Art Vandelay;1569631
There's a bit of a difference between saying that a metric [I said:
defines[/i] a diffeomorphism, and a metric is a diffeomorphism. Furthermore, I may indeed be deficient in my understanding of the math, but I don't see how a metric defines a diffeomorphism.
Do you know about dual spaces? We have V, the space of vectors and V*, the space of linear applications V ->
R. We say V* is the dual space to V and we can define a dual basis. But these spaces are not canonically isomorphic, the isomorphisms you can define between them depend on the basis. If you are in a riemannian manifold, the metric automatically is a base independent isomorphism. It is also a diffeomorphism if everything is smooth (a diffeomorphism is an application such that both the application and its inverse are differentiable).
There's no point arguing that a metric is a diffeomorphism between the tangent and cotangent bundles, because this is basic geometry, not something I have just invented. How much do you know about geometry and analysis? I can't explain these things unless I know where to start.
First of all, a metric applies to one space, so if you're trying to set up a diffeomorphism, don't you need two metrics (one for each space)?
No. A metric has two slots g(·,·) if you fill both of them you get a number. If you fill one of them you get a covariant vector. Its inverse, g
-1, has also two slots, to be filled with covariant vectors. If you only fill one you get a contravariant vector. Haven't you seen this kind of expressions:
g
abv
a=v
b (TM -> T*M)
g
cdv
c=v
d (T*M -> TM)
Whe I say the metric is an isomorphism I mean the formulae above. The metric raises and lowers indice, and the relation v
a -> v
a is unambiguous once you have a metric. That's the second thing you learn about a metric (the first being the bit about the scalar product). Of course, g
ac is the inverse application.
Secondly, let's consider the following situation:
You have two spaces, X and Y, and diffeomorphisms between each and the real numbers:
f: X->R
g: Y->R
There are obvious metrics d1, d2:
d1(x1,x2)=|f(x1)-f(x2)|
d2(y1,y2)=|g(y1)-g(y2)|
Those seem to be distances, rather than metrics. d1(x1,x1) = 0, for all x1. This is not a metric, every vector would have length 0.
So now it looks like this defines a diffeomorphism
h: X->Y
h(x)=g-1(f(x))
But isn't h(x)=g-1(-f(x))
also a diffeomorphism? What's wrong with my thinking?
I'm sorry, I don't understand what you are saying here, or how it is relevant to the metric.
Yllanes said:
That doesn't make sense. Tell me why can't I talk of [the?] metric of a 2-dimensional rotating disk?
You can. You just can't define a metric for a 2-dimensional rotating disk, then refer to it as "the" metric
when discussing the 3-dimensional space in which the disk exists.
The 3-d space doesn't matter. The third coordinate doesn't add anything special, we can concentrate on the other two. If you think of the 3D metric as a 3x3 matrix, we can talk about the 2x2 submatrix, which is the interesting part. The disk could be embedded in a 6-dimensional space, all we wanted to talk about is the 2 relevant dimensions. And I can very well talk about *THE* metric.
Why do I need to carry all first 4 trivial rows? If the only part that can change is the 2x2 submatrix a,b,c,d, then I can refer to it as the metric. And I don't know how I have been dragged into this. If you are on a rotating disk, you don't have an Euclidean metric, you have a different thing. That's all I said.