Mazur-Ulam theorem (bijective isometries are affine maps)

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In summary, The Mazur-Ulam theorem states that for any arbitrary normed spaces E and F, if a bijective isometry ##f:E\to F## is given, then ##f## is an affine map. The definition of an affine map is that for all ##t\in[0,1]## and all ##x,y\in E##, ##f(tx+(1-t)y)=tf(x)+(1-t)f(y)##. This implies that ##f-f(0)## is linear and there is a linear map ##L:E\to F## and a vector ##y\in F## such that ##f(x)=Lx+y## for all ##x\in E##. This is
  • #1
Fredrik
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I've been studying the proof of the Mazur-Ulam theorem in the pdf linked to at the end of this Wikipedia article. I'm struggling with some details in that pdf.

Theorem: Let E and F be arbitrary normed spaces. If ##f:E\to F## is a bijective isometry, then f is an affine map.

Some of the things I don't get:

1. Their definition of "affine map". How does ##f(tx+(1-t)y)=tf(x)+(1-t)f(y)## for all ##x,y\in X## and all ##t\in[0,1]## imply that f-f(0) is linear? I don't see how to deal with (f-f(0))(ax) where ##a\in\mathbb R## is arbitrary.

2. The claim that ##\psi## is an isometry. ##\psi:E\to E## is defined by ##\psi(x)=2z-x## for all ##x\in E##. This map sends an arbitrary point in E to the point that's "on the opposite side of z", i.e. the point y such that y=z+(z-x). They claim that ##\psi## is an isometry, but consider e.g. ##E=\mathbb R##, z=2, x=1. We have ##\psi(1)=2\cdot 2-1=3##, but ##\|\psi(1)\|=3\neq 1=\|1\|##.

3. If ##\psi## isn't an isometry, then I don't see a reason to think that the map the author denotes by g* should be an isometry either. It's defined by ##g^*=\psi\circ g^{-1}\circ\psi\circ g##, where g is a bijective isometry. The step ##\|g^*(z)-z\|\leq\lambda## relies on ##g^*## being an isometry.

4. All they're proving is that for all ##a,b\in E##, we have ##f\left(\frac{a+b}{2}\right)=\frac 1 2 f(a)+\frac 1 2 f(b)##. It's not obvious that this implies that f is affine.
 
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  • #2
Fredrik said:
1. Their definition of "affine map". How does ##f(tx+(1-t)y)=tf(x)+(1-t)f(y)## for all ##x,y\in X## and all ##t\in[0,1]## imply that f-f(0) is linear? I don't see how to deal with (f-f(0))(ax) where ##a\in\mathbb R## is arbitrary.

So the claim is that if ##f## is an affine map such that ##f(0)=0##, then ##f## is linear. First, take ##t\in [0,1]## arbitrary, then
[tex]f(tx) = f(tx + (1-t)0) = tf(x) + (1-t)f(0) = tf(x)[/tex]

Now it follows that
[tex]\frac{1}{2}f(x+y) = f(\frac{1}{2} x+ \frac{1}{2}y) = \frac{1}{2} f(x) + \frac{1}{2}f(y)[/tex]
so ##f(x+y) = f(x) + f(y)## and ##f## is additive.

Now take ##\lambda\geq 0## arbitrary. Then we can write ##\lambda = nt## for some positive integer ##n## and some ##t\in [0,1]##. Then
[tex]f(\lambda x) = f(ntx) = f(tx + ...+ tx) = f(tx) + ... + f(tx) = tf(x) + ... + tf(x) = ntf(x) = \lambda f(x)[/tex]

Now take ##\lambda<0##, then

[tex]0 = f(0) = f(\lambda x - \lambda x) = f(\lambda x) -\lambda f(x)[/tex]
Thus ##f(\lambda x) = \lambda f(x)## and ##f## is linear.

2. The claim that ##\psi## is an isometry. ##\psi:E\to E## is defined by ##\psi(x)=2z-x## for all ##x\in E##. This maps sends an arbitrary point in E to the point that's "on the opposite side of z", i.e. the point y such that y=z+(z-x). They claim that ##\psi## is an isometry, but consider e.g. ##E=\mathbb R##, z=2, x=1. We have ##\psi(1)=2\cdot 2-1=3##, but ##\|\psi(1)\|=3\neq 1=\|1\|##.

