Contraction, integral, maximum norm

In summary, Julien found that the function ƒ is a contraction with respect to the norm || ⋅ ||∞ and that the function ƒ is a fixed point of ƒ.
  • #1
JulienB
408
12

Homework Statement



Hi everybody! Here is another problem about contraction and Banach fixed-point theorem that I don't get:

The function ƒ: C([0,½]) → C([0,½]) is defined by:
[tex]
[f(x)](t) := 1 + \int_{0}^{t} x(s) ds ∀ t∈[0,\frac{1}{2}].
[/tex]

Is ƒ a contraction with respect to the norm || ⋅ ||? If yes, which function is the fixed point of ƒ?

Homework Equations



Contraction mapping theorem, Banach fixed-point theorem

The Attempt at a Solution



Well I could not really get anywhere, because I don't understand really the definition of the function. Here is what I would do anyway:

[tex]
|| [f(x)](t) - [f(y)](t) ||_{\infty} = \mbox{max } | 1 + \int_{0}^{t} x(s) ds - 1 - \int_{0}^{t} y(s) ds | \\
= \mbox{max } | \int_{0}^{t} x(s) - y(s) ds |
[/tex]

Then I have no idea how to integrate that since x is a function of s... What is the primitive of x(s)? Also not sure if I did the right thing in the first place as well! Some help would be very appreciated. :)

Thank you in advance for your answers.Julien.
 
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  • #2
JulienB said:

Homework Statement



Hi everybody! Here is another problem about contraction and Banach fixed-point theorem that I don't get:

The function ƒ: C([0,½]) → C([0,½]) is defined by:
[tex]
[f(x)](t) := 1 + \int_{0}^{t} x(s) ds ∀ t∈[0,\frac{1}{2}].
[/tex]

Is ƒ a contraction with respect to the norm || ⋅ ||? If yes, which function is the fixed point of ƒ?

Homework Equations



Contraction mapping theorem, Banach fixed-point theorem

The Attempt at a Solution



Well I could not really get anywhere, because I don't understand really the definition of the function. Here is what I would do anyway:

[tex]
|| [f(x)](t) - [f(y)](t) ||_{\infty} = \mbox{max } | 1 + \int_{0}^{t} x(s) ds - 1 - \int_{0}^{t} y(s) ds | \\
= \mbox{max } | \int_{0}^{t} x(s) - y(s) ds |
[/tex]

Then I have no idea how to integrate that since x is a function of s... What is the primitive of x(s)? Also not sure if I did the right thing in the first place as well! Some help would be very appreciated. :)

Thank you in advance for your answers.Julien.
Looks OK so far. Do some overestimating. How big can that integral be?
 
  • #3
LCKurtz said:
Looks OK so far. Do some overestimating. How big can that integral be?

@LCKurtz Hi and thanks for your answer. I have no idea, really. How should I do some estimation of this integral?Julien.
 
  • #4
Well, you know you can't actually perform the integration. But remember from calculus$$
\left | \int_a^b f(x)~dx \right | \le \int_a^b |f(x)|~dx$$and other properties of integration. And that integrand looks like it might be useful calculating ##\| \cdot \|_\infty##.
 
  • #5
@LCKurtz Thank you again for your answer. So I would have:

[tex]
|| [f(x)](t) - [f(y)](t) ||_{\infty} ≤ max \cdot \int_{0}^{t} | x(s) - y(s) | ds
[/tex]

and

[tex]
|| x - y ||_{\infty} = max | x(t) - y(t) |
[/tex]

Right? Mm I still don't see how to compare them, the only thing I know is that t is between 0 and 1 and ƒ is continuous between 0 and 1. I'm also not sure about my || x - y ||. Shouldn't it be || x(t) - y(t) || or something?

Maybe I just don't know the inequalities of calculus well enough, I'm going to take a close look at them during the next days.Julien.
 
