Maximum norm and Banach fixed-point theorem

In summary, the conversation discusses a math problem involving the Banach fixed-point theorem and the concept of contractive functions in relation to different norms. The attempt at a solution provides proofs for two out of three given functions being strictly contractive. For the remaining function, further analysis is needed. The idea of finding points where the inequality does not hold is suggested.
  • #1
JulienB
408
12

Homework Statement



Hi everybody! I have a math problem to solve, I'd like to check if I understand well the Banach fixed-point theorem in the case of Euclidean norm and how to deal with maximum norm.

Check if the following functions ƒ: ℝ2 → ℝ2 are strictly contractive in relation to the given norms:
[tex]\mbox{a) } || \cdot ||_2 , f(x_1,x_2) = \frac{1}{2} (sin x_1, cos x_2)
\\ \mbox{b) } || \cdot ||_2 , f(x_1,x_2) = \frac{1}{2} (x_1 + x_2, x_2)
\\ \mbox{c) } || \cdot ||_{\infty} , f(x_1,x_2) = \frac{1}{2} (x_1 + x_2, x_2)
[/tex]

(note: not sure about my translation, can you say "contractive" in english?)

Homework Equations



Banach fixed-point theorem, mean value theorem for a), definition of norms

The Attempt at a Solution



I found it was not so easy to prove that the functions were strictly contractive or not, but here is a go:

[tex] \mbox{a) } || \frac{1}{2} \binom{sin x_1}{cos x_2} - \frac{1}{2} \binom{sin y_1}{cos y_2} ||_2 = \frac{1}{2} || \binom{sin x_1 - sin y_1}{cos x_2 - cos y_2} ||_2 \\
= \frac{1}{2} \sqrt{(sin x_1 - sin y_1)^2 + (cos x_2 - cos y_2)^2} \\
= \frac {1}{2} \sqrt{cos^2(α) (x_1 - y_1)^2 + sin^2 (β) (x_2 - y_2)^2} ≤ \frac{1}{2} \sqrt{(x_1 - y_1)^2 - (x_2 - y_2)^2} = \frac{1}{2} || \binom{x_1 - y_1}{x_2 - y_2} ||_2 \\
\mbox{(note that I made use of the mean value theorem to show the inequality)} \\
c < 1 \implies f(x_1,x_2) \mbox{ is strictly contractive.}
[/tex]

Is that correct? Am I understanding the Banach fixed-point theorem correctly? Now start the problems:

[tex] \mbox{b) } || \frac{1}{2} \binom{x_1 + x_2}{x_2} - \frac{1}{2} \binom{y_1 + y_2}{y_2} ||_2 = \frac{1}{2} \sqrt{(x_1 + x_2 - y_1 - y_2)^2 + (x_2 - y_2)^2} \\
= \frac{1}{2} \sqrt{x_1^2 + 2x_1 x_2 + x_2^2 - 2x_1y_1 + 2x_1y_2 - 2 x_2y_1 + 2x_2y_2 + y_1^2 - 2y_1y_2 + y_2^2 + (x_2 - y_2)^2} \\
= \frac{1}{2} \sqrt{(x_1 - y_1)^2 + (x_2 - y_2)^2 + (x_2 + y_2)^2 + 2(x_1x_2 + x_1y_2 - x_2y_1 - y_1y_2)}
[/tex]

Ehem... It seems to me that it would require a c bigger than 1 to make the inequality of the Banach theorem work, therefore the function would not be strictly contractive. On another hand the ½ makes it hard to prove... Is my intuition correct? Any clue about how to prove it if so?

And for c) I don't have a clue really. According to the definition in my teacher's script:

[tex]
c \cdot || \binom{x_1 - y_1}{x_2 - y_2} ||_{\infty} = c \cdot max | \binom{x_1 - y_1}{x_2 - y_2} | \\
\mbox{and} \\
\frac{1}{2} || \binom{x_1 + x_2 - y_1 - y_2}{x_2 - y_2} ||_{\infty} = \frac{1}{2} \cdot max | \binom{x_1 + x_2 - y_1 - y_2}{x_2 - y_2} |
[/tex]

But what does that mean? It seems to me like those maximums are not existing! :wideeyed: Is that the case? If yes, what can I conclude? If no, I must have misunderstood how to determine the maximum of a function in ℝ2...or the definition of a maximum norm altogether!