You are verifying the property ##\|\psi(x)\| = \|x\|##, but this is not the property that you want to verify. The property is ##\|\psi(x) - \psi(y)\| =\|x-y\|##. This is the one that holds for ##\psi##. The two properties are equivalent, but only for linear maps.

4. All they're proving is that for all ##a,b\in E##, we have ##f\left(\frac{a+b}{2}\right)=\frac 1 2 f(a)+\frac 1 2 f(b)##. It's not obvious that this implies that f is affine.

So, it suffices to show that if ##f\left(\frac{a+b}{2}\right)=\frac 1 2 f(a)+\frac 1 2 f(b)## and ##f(0) = 0##, then ##f## is linear.

Note that
[tex]f\left(\frac{a+0}{2}\right)=\frac 1 2 f(a)+\frac 1 2 f(0)[/tex]
implies that ##f(a/2) = f(a)/2##. And as above, we can prove ##f(a+b) = f(a) + f(b)## now.
By induction, it follows easily that
[tex]f\left(\frac{1}{2^n}x\right)=\frac{1}{2^n} f(x)[/tex]
Now if ##t= c/2^n## for some ##c\in \{0,...,2^n\}## then it follows easily (since the map is additive) that
[tex]f(tx) = tf(x)[/tex]

Now, fix ##x## and define ##g:[0,1]\rightarrow E:t\rightarrow f(tx) - tf(x)##. This function is continuous and vanishes on the dense set ##\{c/2^n~\vert~c\in \{0,...,2^n\}\}##. So ##g## vanishes everywhere. Thus ##f(tx) = tf(x)## for all ##t\in [0,1]##. As above, we can now prove that ##f## is linear.
 
  • #3
Awesome reply. :approve: I don't know how you manage to explain everything I'm stuck on so fast, but I'm glad that you do.
 
  • #4
You might be interested that if ##E## is a (real) Hilbert space, then things simplify considerably.

Let ##\varphi## be an surjective isometry, then . Thus ##\|\varphi(x) - \varphi(y)\| = \|x-y\|##.

Let ##\psi(x) = \varphi(x) - \varphi(0)##, then ##\psi## is a surjective isometry which satisfies ##\psi(0) = 0##.

Note that in a Hilber space, we have ##\|x - y\|^2 = \|x\|^2 + \|y\|^2 - 2<x,y>##. Thus

[tex]
\begin{eqnarray*}
2<\psi(x),\psi(y)>
& = & \|\psi(x) - \psi(0)\|^2 + \|\psi(y) - \psi(0)\|^2 -\|\psi(x) - \psi(y)\|^2\\
& = & \|x\|^2 -\|y\|^2 - \|x-y\|^2\\
& = & 2<x,y>
\end{eqnarray*}
[/tex]

Now let ##z## be arbitrary. Then ##z=\psi(y)## for some ##y##. Then

[tex]
\begin{eqnarray*}
<\psi(\alpha a +\beta b),z>
& = & <\psi(\alpha a + \beta b),\psi(y)>\\
& = & <\alpha a + \beta b, y>\\
& = & \alpha <a,y> + \beta <b,y>\\
& = & \alpha <\psi(a),\psi(y)> + \beta <\psi(b),\psi(y)>\\
& = & <\alpha \psi(a) + \beta \psi(b), z>
\end{eqnarray*}
[/tex]

This holds for all ##z##, thus ##\psi(\alpha a + \beta b) = \alpha \psi(a) + \beta \psi(b)## and ##\psi## is linear.
 
  • #5
micromass said:
You might be interested that if ##E## is a (real) Hilbert space, then things simplify considerably.
Yes, I am interested in that. Thanks for posting it.

I have a followup about the first issue I brought up in post #1. After reading your reply, I see that if X and Y are normed spaces over ℝ, the following conditions on a function ##f:X\to Y## are equivalent.

