Time Parameterizations and Diffeomorphisms

In summary, Fred is trying to understand a dynamical system that is time-dependent and he is having trouble because he does not understand how to re-parameterize time.
  • #1
FreHam
10
0
Hello!

It's my first post here, as I am currently reading some material, but have not been able to really grasp it. Sorry, if this is a rather dumb question.

I have a dynamical system (Newtonian) that is defined on some manifold M times R (time-dependent system). Say that time is labeled t. If I now transform the time t\mapsto t(s), which is a map from R to R.

If M has coordinates (x(t),y(t),z(t),u(t),v(t),w(t)) and I want to transform it with the time re-parameterization I get (x(t(s)),y(t(s)),z(t(s)),...). Is that a diffeomorphism from M x R to M x R, or how should I write that properly? Is the real map here not x(t) -> x(t(s)), etc. or does it suffice to say that the full map is just t -> t(s)?

I'm stuck and I have no idea. Again, I apologize for my stupidity, but any help is much appreciated. I could ask my professor, but having asked several things already without receiving much help, I hope you guys (and gals?) might have an answer...

Cheers,

Fred.
 
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  • #2
If your manifold is M x R and if you reparameterize time, then your manifold is still M x R and the diffeomorphism is described by (x,t) -> (x,s(t)). Reparameterization of time does nothing to the x coordinates. But if you consider maps from R to M (say, sections of the product bundle), then the coordinate description of these sections will change the way you wrote.
 
  • #3
Yes, it's basically a Lagrangian system, so I have a tangent bundle, M=TQ, where Q is the base manifold with coordinates q, and TQ has coordinates (q,\dot{q}). For a time-dependent Lagrangian L:TQ x R -> R, the diffeomorphism is a map TQ x R -> TQ x R, right? If so, I think I might finally get the hang of it. Otherwise, I'm back to square one.
 
  • #4
Well, it all depends on the details. Sometimes you are in the tangent bundle and sometimes in the "bundle of of jets" of maps from R to Q. When you re-parametrize time nothing happens to the tangent bundle. But something happens to the "bundle of jets". Jets are not very popular, therefore most textbooks avoid them. But then the readers may get confused as you are.

Things get however simpler when you get to particular problems and applications. Then you know what to calculate and how.
 
  • #5
Great, thanks a lot!
 

1. What are time parameterizations and diffeomorphisms?

Time parameterizations and diffeomorphisms are mathematical concepts used to describe the transformations of time in a physical system. A time parameterization refers to the mathematical representation of time in a system, while a diffeomorphism is a type of transformation that preserves the smoothness and structure of the system.

2. Why are time parameterizations and diffeomorphisms important in science?

These concepts are important because they allow scientists to accurately describe and analyze the behavior of systems over time. By understanding the transformations of time in a system, scientists can make predictions and gain insights into the underlying mechanisms of the system.

3. How do time parameterizations and diffeomorphisms relate to Einstein's theory of relativity?

Einstein's theory of relativity states that time is relative and can be affected by factors such as gravity and velocity. Time parameterizations and diffeomorphisms are used to describe these changes in time and help reconcile the differences between the theories of relativity and classical mechanics.

4. Can time parameterizations and diffeomorphisms be applied to all systems?

Yes, these concepts can be applied to any system that exhibits changes over time. This includes physical systems such as the movement of objects, as well as more abstract systems like financial markets or biological processes.

5. How do scientists use time parameterizations and diffeomorphisms in their research?

Scientists use these concepts in a variety of ways, such as modeling and simulating systems, analyzing data, and developing mathematical theories. They are particularly useful in understanding dynamic systems that involve complex interactions and changes over time.

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