Thank you in advance for your answers.Julien.
 
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  • #2
Nobody has an idea? :smile:
 
  • #3
JulienB said:

Homework Statement



Hi everybody! I have a math problem to solve, I'd like to check if I understand well the Banach fixed-point theorem in the case of Euclidean norm and how to deal with maximum norm.

Check if the following functions ƒ: ℝ2 → ℝ2 are strictly contractive in relation to the given norms:
[tex]\mbox{a) } || \cdot ||_2 , f(x_1,x_2) = \frac{1}{2} (sin x_1, cos x_2)
\\ \mbox{b) } || \cdot ||_2 , f(x_1,x_2) = \frac{1}{2} (x_1 + x_2, x_2)
\\ \mbox{c) } || \cdot ||_{\infty} , f(x_1,x_2) = \frac{1}{2} (x_1 + x_2, x_2)
[/tex]

(note: not sure about my translation, can you say "contractive" in english?)

Homework Equations



Banach fixed-point theorem, mean value theorem for a), definition of norms

The Attempt at a Solution



I found it was not so easy to prove that the functions were strictly contractive or not, but here is a go:

[tex] \mbox{a) } || \frac{1}{2} \binom{sin x_1}{cos x_2} - \frac{1}{2} \binom{sin y_1}{cos y_2} ||_2 = \frac{1}{2} || \binom{sin x_1 - sin y_1}{cos x_2 - cos y_2} ||_2 \\
= \frac{1}{2} \sqrt{(sin x_1 - sin y_1)^2 + (cos x_2 - cos y_2)^2} \\
= \frac {1}{2} \sqrt{cos^2(α) (x_1 - y_1)^2 + sin^2 (β) (x_2 - y_2)^2} ≤ \frac{1}{2} \sqrt{(x_1 - y_1)^2 - (x_2 - y_2)^2} = \frac{1}{2} || \binom{x_1 - y_1}{x_2 - y_2} ||_2 \\
\mbox{(note that I made use of the mean value theorem to show the inequality)} \\
c < 1 \implies f(x_1,x_2) \mbox{ is strictly contractive.}
[/tex]

Is that correct? Am I understanding the Banach fixed-point theorem correctly? Now start the problems:

That looks good. You have shown it is a contraction map. That is just a definition, regardless of the Banach fixed-point theorem.

[tex] \mbox{b) } || \frac{1}{2} \binom{x_1 + x_2}{x_2} - \frac{1}{2} \binom{y_1 + y_2}{y_2} ||_2 = \frac{1}{2} \sqrt{(x_1 + x_2 - y_1 - y_2)^2 + (x_2 - y_2)^2} \\
= \frac{1}{2} \sqrt{x_1^2 + 2x_1 x_2 + x_2^2 - 2x_1y_1 + 2x_1y_2 - 2 x_2y_1 + 2x_2y_2 + y_1^2 - 2y_1y_2 + y_2^2 + (x_2 - y_2)^2} \\
= \frac{1}{2} \sqrt{(x_1 - y_1)^2 + (x_2 - y_2)^2 + (x_2 + y_2)^2 + 2(x_1x_2 + x_1y_2 - x_2y_1 - y_1y_2)}
[/tex]

Ehem... It seems to me that it would require a c bigger than 1 to make the inequality of the Banach theorem work, therefore the function would not be strictly contractive. On another hand the ½ makes it hard to prove... Is my intuition correct? Any clue about how to prove it if so?

If you suspect it isn't true, find a couple of points ##X=(x_1,x_2)## and ##Y=(y_1,y_2)## where ##\|f(X) - f(Y)\| > \| X-Y\|##. With a little fiddling around, that shouldn't be difficult.

I will look at the third one if I have time.
 
  • #4
JulienB said:
And for c) I don't have a clue really. According to the definition in my teacher's script:

[tex]
c \cdot || \binom{x_1 - y_1}{x_2 - y_2} ||_{\infty} = c \cdot max | \binom{x_1 - y_1}{x_2 - y_2} | \\
\mbox{and} \\
\frac{1}{2} || \binom{x_1 + x_2 - y_1 - y_2}{x_2 - y_2} ||_{\infty} = \frac{1}{2} \cdot max | \binom{x_1 + x_2 - y_1 - y_2}{x_2 - y_2} |
[/tex]

But what does that mean? It seems to me like those maximums are not existing! :wideeyed: Is that the case? If yes, what can I conclude? If no, I must have misunderstood how to determine the maximum of a function in ℝ2...or the definition of a maximum norm altogether!
For c), since ##f## is linear, you can simplify it somewhat by looking at ##||f(x)||_\infty =\frac12 ||(x_1+x_2,x_2)||_\infty##. As @LCKurtz suggested for b), you can rather easily find values for ##(x_1,x_2)## that answer the question whether ##f## is a contraction or not.
 