  • #6
JulienB said:
@LCKurtz Thank you again for your answer. So I would have:

[tex]
|| [f(x)](t) - [f(y)](t) ||_{\infty} ≤ max \cdot \int_{0}^{t} | x(s) - y(s) | ds
[/tex]

and

[tex]
|| x(s) - y(s) ||_{\infty} = max | x(t) - y(t) |
[/tex]

Right? Mm I still don't see how to compare them, the only thing I know is that t is between 0 and 1 and ƒ is continuous between 0 and 1. Maybe I just don't know the inequalities of calculus well enough, I'm going to take a close look at them during the next days.Julien.

You know more about ##t## than it is in ##[0,1]##, and it matters.
 
  • #7
@LCKurtz Yes indeed it is between 0 and ½. Is that what you meant?

PS: I edited my last post while you were writing I believe, sorry for that.
 
  • #8
Yes. Now you are close. You just need to continue a couple more inequalities to get your overestimate. It might be easier to see you way through these inequalities if you start with$$
| [f(x)](t) - [f(y)](t)| = | 1 + \int_{0}^{t} x(s) ds - 1 - \int_{0}^{t} y(s) ds |
= | \int_{0}^{t} x(s) - y(s) ds |$$and don't worry about taking the max until you are done overestimating.
 
Last edited:
  • #9
@LCKurtz What about that:

[tex]
|| [f(x)](t) - [f(y)](t) ||_{\infty} ≤ max \int_{0}^{t} | x(s) - y(s) | ds ≤ (t - 0) \cdot max |x(s) - y(s)| \\
[/tex]

Since t is between 0 and ½, ƒ is a contraction. The inequality comes from: if ƒ is bounded on [0,t] and integrable then | ƒ | is integrable and:

[tex]
\frac{1}{t - 0} \int_{0}^{t} | f(x) | dx ≤ max | f(x) |
[/tex]

Is that a valid proof? Thx a lot for your help.Julien.
 
  • #10
LCKurtz said:
Yes. Now you are close. You just need to continue a couple more inequalities to get your overestimate.
JulienB said:
@LCKurtz What about that:

[tex]
|| [f(x)](t) - [f(y)](t) ||_{\infty} ≤ max \int_{0}^{t} | x(s) - y(s) | ds ≤ (t - 0) \cdot max |x(s) - y(s)| \\
[/tex]

Since t is between 0 and ½, ƒ is a contraction. The inequality comes from: if ƒ is bounded on [0,t] and integrable then | ƒ | is integrable and:

[tex]
\frac{1}{t - 0} \int_{0}^{t} | f(x) | dx ≤ max | f(x) |
[/tex]

Is that a valid proof? Thx a lot for your help.Julien.
I think that is a bit sketchy, especially with ##t##'s in your answer. I had edited my previous post while you posted this. You might want to look at my previous post again.
 
  • #11
@LCKurtz Okay I'm not sure that's exactly what you had in mind but I give it another go:

[tex]
| [f(x)](t) - [f(y)](t) | = | 1 + \int_{0}^{t} x(s) ds - 1 - \int_{0}^{t} y(s) ds | = | \int_{0}^{t} | x(s) - y(s) ds | \\
≤ \int_{0}^{t} | x(s) - y(s) | ds \\
≤ \int_{0}^{\frac{1}{2}} | x(s) - y(s) | ds \\
≤ \frac{1}{2} \cdot max | x(s) - y(s) | \\
\implies || [f(x)](t) - [f(y)](t) ||_{\infty} ≤ \frac{1}{2} \cdot || x(s) - y(s) ||_{\infty} \\
\implies \mbox{f is a contraction}
[/tex]

Very similar to what I've done last post though..Julien.
 
  • #12
Yes, it is similar, but much clearer, leaving no doubt each step is correct. Good. I have to leave for a few hours now. When I return I will check and see how you are doing in finding the fixed point.
 
  • #13
@LCKurtz Thanks a lot for all this help, I appreciate it. I might search for the fixed point tomorrow as it is close to midnight here in Germany :)Julien.
 