(a) ##f-f(0)## is linear.
(b) There's a linear ##L:X\to Y## and a ##y\in Y## such that ##f(x)=Lx+y## for all ##x\in X##.
(c) For all ##t\in[0,1]## and all ##x,y\in X##, we have ##f(tx+(1-t)y)=tf(x)+(1-t)f(y)##.

My question is, is this still true if X and Y are normed spaces over ℂ? Define F=f-f(0). Your method shows that (c) implies that F is ℝ-linear. But is it ℂ-linear? I think I see how to deal with arbitrary complex numbers if it's true that F(ix)=iF(x) for all x. But I don't see how to deal with F(ix).

As far as I can tell, this has no relevance to the validity of the proof of the Mazur-Ulam theorem that we've been discussing, since we prove (a) directly, not (c). I'm just curious if (c) works as a definition of "affine map" even in the complex case.
 
  • #6
I don't think it holds. Take ##\mathbb{C}\rightarrow \mathbb{C}:z\rightarrow \overline{z}##. Then this map is easily checked to be affine, but it's not linear. So (a) and (b) are not equivalent anymore.

Note that the same example shows that Mazur-Ulam fails in complex vector spaces.
 
  • #7
micromass said:
I don't think it holds. Take ##\mathbb{C}\rightarrow \mathbb{C}:z\rightarrow \overline{z}##. Then this map is easily checked to be affine, but it's not linear. So (a) and (b) are not equivalent anymore.

Note that the same example shows that Mazur-Ulam fails in complex vector spaces.

Ah, I should have thought of that example. It satisfies (c), but not (a) or (b). (a) and (b) are so trivially equivalent that you probably forgot that I wrote them down as two separate statements.

(a) and (b) are equivalent, and imply (c). But (c) doesn't imply (a) or (b), if "linear" now means "ℂ-linear".

I'm not entirely clear on which condition is the appropriate definition of "affine map" in the context of complex normed spaces. I suspect that it's (a). In that case, Mazur-Ulam doesn't hold for complex normed spaces. But if it's (c), then it does hold.

I have typed up my version of the proof from the pdf (completed by your insights) for my notes. It seems to me that that what we actually prove is that if ##f:X\to Y## is a bijective isometry between normed spaces, then f-f(0) is ℝ-linear. This implies that f-f(0) satisfies (c). But your example shows that in general, it doesn't satisfy (a) (with "linear" meaning "ℂ-linear").
 
  • #8
I think the right notion of of affine map is the following. Let k be a field. Then an affine map of a k-vector space E to a k-vector space F must satisfy

[tex]f(\lambda_1 x_1 + ... + \lambda_n x_n) = \lambda_1 f(x_1) + ... + \lambda_n f(x_n)[/tex]

for any ##\lambda_1 + ... + \lambda_n = 1##

This is again a new definition that didn't show up yet. However, it can be shown that it's always equivalent to (a).
 

FAQ: Mazur-Ulam theorem (bijective isometries are affine maps)

What is the Mazur-Ulam theorem?

The Mazur-Ulam theorem, also known as the Mazur-Ulam isometric embedding theorem, is a mathematical theorem that states that any bijective isometry between two normed vector spaces is automatically an affine map.

What is a bijective isometry?

A bijective isometry is a function between two metric spaces that preserves distances and is a one-to-one and onto mapping. In other words, it is a bijection that preserves the metric structure of the spaces.

How does the Mazur-Ulam theorem relate to affine maps?

The Mazur-Ulam theorem proves that any bijective isometry must also be an affine map. An affine map is a function that preserves straight lines and ratios of distances, and it is a fundamental concept in geometry and linear algebra.

What are the applications of the Mazur-Ulam theorem?

The Mazur-Ulam theorem has various applications in pure mathematics, including the study of convex geometry, functional analysis, and metric geometry. It also has applications in physics, specifically in the theory of relativity.

Is the Mazur-Ulam theorem only applicable to normed vector spaces?

No, the Mazur-Ulam theorem can be extended to other types of metric spaces, such as Banach spaces, Hilbert spaces, and more general metric spaces. However, the original theorem only applies to normed vector spaces.

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