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]
Definition. Let ( X , d ) {\displaystyle (X,d)} be a metric space. Then a map T : X → X {\displaystyle T:X\to X} is called a contraction mapping on X if there exists q ∈ [ 0 , 1 ) {\displaystyle q\in [0,1)} such that
for all x , y ∈ X . {\displaystyle x,y\in X.}
Banach fixed-point theorem. Let ( X , d ) {\displaystyle (X,d)} be a non-empty complete metric space with a contraction mapping T : X → X . {\displaystyle T:X\to X.} Then T admits a unique fixed-point x ∗ {\displaystyle x^{*}} in X (i.e. T ( x ∗ ) = x ∗ {\displaystyle T(x^{*})=x^{*}} ). Furthermore, x ∗ {\displaystyle x^{*}} can be found as follows: start with an arbitrary element x 0 ∈ X {\displaystyle x_{0}\in X} and define a sequence ( x n ) n ∈ N {\displaystyle (x_{n})_{n\in \mathbb {N} }} by x n = T ( x n − 1 ) {\displaystyle x_{n}=T(x_{n-1})} for n ≥ 1. {\displaystyle n\geq 1.} Then lim n → ∞ x n = x ∗ {\displaystyle \lim _{n\to \infty }x_{n}=x^{*}} .
Remark 1. The following inequalities are equivalent and describe the speed of convergence:
Any such value of q is called a Lipschitz constant for T {\displaystyle T} , and the smallest one is sometimes called "the best Lipschitz constant" of T {\displaystyle T} .
Remark 2. d ( T ( x ) , T ( y ) ) < d ( x , y ) {\displaystyle d(T(x),T(y))<d(x,y)} for all x ≠ y {\displaystyle x\neq y} 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 X {\displaystyle X} is compact, then this weaker assumption does imply the existence and uniqueness of a fixed point, that can be easily found as a minimizer of d ( x , T ( x ) ) {\displaystyle d(x,T(x))} , indeed, a minimizer exists by compactness, and has to be a fixed point of T . {\displaystyle T.} It then easily follows that the fixed point is the limit of any sequence of iterations of T . {\displaystyle T.}
Remark 3. When using the theorem in practice, the most difficult part is typically to define X {\displaystyle X} properly so that T ( X ) ⊆ X . {\displaystyle T(X)\subseteq X.}
Let x 0 ∈ X {\displaystyle x_{0}\in X} be arbitrary and define a sequence ( x n ) n ∈ N {\displaystyle (x_{n})_{n\in \mathbb {N} }} by setting x n = T ( x n − 1 ) {\displaystyle x_{n}=T(x_{n-1})} . We first note that for all n ∈ N , {\displaystyle n\in \mathbb {N} ,} we have the inequality
This follows by induction on n {\displaystyle n} , using the fact that T {\displaystyle T} is a contraction mapping. Then we can show that ( x n ) n ∈ N {\displaystyle (x_{n})_{n\in \mathbb {N} }} is a Cauchy sequence. In particular, let m , n ∈ N {\displaystyle m,n\in \mathbb {N} } such that m > n {\displaystyle m>n} :
Let ε > 0 {\displaystyle \varepsilon >0} be arbitrary. Since q ∈ [ 0 , 1 ) {\displaystyle q\in [0,1)} , we can find a large N ∈ N {\displaystyle N\in \mathbb {N} } so that
Therefore, by choosing m {\displaystyle m} and n {\displaystyle n} greater than N {\displaystyle N} we may write:
This proves that the sequence ( x n ) n ∈ N {\displaystyle (x_{n})_{n\in \mathbb {N} }} is Cauchy. By completeness of ( X , d ) {\displaystyle (X,d)} , the sequence has a limit x ∗ ∈ X . {\displaystyle x^{*}\in X.} Furthermore, x ∗ {\displaystyle x^{*}} must be a fixed point of T {\displaystyle T} :
As a contraction mapping, T {\displaystyle T} is continuous, so bringing the limit inside T {\displaystyle T} was justified. Lastly, T {\displaystyle T} cannot have more than one fixed point in ( X , d ) {\displaystyle (X,d)} , since any pair of distinct fixed points p 1 {\displaystyle p_{1}} and p 2 {\displaystyle p_{2}} would contradict the contraction of T {\displaystyle T} :
Several converses of the Banach contraction principle exist. The following is due to Czesław Bessaga, from 1959:
Let f : X → X be a map of an abstract set such that each iterate fn has a unique fixed point. Let q ∈ ( 0 , 1 ) , {\displaystyle q\in (0,1),} then there exists a complete metric on X such that f is contractive, and q is the contraction constant.
Indeed, very weak assumptions suffice to obtain such a kind of converse. For example if f : X → X {\displaystyle f:X\to X} is a map on a T1 topological space with a unique fixed point a, such that for each x ∈ X {\displaystyle x\in X} we have fn(x) → a, then there already exists a metric on X with respect to which f satisfies the conditions of the Banach contraction principle with contraction constant 1/2.[8] In this case the metric is in fact an ultrametric.
There are a number of generalizations (some of which are immediate corollaries).[9]
Let T : X → X be a map on a complete non-empty metric space. Then, for example, some generalizations of the Banach fixed-point theorem are:
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 T 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 T {\displaystyle T} satisfying d ( T ( x ) , T ( y ) ) < d ( x , y ) {\displaystyle d(T(x),T(y))<d(x,y)} for all distinct x , y {\displaystyle x,y} , has a unique fixed point. The proof is simpler than the Banach theorem, because the function d ( T ( x ) , x ) {\displaystyle d(T(x),x)} 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]
An application of the Banach fixed-point theorem and fixed-point iteration can be used to quickly obtain an approximation of π with high accuracy. Consider the function f ( x ) = sin ( x ) + x {\displaystyle f(x)=\sin(x)+x} . It can be verified that π is a fixed point of f, and that f maps the interval [ 3 π / 4 , 5 π / 4 ] {\displaystyle \left[3\pi /4,5\pi /4\right]} to itself. Moreover, f ′ ( x ) = 1 + cos ( x ) {\displaystyle f'(x)=1+\cos(x)} , and it can be verified that
on this interval. Therefore, by an application of the mean value theorem, f has a Lipschitz constant less than 1 (namely 1 − 1 / 2 {\displaystyle 1-1/{\sqrt {2}}} ). Applying the Banach fixed-point theorem shows that the fixed point π is the unique fixed point on the interval, allowing for fixed-point iteration to be used.
For example, the value 3 may be chosen to start the fixed-point iteration, as 3 π / 4 ≤ 3 ≤ 5 π / 4 {\displaystyle 3\pi /4\leq 3\leq 5\pi /4} . The Banach fixed-point theorem may be used to conclude that
Applying f to 3 only three times already yields an expansion of π accurate to 33 digits:
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