  • #5
@LCKurtz @Samy_A Hi guys and thanks for your answers!

LCKurtz said:
If you suspect it isn't true, find a couple of points ##X=(x_1,x_2)## and ##Y=(y_1,y_2)## where ##\|f(X) - f(Y)\| > \| X-Y\|##. With a little fiddling around, that shouldn't be difficult.

Samy_A said:
As @LCKurtz suggested for b), you can rather easily find values for ##(x_1,x_2)## that answer the question whether ##f## is a contraction or not.

I've been trying to find values of x and y for which ∥f(X)−f(Y)∥>∥X−Y∥ but I couldn't! Could you? I tried to put the highest value for x1 and the smallest for y1 but the ½ makes that I always get smaller than ∥X−Y∥! I now think it is a contraction, but I must work harder to prove it (if I'm right). I'll get back to you tomorrow.

Samy_A said:
For c), since ##f## is linear, you can simplify it somewhat by looking at ##||f(x)||_\infty =\frac12 ||(x_1+x_2,x_2)||_\infty##.

I did that, and to my mind the maximum of |(x1 + x2 - y1 - y2, x2 - y2)| is |(∞,∞)|... Same thing for the maximum of |(x1 - y1, x2 - y2)|. That would be the case for example if x has an infinitely high value for both x1 and x2 while y = (0, 0), right?Thanks a lot for your help, I appreciate it.Julien.
 
  • #6
JulienB said:
@LCKurtz @Samy_A Hi guys and thanks for your answers!I've been trying to find values of x and y for which ∥f(X)−f(Y)∥>∥X−Y∥ but I couldn't! Could you? I tried to put the highest value for x1 and the smallest for y1 but the ½ makes that I always get smaller than ∥X−Y∥! I now think it is a contraction, but I must work harder to prove it (if I'm right). I'll get back to you tomorrow..
There may be a good reason why you can't find values of x and y for which ∥f(X)−f(Y)∥>∥X−Y∥
But, to prove ##f## is not a contraction, it is sufficient to find a ##x \neq (0,0)## such that ##∥f(x)∥_\infty=∥x∥_\infty##.
JulienB said:
I did that, and to my mind the maximum of |(x1 + x2 - y1 - y2, x2 - y2)| is |(∞,∞)|... Same thing for the maximum of |(x1 - y1, x2 - y2)|. That would be the case for example if x has an infinitely high value for both x1 and x2 while y = (0, 0), right?
Of course the maximum of the norms over the whole ##\mathbb R^2## is ##\infty##. But that is not what you have to check.
You have (for c)) to compare ##∥f(x)∥_\infty## with ##∥x∥_\infty##.
Let's take an example: ##x=(x_1,x_2)=(1,2)##.
Then ##∥x∥_\infty = \max(1,2)=2##, ##∥f(x)∥_\infty =\frac12\max(1+2,2)=\frac12 . 3=1.5##.
 
  • #7
Samy_A said:
But, to prove ##f## is not a contraction, it is sufficient to find a ##x \neq (0,0)## such that ##∥f(x)∥_\infty=∥x∥_\infty##.

Does that apply even when the norm specified for the problem is [tex]|| \cdot ||_2 ?[/tex]

Samy_A said:
Of course the maximum of the norms over the whole ##\mathbb R^2## is ##\infty##. But that is not what you have to check.
You have (for c)) to compare ##∥f(x)∥_\infty## with ##∥x∥_\infty##.
Let's take an example: ##x=(x_1,x_2)=(1,2)##.
Then ##∥x∥_\infty = \max(1,2)=2##, ##∥f(x)∥_\infty =\frac12\max(1+2,2)=\frac12 . 3=1.5##.

Aha that is already quite different from what I had in mind. I'm giving it a go now and I'll post again after that.Thanks for those precious explanations!Julien.
 
