Problem 6
Question
a) Find an example of a contraction \(f: X \rightarrow X\) of a non-complete metric space \(X\) with no fixed point. b) Find a 1-Lipschitz map \(f: X \rightarrow X\) of a complete metric space \(X\) with no fixed point.
Step-by-Step Solution
Verified Answer
a) A contraction on \( (0, 1) \) with \( f(x) = \frac{x}{2} \); b) a 1-Lipschitz map on \( \mathbb{R} \) with \( f(x) = x + 1 \).
1Step 1: Understanding Contraction in Non-Complete Metric Space
A contraction mapping is a function where there exists a constant \(0 \leq c < 1\) such that for all points \(x, y\) in the space \(X\), \(d(f(x), f(y)) \leq c \cdot d(x, y)\). However, a contraction on a non-complete metric space might not have a fixed point. The goal is to find such an example.
2Step 2: Example of Contraction without Fixed Point
Consider the metric space \(X = (0, 1)\) with the usual metric \(d(x, y) = |x - y|\) and the function \(f(x) = \frac{x}{2}\). Since \(f(x) \leq \frac{1}{2}x\), \(f\) is a contraction with constant \(c = \frac{1}{2}\). However, a potential fixed point \(x = f(x)\) would satisfy \(x = \frac{x}{2}\), leading to \(x = 0\), which is not in \(X\). Thus, \(f\) has no fixed point.
3Step 3: Understanding 1-Lipschitz Map with No Fixed Point in Complete Space
A 1-Lipschitz map is a function \(f: X \rightarrow X\) where for all points \(x, y\) in \(X\), \(d(f(x), f(y)) \leq d(x, y)\). Lipschitz maps do not contract distances, and such a map might not have a fixed point in a complete space.
4Step 4: Example of 1-Lipschitz Map without Fixed Point
Consider the complete metric space \(X = (\mathbb{R}, d)\) where \(d(x, y) = |x - y|\), and the function \(f(x) = x + 1\). Here, \(f\) shifts each point by 1, maintaining distance \(d(f(x), f(y)) = |f(x) - f(y)| = |(x + 1) - (y + 1)| = |x - y|\). This function is 1-Lipschitz but has no fixed point, since \(x = f(x)\) implies \(x = x + 1\), which is a contradiction.
Key Concepts
Contraction MappingLipschitz MapFixed PointCompleteness
Contraction Mapping
A contraction mapping is a powerful concept in metric spaces. It is a special kind of function defined on a metric space such that it brings points closer together. More formally, it is a function \(f: X \rightarrow X\) for which there exists some constant \(0 \leq c < 1\) where for all points \(x, y\) in the metric space \(X\), the distance between \(f(x)\) and \(f(y)\) satisfies the inequality \[ d(f(x), f(y)) \leq c \cdot d(x, y) \].
However, in non-complete metric spaces, such as the open interval \((0, 1)\), a contraction mapping does not always result in a fixed point.
- The constant \(c\) is known as the contraction constant.
- A contraction mapping reduces distances by a factor of \(c\).
- It is typically associated with fixed points, which are points that map to themselves \((x = f(x))\).
However, in non-complete metric spaces, such as the open interval \((0, 1)\), a contraction mapping does not always result in a fixed point.
Lipschitz Map
A Lipschitz map is similar to a contraction but comes with its unique characteristics. A 1-Lipschitz map is a function \(f: X \rightarrow X\) such that for every pair of points \(x, y\) in a metric space, the distance between \(f(x)\) and \(f(y)\) is at most equal to the distance between \(x\) and \(y\). Formally, it satisfies\[ d(f(x), f(y)) \leq d(x, y) \].
- The map does not "expand" the space but doesn't necessarily "contract" it either.
- 1-Lipschitz maps preserve distances or make them shorter, but unlike contractions, they can be equal.
- Such maps are useful in applied mathematics due to their "non-expansive" property.
Fixed Point
A fixed point of a function \(f: X \rightarrow X\) is simply a point \(x\) such that \(f(x) = x\). It is a concept essential in many mathematical fields due to its foundational role in analysis and topology.
Here's why fixed points are so important:
Here's why fixed points are so important:
- They indicate an equilibrium state, where the function leaves the point unchanged.
- In applied scenarios, fixed points can represent stable states in models.
- Solvers and algorithms benefiting from this concept are more efficient in reaching solutions in optimization problems.
Completeness
Completeness is a property of a metric space that deals with the idea of limits and convergence. A metric space is complete if every Cauchy sequence of points within the space has a limit that also belongs to the space.
Understanding completeness is crucial for various mathematical theorems and results:
Understanding completeness is crucial for various mathematical theorems and results:
- In a complete metric space, every Cauchy sequence converges to a point within the space, ensuring no 'gaps'.
- This property is critical in proving the existence of fixed points for contraction mappings, as outlined by the Banach Fixed-Point Theorem.
- Completeness implies that analysis on such spaces can be done seamlessly, offering robustness and predictability.
Other exercises in this chapter
Problem 5
Suppose \(f: X \rightarrow Y\) is continuous for metric spaces \(\left(X, d_{X}\right)\) and \(\left(Y, d_{Y}\right) .\) Show that if \(X\) is connected, then \
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Suppose \((X, d)\) is a metric space and \(\varphi:[0, \infty) \rightarrow \mathbb{R}\) is an increasing function such that \(\varphi(t) \geq 0\) for all \(t\)
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Show that a compact set \(K\) is a complete metric space (using the subspace metric).
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If \((X, d)\) is a metric space where d is the discrete metric. Suppose \(\left\\{x_{n}\right\\}\) is a convergent sequence in \(X .\) Show that there exists \(
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