Throw of a die: Dependance on initial conditions and chaos

AI Thread Summary
The discussion explores the probability of outcomes when throwing a fair die, questioning whether it's possible to model the physics behind the throw to confirm that each outcome has a probability of 1/6. It highlights that, theoretically, knowing the initial conditions could allow for predicting the outcome, but achieving this requires a comprehensive model of the die's interactions during the throw. The complexity of accurately simulating the throw, including collisions and rolling dynamics, is noted as a significant challenge. Additionally, the conversation raises the possibility of calculating probabilities for asymmetric dice, suggesting that random initial conditions could influence the outcome distribution. Overall, the feasibility of modeling these scenarios remains uncertain due to the lack of precise empirical models.
greypilgrim
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Hi,

We normally use a simple symmetry argument to show that the probability of each outcome of a throw of a fair, cube-shaped die is 1/6. However, is it possible to actually model the physics of the throw and show that the probabilities are 1/6?

Since this is classical physics, the outcome can in principle be predicted knowing the inital conditions of the throw. So I guess we'd have to show that very similar initial conditions lead to any of the six outcomes. A numerical simulation of the throw might get nasty, but maybe there's a simpler chaos-theoretic argument?
 
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In practice, one needs a model based not only on initial conditions, but accurate empirical descriptions of all the collisions and interactions as the die is rolling and bouncing along. To my knowledge, an accurate model for all this is unavailable.
 
If already this is unavailable, is there a way to compute the probability distribution of an asymmetric die, consisting of a general rectangular cuboid with different sides a,b,c (or maybe let's first have a=b) with constant mass distribution, if the initial conditions are "random enough"?
 
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