Deriving Statistical Behavior of Particles via Classical Mechanics

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Discussion Overview

The discussion revolves around the possibility of deriving the statistical behavior of many particles through deterministic classical mechanics, particularly in the context of computational simulations. Participants explore theoretical implications, practical challenges, and the definition of entropy within such simulations.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • Some participants propose that it is theoretically possible to derive statistical behavior from deterministic classical mechanics through computation, but practical limitations exist regarding computation time and resources.
  • One participant suggests using Boyle's law as a tractable case for simulation, emphasizing the need for significant computational power to simulate a large number of particles.
  • There is a discussion about defining entropy in a deterministic simulation, with some participants suggesting it could be based on the number of microstates corresponding to a given macrostate.
  • One participant raises the issue of indistinguishability in simulations, referencing Gibbs' paradox and its implications for classical mechanics.
  • Another participant questions whether dynamical systems can adequately describe electron behavior in atoms, suggesting a potential off-topic divergence in the discussion.

Areas of Agreement / Disagreement

Participants express a mix of agreement on the theoretical possibility of using classical mechanics for statistical behavior, but practical challenges and definitions remain contested. There is no consensus on how to define entropy or the applicability of dynamical systems to atomic behavior.

Contextual Notes

Limitations include the dependence on computational resources, the need for careful consideration of indistinguishability in simulations, and unresolved definitions of entropy in the context of deterministic simulations.

thaiqi
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Hello, using computation simulation, can the statistical behavior of many particles be derived through deterministic classical mechanics?
 
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In principle, yes. In practice... how long are you willing to wait on the computation?

Consider Boyle's law, which might be the most tractable case. Google will give you reasonable estimates for the velocity and mean free path of a particle; these will give you order-of-magnitude values for the time and space granularity you’ll need. Figure something ##10^{22}## particles in your simulation. How many floating point operations do you need to simulate one second? Divide that by what your hardware is capable of to know how long the simulation will take.
 
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Nugatory said:
In principle, yes.

How would we define Entropy in a deterministic simulation?
 
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Stephen Tashi said:
How would we define Entropy in a deterministic simulation?
I’m thinking the same way as always: number of microstates corresponding to a given macrostate. The simulation of course takes the system to a particular microstate, but we can still consider how many other microstates would produce the same macrostate.
 
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Thanks.
Nugatory said:
In principle, yes. In practice... how long are you willing to wait on the computation?

Consider Boyle's law, which might be the most tractable case. Google will give you reasonable estimates for the velocity and mean free path of a particle; these will give you order-of-magnitude values for the time and space granularity you’ll need. Figure something ##10^{22}## particles in your simulation. How many floating point operations do you need to simulate one second? Divide that by what your hardware is capable of to know how long the simulation will take.
Can dynamical system be used to describe the behavior of the electron in the atom?
 
Nugatory said:
I’m thinking the same way as always: number of microstates corresponding to a given macrostate. The simulation of course takes the system to a particular microstate, but we can still consider how many other microstates would produce the same macrostate.
Don't want to go off-topic, but you have to assume indistinguishability is not relevant to the problem you are simulating otherwise you could run into problems (like Gibbs' paradox). That's really an extreme case and is more of a question whether classical mechanics could be applied.

PS: You could still solve Gibbs paradox in the framework of classical mechanics, but you'll need to take care of the indistinguishability separately and it will not follow directly from the equations of motion (hamilton equations) since distinguishability implies a greater number of microstates. The interesting thing (to me) is that Gibbs' paradox arise in a pretty "classical" context (a box full of gas) which classical mechanics is perfectly fit to describe.
 
Stephen Tashi said:
How would we define Entropy in a deterministic simulation?
You mean in a classical molecular-dynamics simulation? That's very difficult. One way is to consider some subsystem (e.g., considering only particles in a certain partial volume) and calculating the corresponding averages on the one-particle distribution.
 

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