You can predict it, you don't really need the vacuum either. This is actually one way that people cheat with dice: https://youtu.be/t1dTadFlyDE
We used to play dice a lot when I was a kid, and sooner or later most of us figured out ways of cheating with trick rolls. The simplest of these works by reducing the amount of rotation the die will have like in the video, but also restricting how much the die bounces in your hand and throwing in a consistent way. But in principle I don't see why you couldn't build a machine to cheat more elaborately.
An idealized die thrown on an ideal flat plane is pretty easy to predict. I personally would do it by running a Monte Carlo to build a model, and then running future throws through that model. It would be 100% correct.
For the real world, I suspect there are three major sources of error:
- Slight variations in how you throw - can be solved by building a precision throwing machine
- Imperfections on the surface - you would have to build some sort of profile of the environment empirically, and your model wouldn't work for a different table
- Air currents - minimized with heavy dice, still air in a closed space, or a vacuum like you say
The question is whether the ideal model can predict the real world. I suspect if the table is reasonably flat, the dice are even, the air is still, it would work quite well. Not 100% maybe, but probably %99 with a good thrower robot.
The die roll is actually a pseudorandom number generator. It is a deterministic, mechanical process, but the output is produced in an obfuscated way from two inputs, or seeds: The particular imperfections of the table, and the particular characteristics of each throw (no two human throws are exactly the same, and that probably does have quantum mechanical causes). If you can supply the same seed, you should get the same result.
Another analogy is the hash: The roll is the hash function. The output is the die result. The input is the throw (vector momentum and and angular momentum imparted). The surface is the salt.
Dice are a very good PRNG (or hash) because it is well known that the resulting distribution is flat. If a human is throwing, you can even treat them as true random. But true randomness comes from the randomness inherent in our musculoskeletal system, not the mechanics of die roll.
Why in quantum mechanics we say a particle for example electrons are in two states. We only get a probabilistic value of position, that does not mean, its in two states at a time. The way we see it may be destroying the probabilistic character.
Heisenberg's principle says that the exact location and speed of a particle cannot be known. Not only by us humans, but it is generally indeterminate. This appears to be a fundamental property of the universe. In that sense, it literally is in two places at the same time, but of course the mistake made here is assuming that the electron must be a point mass simply because we derived the probability cloud by modeling it as one.
However, when you have a large number of particles glues to each other, their location probabilities (for instance) combine in a way that reduces the spread. A die is made of an absurdly large number ($10^{23}$ ish) of protons, neutrons and electrons, and so the spread is tiny. Of course, you can't know the exact location of the die, but when the error is fractions of the size of an atom, you won't notice. That's why we pretend uncertainty does not exist on the macro scale: It's usually just averaged away and has too little effect.
We only get a probabilistic value of position, that does not mean, it's in two states at a time.
-yes, it doesn't mean it is in two states at the same time. Many people use this wrong sentence to describe quantum superposition probably because they've remained classical from their heart. It's utterly nonsense to say that the electron is at many places at the same time. Rather, the electron has the possibility to be at both places at the same time. BTW, how is this related to the dice?? – Oct 26 '15 at 19:08