Show that T is a contraction on a metric space

In summary, the problem involves showing that the mapping T from the metric space (R^{n}, d_{∞}) to itself is a contraction, given certain conditions on the matrix C. The key step is recognizing that the sum of every row of C is less than 1, and then using this to show that the distance between T(x) and T(y) is less than a constant multiple of the distance between x and y.
  • #1
phosgene
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1

Homework Statement



Consider the metric space [itex](R^{n}, d_{∞})[/itex], where if [itex]\underline{x}=(x_{1}, x_{2}, x_{3},...,x_{n})[/itex] and [itex]\underline{y}=(y_{1}, y_{2}, y_{3},...,y_{n})[/itex] we define

[itex]d_{∞}(\underline{x},\underline{y}) = max_{i=1,2,3...,n} |x_{i} - y_{i}|[/itex]

Assume that [itex](R^{n}, d_{∞})[/itex] is complete.

Let [itex]T: R^{n} → R^{n}[/itex] be the mapping given by [itex]T\underline{x}=C\underline{x} + \underline{b}[/itex]. If C has the following property

[itex]∑_{j}|C_{ij}| < 1[/itex], for [itex]i=1,2,3,...,n[/itex]

show that [itex]T: R^{n} → R^{n}[/itex] is a contraction on [itex](R^{n}, d_{∞})[/itex]


Homework Equations



[itex]∑_{j}|C_{ij}| < 1[/itex], for [itex]i=1,2,3,...,n[/itex]

Therefore the sum of every row of the matrix C is less than 1.

T is a contraction on [itex](R^{n}, d_{∞})[/itex] if
[itex]d_{∞}(T(\underline{x}),T(\underline{y}) )≤ Kd_{∞}(\underline{x}, \underline{y}), 0≤K<1[/itex]

The Attempt at a Solution



For d(T(y), T(x)) I get

[itex]max_{i=1,2,3,...,n} |C\underline{x} + \underline{b} - C\underline{y} - \underline{b}|[/itex]

[itex]=max_{i=1,2,3,...,n} |∑_{j} c_{ij}x{j} - c_{ij}y_{j}|[/itex]

The best that I can get from this is that [itex]∑_{j} c_{ij}x{j}[/itex] is less than the maximum value of x. But I don't think that's particularly useful and I'm not sure what else to do.
 
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  • #2
You have already said that "Therefore the sum of every row of the matrix C is less than 1." So [itex]\sum_j c_{ij}< 1[/itex]. What does that tell you about [itex]\sum_j c_{ij}x_j[/itex]?
 
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  • #3
Thanks for the reply, but I have the solution now. The key step was (for anyone else who might be having trouble with a question similar to this) to recognize that

[itex]|∑_{j} c_{ij}x_{j} - c_{ij}y_{j}| ≤ ∑_{j} |c_{ij}x_{j} - c_{ij}y_{j}|[/itex]

and then to note how [itex]|x_{j} - y_{j}| ≤ max_{i=1,2,3,...,n} |x_{i} - y_{i}|[/itex]

Then everything is straight forward from there.
 

1. What is a metric space?

A metric space is a mathematical concept that defines a set of objects along with a distance function, known as a metric, that measures the distance between any two objects in the set. This distance function must satisfy certain properties, such as being non-negative and symmetric.

2. What does it mean for T to be a contraction on a metric space?

A function T is a contraction on a metric space if there exists a constant k, such that for any two points x and y in the metric space, the distance between T(x) and T(y) is less than k times the distance between x and y. This means that the function T shrinks the distance between points in the metric space by a constant factor k.

3. How is a contraction different from a linear transformation?

A linear transformation preserves distances, meaning that the distance between any two points is the same before and after the transformation. On the other hand, a contraction reduces the distance between points, making them closer together. This is a key difference between the two concepts.

4. What is the importance of a contraction on a metric space?

Contraction mappings have important applications in various fields, such as physics, engineering, and computer science. They are particularly useful in proving the existence and uniqueness of solutions to differential equations, as well as in optimization and approximation algorithms.

5. How can you show that T is a contraction on a metric space?

To show that T is a contraction on a metric space, you can use the definition of a contraction and the properties of the metric space. Specifically, you would need to find a constant k and prove that for any two points x and y in the metric space, the distance between T(x) and T(y) is less than k times the distance between x and y. This can be done through various techniques, such as using inequalities and the properties of the metric space.

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