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In mathematics, the Banach fixed-point theorem (also known as the contraction mapping theorem or contractive mapping theorem or Banach–Caccioppoli theorem) is an important tool in the theory of metric spaces; it guarantees the existence and uniqueness of fixed points of certain self-maps of metric spaces and provides a constructive method to find those fixed points. It can be understood as an abstract formulation of Picard's method of successive approximations.[1] The theorem is named after Stefan Banach (1892–1945) who first stated it in 1922.[2][3]

Statement

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Definition. Let be a metric space with metric . Then a map is called a contraction mapping on if there exists a nonnegative constant such that

for all

Banach fixed-point theorem. Let be a non-empty complete metric space with a contraction mapping Then admits a unique fixed point , meaning . Furthermore, can be found as follows: start with an arbitrary element and define for Then .

Remark 1. The following inequalities are equivalent and describe the speed of convergence:

The value is called a Lipschitz constant for , and a minimal such is sometimes called "the best Lipschitz constant" of .

Remark 2. The condition for all is in general not enough to ensure the existence of a fixed point, as is shown by the map which lacks a fixed point. However, if is compact, then this weaker condition does imply the existence and uniqueness of a fixed point which can be easily found as a minimizer of : indeed, a minimizer exists by compactness, and must be a fixed point. It then easily follows that the fixed point is the limit of any sequence of iterations of .

Remark 3. When using the theorem in practice, the most difficult part is typically to define properly so that .

Proof

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Let be arbitrary and define a sequence by setting . We first note that for all we have the inequality

This follows by induction on , using the fact that is a contraction mapping. Then we can show that is a Cauchy sequence. In particular, let such that :

Let be arbitrary. Since , we can find a large so that

Therefore, by choosing and greater than we may write:

This proves that the sequence is Cauchy. By completeness of , the sequence has a limit Furthermore, must be a fixed point of :

As a contraction mapping, is continuous, so bringing the limit inside was justified. Lastly, cannot have more than one fixed point in , since any pair of distinct fixed points and would contradict the contraction of :

where the equality is due to being fixed points of , the first inequality is due to being a contraction mapping, and the last inequality is due to and as .

Applications

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  1. is an open subset of : precisely, for any in such that one has ;
  2. is a bi-Lipschitz homeomorphism;
precisely, is still of the form with a Lipschitz map of constant . A direct consequence of this result yields the proof of the inverse function theorem.

Converses

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Several converses of the Banach contraction principle exist. The following is due to Czesław Bessaga, from 1959:

Let be a map of an abstract set such that each iterate has a unique fixed point. Let , then there exists a complete metric on such that is contractive, and is the contraction constant.

Indeed, very weak assumptions suffice to obtain such a kind of converse. For example if is a map on a T1 topological space with a unique fixed point , such that for each we have , then there already exists a metric on with respect to which satisfies the conditions of the Banach contraction principle with contraction constant .[8] In this case the metric is in fact an ultrametric.

Generalizations

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There are a number of generalizations (some of which are immediate corollaries).[9]

Let be a map on a complete non-empty metric space. Then, for example, some generalizations of the Banach fixed-point theorem are:

  • Assume that some iterate of is a contraction. Then has a unique fixed point.
  • Assume that for each , there exist such that for all and , and that
Then has a unique fixed point.

In applications, the existence and uniqueness of a fixed point often can be shown directly with the standard Banach fixed point theorem, by a suitable choice of the metric that makes the map a contraction. Indeed, the above result by Bessaga strongly suggests to look for such a metric. See also the article on fixed point theorems in infinite-dimensional spaces for generalizations.

In a non-empty compact metric space, any function satisfying for all distinct , has a unique fixed point. The proof is simpler than the Banach theorem, because the function is continuous, and therefore assumes a minimum, which is easily shown to be zero.

A different class of generalizations arise from suitable generalizations of the notion of metric space, e.g. by weakening the defining axioms for the notion of metric.[10] Some of these have applications, e.g., in the theory of programming semantics in theoretical computer science.[11]

Example

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An application of the Banach fixed-point theorem and fixed-point iteration can be used to quickly obtain an approximation of with high accuracy. Consider the function . It can be verified that is a fixed point of , and that maps the interval to itself. Moreover, , and it can be verified that

on this interval. Therefore, by an application of the mean value theorem, has a Lipschitz constant less than (namely ). Applying the Banach fixed-point theorem shows that the fixed point is the unique fixed point on the interval, allowing for fixed-point iteration to be used.

For example, the value may be chosen to start the fixed-point iteration, as . The Banach fixed-point theorem may be used to conclude that

Applying to only thrice already yields an expansion of accurate up to digits:

See also

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Notes

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  1. ^ Kinderlehrer, David; Stampacchia, Guido (1980). "Variational Inequalities in RN". An Introduction to Variational Inequalities and Their Applications. New York: Academic Press. pp. 7–22. ISBN 0-12-407350-6.
  2. ^ Banach, Stefan (1922). "Sur les opérations dans les ensembles abstraits et leur application aux équations intégrales" (PDF). Fundamenta Mathematicae. 3: 133–181. doi:10.4064/fm-3-1-133-181. Archived (PDF) from the original on 2011-06-07.
  3. ^ Ciesielski, Krzysztof (2007). "On Stefan Banach and some of his results" (PDF). Banach J. Math. Anal. 1 (1): 1–10. doi:10.15352/bjma/1240321550. Archived (PDF) from the original on 2009-05-30.
  4. ^ Günther, Matthias (1989). "Zum Einbettungssatz von J. Nash" [On the embedding theorem of J. Nash]. Mathematische Nachrichten (in German). 144: 165–187. doi:10.1002/mana.19891440113. MR 1037168.
  5. ^ Lewis, Frank L.; Vrabie, Draguna; Syrmos, Vassilis L. (2012). "Reinforcement Learning and Optimal Adaptive Control". Optimal Control. New York: John Wiley & Sons. pp. 461–517 [p. 474]. ISBN 978-1-118-12272-3.
  6. ^ Long, Ngo Van; Soubeyran, Antoine (2000). "Existence and Uniqueness of Cournot Equilibrium: A Contraction Mapping Approach" (PDF). Economics Letters. 67 (3): 345–348. doi:10.1016/S0165-1765(00)00211-1. Archived (PDF) from the original on 2004-12-30.
  7. ^ Stokey, Nancy L.; Lucas, Robert E. Jr. (1989). Recursive Methods in Economic Dynamics. Cambridge: Harvard University Press. pp. 508–516. ISBN 0-674-75096-9.
  8. ^ Hitzler, Pascal; Seda, Anthony K. (2001). "A 'Converse' of the Banach Contraction Mapping Theorem". Journal of Electrical Engineering. 52 (10/s): 3–6.
  9. ^ Latif, Abdul (2014). "Banach Contraction Principle and its Generalizations". Topics in Fixed Point Theory. Springer. pp. 33–64. doi:10.1007/978-3-319-01586-6_2. ISBN 978-3-319-01585-9.
  10. ^ Hitzler, Pascal; Seda, Anthony (2010). Mathematical Aspects of Logic Programming Semantics. Chapman and Hall/CRC. ISBN 978-1-4398-2961-5.
  11. ^ Seda, Anthony K.; Hitzler, Pascal (2010). "Generalized Distance Functions in the Theory of Computation". The Computer Journal. 53 (4): 443–464. doi:10.1093/comjnl/bxm108.

References

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