  • #8
[tex]
|| f(x) - f(y) ||_{\infty} = \frac{1}{2} \cdot max |(x_1 + x_2 - y_1 - y_2, x_2 - y_2)| = \frac{1}{2} \cdot |x_1 - y_1 + x_2 - y_2| \\

||x - y||_{\infty} = max \cdot |(x_1 - y_1, x_2 - y_2)| = \frac{1}{2} \cdot |x_1 - y_1 + x_2 - y_2| (\mbox{for } x_2 - y_2 = x_1 - y_1) \\
\implies c = 1 \implies \mbox{The function is not a contraction.} [/tex]
Is that correct then?Julien.
 
Last edited:
  • #9
JulienB said:
Does that apply even when the norm specified for the problem is [tex]|| \cdot ||_2 ?[/tex].
Yes.

By definition, a contraction mapping (as used in the Banach fixed-point theorem) ##T: X \to X##, where ##X## is a normed space, satisfies ##\forall x,y \in X: ||Tx-Ty|| \leq q||x-y||##, where ##q \in [0,1[##.
Notice that ##0\leq q<1##.
If ##T## is linear, this is really saying that ##||T||<1##.

JulienB said:
[tex]
|| f(x) - f(y) ||_{\infty} = \frac{1}{2} \cdot max |(x_1 + x_2 - y_1 - y_2, x_2 - y_2)| = \frac{1}{2} \cdot |x_1 - y_1 + x_2 - y_2| \\

||x - y||_{\infty} = max \cdot |(x_1 - y_1, x_2 - y_2)| = \frac{1}{2} \cdot |x_1 - y_1 + x_2 - y_2| (\mbox{for } x_2 - y_2 = x_1 - y_1) \\
\implies c = 1 \implies \mbox{The function is not a contraction.} [/tex]
Is that correct then?
It certainly shows that ##c \geq 1##, proving that the function is not a contraction.
It is correct that ##c=1##. That's why you couldn't find ##x,y## satisfying ##||f(x)-f(y)||_\infty>||x-y||_\infty##.
 
Last edited:
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  • #10
@Samy_A Great! Thx a lot! For b) it is a bit farfetched but I think I got it too:

[tex]
\frac{1}{2} \sqrt{|x_1 - y_1 + x_2 - y_2|^2 + |x_2 - y_2|^2} ≤ \frac{1}{2} \sqrt{|x_1 - y_1|^2 + 2|x_1 - y_1| \cdot |x_2 - y_2|^2 + 2|x_2 - y_2|^2} \\
≤ \frac{1}{2} \sqrt{2|x_1 - y_1|^2 + 3|x_2 - y_2|^2} \\
≤ \sqrt{\frac{3}{4} |x_1 - y_1|^2 + \frac{3}{4} |x_2 - y_2|^2} \\
= \frac{\sqrt{3}}{2} || \binom{x_1}{x_2} - \binom{y_1}{y_2} ||_2 \\
\implies \mbox{f is a contraction!}
[/tex]

At least I got a c smaller than 1! :DJulien.
 
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1. What is the maximum norm?

The maximum norm, also known as the sup norm or the infinity norm, is a measure of the size of a mathematical function or vector. It is defined as the maximum absolute value of the function or vector over its domain.

2. How is the maximum norm used in the Banach fixed-point theorem?

In the Banach fixed-point theorem, the maximum norm is used to define a complete metric space, which is necessary for the theorem to apply. The theorem states that if a function in this metric space is contractive, meaning it decreases the distance between points, then it must have a unique fixed point.

3. What does the Banach fixed-point theorem prove?

The Banach fixed-point theorem proves the existence and uniqueness of a fixed point for a contractive function in a complete metric space. This theorem is useful in many areas of mathematics, including functional analysis, differential equations, and optimization.

4. How is the Banach fixed-point theorem applied in real life?

The Banach fixed-point theorem has many applications in real life, including in economics, physics, and computer science. For example, it can be used to prove the existence of equilibrium solutions in economic models or to find solutions to differential equations.

5. Are there any limitations to the Banach fixed-point theorem?

Yes, there are some limitations to the Banach fixed-point theorem. It only applies to contractive functions in complete metric spaces, so it cannot be used for non-contractive functions or in incomplete metric spaces. Additionally, the fixed point may not be unique if the function is not strictly contractive.

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