Multiple-scale analysis for 2D Hamiltonian?

Click For Summary

Discussion Overview

The discussion revolves around the application of multiple-scale analysis to a specific 2D Hamiltonian system, exploring the dynamics of a particle described by a Hamiltonian that includes a small parameter. Participants examine the equations of motion and consider numerical methods for analyzing the system's behavior over time.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested
  • Mathematical reasoning
  • Experimental/applied

Main Points Raised

  • One participant introduces the concept of multiple-scale analysis and poses a question about its applicability to a 2D Hamiltonian with a specific form.
  • Some participants express confusion regarding the dimensionality of the problem, suggesting it may be a 3-D problem despite the Hamiltonian being described in 2D.
  • Several participants propose numerical approaches, such as using Runge-Kutta methods and changing coordinate systems, to analyze the equations of motion and estimate quantities like '⟨p_x^2⟩' and '⟨p_y^2⟩'.
  • There is discussion about the use of Poincare plots to visualize the motion and determine whether the system exhibits integrable or chaotic behavior.
  • Participants share insights on interpreting Poincare plots, noting that closed curves indicate integrable motion while scattered points suggest chaotic dynamics.
  • One participant mentions the need to sample the 4D phase space effectively to identify regions of integrability and chaos.
  • Another participant shares their experience of systematically launching trajectories from the origin to create comprehensive Poincare plots, indicating mixed phase space behavior.

Areas of Agreement / Disagreement

Participants express differing views on the dimensionality of the problem and the necessity of using multiple-scale analysis. There is no consensus on the best approach to analyze the Hamiltonian or the interpretation of the Poincare plots, indicating multiple competing views remain.

Contextual Notes

Participants note the complexity of the phase space and the challenges in determining integrability versus chaos, highlighting the dependence on parameter values and initial conditions. The discussion reflects uncertainty regarding the most effective methods for analysis and the interpretation of results.

  • #31
Dr. Courtney said:
I think all your questions regarding behavior close to epsilon = 0.25 can be answered with suitable numerical experiments using your current computational technique in MMa.

I would be confident that a variable step size Runge-Kutta would likely be able to investigate the dynamics for epsilon = 0.01 to 0.001 and likely even down to 0.0001.
The following contains 500 different trajectories with initial condition satisfying: x(0) = 0, y(0) = 1 with p_x^2(0) + p_y^2(0) = 1
poincare_together.jpg
 
Physics news on Phys.org
  • #33
Doing the same thing with a smaller epsilon, it seems like the behaviour is quite different?
poincare_together_extreme.jpg


How can I extract information from these Poincare plots?
 
  • #34
I think you should compute your long time integrals for the squared momenta for different trajectories, overlay the values with the tori they represent in the graph and look for trends between the tori and resulting integrals.
 
  • #35
Dr. Courtney said:
I think you should compute your long time integrals for the squared momenta for different trajectories, overlay the values with the tori they represent in the graph and look for trends between the tori and resulting integrals.

Looking at the 500 trajectories, I calculated <p_x^2> and <p_y^2> for each of the trajectories by evolving the trajectories over a long period of time. Then I arrange the trajectories according to their <p_x^2> value (from smallest to largest).

There seems to be a pattern, similar values of <p_x^2> have similar poincare plots. As <p_x^2> increases, the poincare plots extend further.
http://gph.is/1OOtACG
 
Last edited:
  • #36
Wow! Great work. It seems like you have this one sorted out. Congratulations.
 
  • #37
Dr. Courtney said:
Wow! Great work. It seems like you have this one sorted out. Congratulations.
Well, I still don't really know how to find the invariant. I still don't know how to tackle the questions that I want to answer. Do you have any recommendations?
 
  • #38
Random137 said:
Well, I still don't really know how to find the invariant. I still don't know how to tackle the questions that I want to answer. Do you have any recommendations?

In general, there usually is not a closed form expression for the constant of motion for the remaining tori. There may be some empirical numerical procedure for determining some expression (in terms of positions and momenta) that is approximately constant. Is this what you are trying to do?

