Time reversibility of velocity verlet easy

In summary, the conversation discusses the proof of time reversibility for the velocity verlet scheme. By substituting -dt in at dt, the position and velocity equations can be simplified and shown to be equal to their original values, proving the scheme's time reversibility. The conversation also addresses concerns about the squared factor in the acceleration term and concludes that the proof is correct.
  • #1
dikmikkel
168
0

Homework Statement


Prove that the velocity verlet scheme is time reversible.

Homework Equations


r(t+dt) = r(t) + v(t)dt + 1/2a dt^2
v(t+dt) = v(t) + 1/2 a(t)dt + 1/2a(t+dt)dt

The Attempt at a Solution


I substitute -dt in at dt and get:
r(t-dt) = r(t) - v(t)dt +1/2a dt^2
v(t-dt) = v(t) -1/2a(t)dt -1/2a(t-dt)dt

the squared factor of time in the acceleration term is annoying me, can it be done easier?
 
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  • #2
what exactly do you see is wrong with the squared factor?
 
  • #3
Well, the acceleration should(my opinion) lead to move the position back again if it is time reversible(as it is). Can you help?
 
  • #4
do the calculations for t''=t'+dt, then do them again for t'=t-dt, everything should simplify back to t''=t.
 
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  • #5
When i do that it still does not make sense to me.
Would you do the first half part, maybe with substitutions.
 
  • #6
Okay, now i found out i think.

r(t+dt) = r(t)+v(t)dt + 1/2a(t)dt^2
v(t+dt) = v(t)+1/2a(t)dt + 1/2a(t+dt)dt
Now we are at r(t+dt) and want to reverse it:
r(t-dt) = r(t+dt) - v(t+dt)dt + 1/2a(t+dt)dt^2 =
r(t)+v(t)dt + 1/2a(t)dt^2 -(v(t)+1/2a(t)dt + 1/2a(t+dt)dt)dt +1/2a(t+dt)dt^2 =
r(t) . Q.e.d
v(t-dt) = v(t+dt) - 1/2a(t+dt)dt-1/2a(t+dt-dt)dt =
v(t)+1/2a(t)dt + 1/2a(t+dt)dt -1/2a(t+dt)dt-1/2a(t)dt =
v(t), q.e.d
Is that right?
 

FAQ: Time reversibility of velocity verlet easy

What is the concept of time reversibility in the Velocity Verlet algorithm?

The Velocity Verlet algorithm is a numerical integration method used to solve equations of motion in classical mechanics. Time reversibility refers to the ability of the algorithm to accurately simulate the motion of a system both forwards and backwards in time, with the same initial conditions. This means that the algorithm is able to accurately predict the future state of the system based on its current state, and also accurately recreate the past state of the system based on its current state.

Why is it important for the Velocity Verlet algorithm to be time reversible?

Time reversibility is important for the Velocity Verlet algorithm because it ensures the accuracy and stability of the simulation. If the algorithm is not time reversible, small errors in the calculation can accumulate and lead to significant deviations in the results. By being time reversible, the algorithm is able to correct these errors and produce reliable and consistent results.

Is the Velocity Verlet algorithm always time reversible?

Yes, the Velocity Verlet algorithm is always time reversible. This is because the algorithm is based on symplectic integration, which is a type of numerical integration that preserves the symplectic geometry of the system. This property ensures that the algorithm is always able to accurately simulate the motion of the system both forwards and backwards in time.

What factors can affect the time reversibility of the Velocity Verlet algorithm?

One factor that can affect the time reversibility of the Velocity Verlet algorithm is the timestep used in the simulation. A smaller timestep can improve the accuracy and stability of the simulation, making it more time reversible. However, a very small timestep can also increase the computational cost of the simulation. Other factors that can affect time reversibility include rounding errors in the calculations and the use of approximations or simplifications in the model.

Are there any limitations to the time reversibility of the Velocity Verlet algorithm?

While the Velocity Verlet algorithm is generally considered to be time reversible, there can be limitations in certain cases. For example, if the system being simulated is chaotic, small differences in initial conditions can lead to large differences in the results. In these cases, the algorithm may not be able to accurately simulate the motion of the system backwards in time. Additionally, if the system undergoes a phase transition or discontinuity, the algorithm may not be able to accurately predict the past state of the system based on its current state.

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