''f'' has a fixed point.<ref name=Gold17>{{cite book | last=Goldstein | first=A.A. | title=Constructive real analysis | zbl=0189.49703 | series=Harper's Series in Modern Mathematics | location=New York-Evanston-London | publisher=Harper and Row | year=1967 |page=17 }}</ref> | ||
Latest revision as of 07:42, 21 July 2025
Template:Short description In mathematics, a contraction mapping, or contraction or contractor, on a metric space (M, d) is a function f from M to itself, with the property that there is some real number such that for all x and y in M, The smallest such value of k is called the Lipschitz constant of f. Contractive maps are sometimes called Lipschitzian maps. If the above condition is instead satisfied for k ≤ 1, then the mapping is said to be a non-expansive map.
More generally, the idea of a contractive mapping can be defined for maps between metric spaces. Thus, if (M, d) and (N, d') are two metric spaces, then is a contractive mapping if there is a constant such that for all x and y in M.
Every contraction mapping is Lipschitz continuous and hence uniformly continuous (for a Lipschitz continuous function, the constant k is no longer necessarily less than 1).
A contraction mapping has at most one fixed point. Moreover, the Banach fixed-point theorem states that every contraction mapping on a non-empty complete metric space has a unique fixed point, and that for any x in M the iterated function sequence x, f (x), f (f (x)), f (f (f (x))), ... converges to the fixed point. This concept is very useful for iterated function systems where contraction mappings are often used. Banach's fixed-point theorem is also applied in proving the existence of solutions of ordinary differential equations, and is used in one proof of the inverse function theorem.[1]
Contraction mappings play an important role in dynamic programming problems.[2][3]
Firmly non-expansive mapping
A non-expansive mapping with can be generalized to a firmly non-expansive mapping in a Hilbert space if the following holds for all x and y in : where This is a special case of averaged nonexpansive operators with .[4] A firmly non-expansive mapping is always non-expansive, via the Cauchy–Schwarz inequality.
The class of firmly non-expansive maps is closed under convex combinations, but not compositions.[5] This class includes proximal mappings of proper, convex, lower-semicontinuous functions, hence it also includes orthogonal projections onto non-empty closed convex sets. The class of firmly nonexpansive operators is equal to the set of resolvents of maximally monotone operators.[6] Surprisingly, while iterating non-expansive maps has no guarantee to find a fixed point (e.g. multiplication by -1), firm non-expansiveness is sufficient to guarantee global convergence to a fixed point, provided a fixed point exists. More precisely, if then for any initial point , iterating yields convergence to a fixed point . This convergence might be weak in an infinite-dimensional setting.[5]
Subcontraction map
A subcontraction map or subcontractor is a map f on a metric space (M, d) such that If the image of a subcontractor f is compact, then f has a fixed point.[7]
Locally convex spaces
In a locally convex space (E, P) with topology given by a set P of seminorms, one can define for any p ∈ P a p-contraction as a map f such that there is some kp < 1 such that p(f(x) − f(y)) ≤ kp p(x − y). If f is a p-contraction for all p ∈ P and (E, P) is sequentially complete, then f has a fixed point, given as limit of any sequence xn+1 = f(xn), and if (E, P) is Hausdorff, then the fixed point is unique.[8]
See also
- Short map
- Contraction (operator theory)
- Transformation
- Comparametric equation
- Blackwell's contraction mapping theorem
- CLRg property
References
Further reading
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