Contraction mapping

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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 nonnegative 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, and , then 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 nonempty 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 mapping plays an important role in dynamic programming problems.[2][3]

Firmly non-expansive mapping[edit]

A non-expansive mapping with can be strengthened to a firmly non-expansive mapping in a Hilbert space H if the following holds for all x and y in H:


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.

Subcontraction map[edit]

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.[5]

See also[edit]


  1. ^ Shifrin, Theodore (2005). Multivariable Mathematics. Wiley. pp. 244–260. ISBN 0-471-52638-X. 
  2. ^ Denardo, Eric V. (1967). "Contraction Mappings in the Theory Underlying Dynamic Programming". SIAM Review. 9 (2): 165–177. doi:10.1137/1009030. 
  3. ^ Stokey, Nancy L.; Lucas, Robert E. (1989). Recursive Methods in Economic Dynamics. Cambridge: Harvard University Press. pp. 49–55. ISBN 0-674-75096-9. 
  4. ^ Combettes, Patrick L. (2004). "Solving monotone inclusions via compositions of nonexpansive averaged operators". Optimization. 53 (5–6): 475–504. doi:10.1080/02331930412331327157. 
  5. ^ Goldstein, A.A. (1967). Constructive real analysis. Harper’s Series in Modern Mathematics. New York-Evanston-London: Harper and Row. p. 17. Zbl 0189.49703. 

Further reading[edit]

  • Istratescu, Vasile I. (1981). Fixed Point Theory : An Introduction. Holland: D.Reidel. ISBN 90-277-1224-7.  provides an undergraduate level introduction.
  • Granas, Andrzej; Dugundji, James (2003). Fixed Point Theory. New York: Springer-Verlag. ISBN 0-387-00173-5. 
  • Kirk, William A.; Sims, Brailey (2001). Handbook of Metric Fixed Point Theory. London: Kluwer Academic. ISBN 0-7923-7073-2.