  • #14
Okay i couldn't wait so I gave it a go, but then I get an integral equation, which is something I have never done before:

[tex]
1 + \int_{0}^{t} x(s) ds = x(t)
[/tex]

The only thing I got out of it is:

[tex] x(0) = 1 [/tex]

That's not much I know :D I'll sleep over it and go further tomorrow.Julien.
 
  • #15
Could it be that the fixed point function is et? I don't really know how to find it, but it seems to work:

[tex]
1 + \int_{0}^{t} e^s ds = 1 + e^t - e^0 = e^t
[/tex]

Maybe I've misunderstood how to find the fixed point though, I'm not really sure.Julien.
 
  • #16
JulienB said:
Okay i couldn't wait so I gave it a go, but then I get an integral equation, which is something I have never done before:

[tex]
1 + \int_{0}^{t} x(s) ds = x(t)
[/tex]

The only thing I got out of it is:

[tex] x(0) = 1 [/tex]

That's not much I know :D I'll sleep over it and go further tomorrow.Julien.

JulienB said:
Could it be that the fixed point function is et? I don't really know how to find it, but it seems to work:

[tex]
1 + \int_{0}^{t} e^s ds = 1 + e^t - e^0 = e^t
[/tex]

Maybe I've misunderstood how to find the fixed point though, I'm not really sure.Julien.

Yes, you have found the fixed point by inspection, but your equation in post #14$$
x(t)=1 + \int_{0}^{t} x(s) ds$$will lead you directly to it. Try differentiating both sides with respect to ##t## to change it from an integral equation to a differential equation and see if you can get it from there.
 
  • Like
Likes JulienB
  • #17
[tex]
1 + \int_{0}^{t} x(s) ds = x(t) \\
\frac{d}{dt} (1 + \int_{0}^{t} x(s) ds) = \frac{d}{dt} (x(t)) \\
0 + \frac{d}{dt} \int_{0}^{t} x(s) ds = \dot{x}(t) \\
\mbox{According to the fundamental theorem of calculus: } \\
x(t) = \dot{x}(t) \\
\implies x_*(t) = e^t
[/tex]

Pretty neat! Thx a lot @LCKurtz, I've learned a lot through this post! Note that x* is the notation my teacher uses for fixed point.

Julien.
 
  • #18
You're welcome. One tiny oversight, you would get ##x_*(t) = Ce^t##, but as you observed earlier, ##x_*(0) = 1##. You need that.
 
  • #19
@LCKurtz Thanks a lot, that makes sense!
 

What is a contraction?

A contraction is a mathematical function that maps a metric space to itself, where the distance between two points is always reduced. In other words, it "contracts" the space. In order for a function to be a contraction, the distance between the images of two points must always be less than the distance between the points themselves.

What is an integral?

An integral is a mathematical operation that represents the area under a curve on a graph. It is used to calculate the total value of a function over a given interval. Integrals are a fundamental concept in calculus and are used in many areas of mathematics and science.

What is the maximum norm?

The maximum norm, also known as the "supremum norm," is a mathematical concept that measures the size of a function or vector. It is defined as the maximum absolute value of the function or vector over a given interval. In other words, it measures the largest value that a function or vector can take on within a given range.

What is the purpose of studying contraction, integral, and maximum norm?

These concepts are important in many areas of mathematics and science. Contraction mappings are used to prove the existence and uniqueness of solutions to differential equations. Integrals are used in calculus and physics to calculate areas, volumes, and other physical quantities. Maximum norm is useful for finding the maximum error in numerical methods and for analyzing the convergence of sequences and series.

What are some applications of contraction, integral, and maximum norm?

Contraction mappings are used in computer science for data compression and in economics for studying market dynamics. Integrals are used in engineering for calculating forces and moments, and in statistics for calculating probabilities. Maximum norm is used in optimization to find the maximum or minimum of a function, and in control theory for analyzing stability of systems.

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