What are the questions you want to answer?
 
  • #39
Dr. Courtney said:
In general, there usually is not a closed form expression for the constant of motion for the remaining tori. There may be some empirical numerical procedure for determining some expression (in terms of positions and momenta) that is approximately constant. Is this what you are trying to do?

What are the questions you want to answer?
What I wanted to answer is, for a given set of initial conditions (x(0), y(0), p_x(0), p_y(0)) can I roughly estimate the values of <p_x^2> and <p_y^2> without running the numerical integrations. Actually, I know the value of <p_x^2> + <p_y^2> (= constant * energy) for a given set of initial conditions because of Virial Theorem but I don't know how they are distributed between <p_x^2> and <p_y^2>.
 
  • #40
Random137 said:
What I wanted to answer is, for a given set of initial conditions (x(0), y(0), p_x(0), p_y(0)) can I roughly estimate the values of <p_x^2> and <p_y^2> without running the numerical integrations. Actually, I know the value of <p_x^2> + <p_y^2> (= constant * energy) for a given set of initial conditions because of Virial Theorem but I don't know how they are distributed between <p_x^2> and <p_y^2>.

I think the phase space is too complicated to do what you want. All the tori close to a given tori at one point in phase space do not remain close to it. Two orbits close to each other at one point can sample very different regions of phase space over time and thus have very different <p_x^2> and <p_y^2>.
 
  • #41
Dr. Courtney said:
I think the phase space is too complicated to do what you want. All the tori close to a given tori at one point in phase space do not remain close to it. Two orbits close to each other at one point can sample very different regions of phase space over time and thus have very different <p_x^2> and <p_y^2>.
Does that mean the system is chaotic?

Would you say in the case where epsilon tending to zero would be easier/feasible to do?
 
  • #42
Random137 said:
Does that mean the system is chaotic?

Would you say in the case where epsilon tending to zero would be easier/feasible to do?

The fact that there are so many tori show that the system is not chaotic. The fact that the tori show intricate and complicated patterns prevents you from expressing <p_x^2> and <p_y^2> as simple functions of the initial conditions.

Will the case where epsilon --> zero be easier? Maybe. It depends on how simple the structure of the tori tends to be. Do most of the tori remain next to the ones next to it, are are they a convoluted and tangled mess?
 
  • #43
Dr. Courtney said:
The fact that there are so many tori show that the system is not chaotic. The fact that the tori show intricate and complicated patterns prevents you from expressing <p_x^2> and <p_y^2> as simple functions of the initial conditions.

Will the case where epsilon --> zero be easier? Maybe. It depends on how simple the structure of the tori tends to be. Do most of the tori remain next to the ones next to it, are are they a convoluted and tangled mess?
Can you explain what do you mean by tori in the poincare plots?
 
  • #44
When all the intersections of a given trajectory trace out a closed curve, this indicates that the motion is confined to a torus - a shape with the topology of a donut winding around through phase space. Trajectories that are confined to tori give evidence of the existence of a constant of motion in addition to the energy.
 
  • #45
Dpitney said:
When all the intersections of a given trajectory trace out a closed curve, this indicates that the motion is confined to a torus - a shape with the topology of a donut winding around through phase space. Trajectories that are confined to tori give evidence of the existence of a constant of motion in addition to the energy.
From the poincare points, it doesn't look it will form a completely closed curve, is it safe to assume it will form a completely closed curve as time tends to infinity?
 
  • #46
The point is more the trajectory is confined to the surface of the tori. Some orbits are periodic in that they retrace the same path and so will make a dotted line rather than closing the curve. Non-periodic orbits will eventually fill in all the gaps to infinitesimally close to each other.
 

Similar threads

  • · Replies 7 ·
Replies
7
Views
1K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 3 ·
Replies
3
Views
1K
  • · Replies 3 ·
Replies
3
Views
3K
Replies
25
Views
1K
Replies
4
Views
2K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 10 ·
Replies
10
Views
2K
  • · Replies 27 ·
Replies
27
Views
3K
  • · Replies 2 ·
Replies
2
Views
2K