Proof of Poincare Recurrence Theorem

In summary, the conversation discusses a search for an accessible reference that outlines a proof of Poincare's recurrence theorem. The individual mentions having trouble finding a suitable proof and requests that it provide a rebuttal to three assumptions related to phase points and their trajectories. Despite searching on Wikipedia and Google, the individual is still unable to find a satisfactory proof. Another individual offers a simplified explanation of the proof, involving dynamics and the Liouville theorem. However, they remind the group that this is not a homework question.
  • #1
NickJ
36
0
Does anyone know of an accessible reference that sketches a proof of Poincare's recurrence theorem? (This is not a homework question.)

I'm coming up short in my searches -- either the proof is too sketchy, or it is inaccessible to me (little background in maths, but enough to talk about phase points, their trajectories).

If possible, I'd like the proof to provide a reductio of the following assumptions:


1. A is a set of phase points in some region of Gamma-space, such that each point in A represents a system with fixed and finite energy E and finite spatial extension.

2. B is a non-empty subset of A consisting of those points on trajectories that never return to A having once left A.

3. The Lebesgue measure of B is both finite and non-zero.

I know these three assumptions are jointly inconsistent -- but I can't figure out why.

Thanks!
 
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  • #2
Did you try Wikipedia, and google?
 
  • #3
yup. no luck.
 
  • #4
Ohw, the proof is quite easy to understand. First you must know that dynamics deals with a Hamiltonian, that is give me 2N numbers which we call position (first N) and momentum (second N) and I can tell you how the system evolves. Now, suppose you don't know precisely what the initial momenta and positions are and you take some volume in 2N space, then the Liouville theorem says that this volume is preserved if you drag it along the flow. Now assume that the points in your original neighborhood all belong to different trajectories, then the snake moves in a finite volume and cannot self intersect herself (because different fluid trajectories cannot intersect each other). This clearly leads to a contradiction.


Careful
 
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1. What is the Poincare Recurrence Theorem?

The Poincare Recurrence Theorem states that in a closed, finite system, any state that the system may be in will eventually recur infinitely many times. This means that if a system is left to evolve on its own, it will eventually return to a state that is nearly identical to a previous state, and this process will continue infinitely.

2. Who discovered the Poincare Recurrence Theorem?

The Poincare Recurrence Theorem was first proven by the French mathematician Henri Poincare in the late 19th century. However, the concept of recurrence in dynamical systems had been studied by mathematicians before Poincare, including Joseph Fourier and Pierre-Simon Laplace.

3. What are the implications of the Poincare Recurrence Theorem?

The Poincare Recurrence Theorem has significant implications in various fields, including physics, mathematics, and philosophy. It suggests that the universe may be a closed, finite system, and that all events that have occurred in the past may recur in the future. This has raised questions about the concept of time and the determinism of the universe.

4. How does the Poincare Recurrence Theorem relate to entropy?

Entropy is a measure of the disorder or randomness in a system. The Poincare Recurrence Theorem states that a closed system will eventually return to a previous state, which means that entropy will decrease over time. This is in contrast to the second law of thermodynamics, which states that entropy always increases in a closed system.

5. Is the Poincare Recurrence Theorem applicable to all systems?

No, the Poincare Recurrence Theorem is only applicable to closed, finite systems. This means that the system must be isolated from outside influences and have a finite number of possible states. It also assumes that the system follows deterministic laws, meaning that its future states can be predicted from its current state. This theorem does not apply to open or infinite systems.

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