How does a mechanical random number generator differ from a pseudo-random number generator?
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In: Mathematics
A psuedo-random number generator takes a “seed”, which is often the current time in milliseconds, and inputs it to a function that spits out another number, uniformly distributed across the possible outcomes. When another “random” number is needed, the first number spit out is fed back into the function to produce another number. The function is such that it is very difficult to predict what the next number will be based off of what the previously-produced numbers are, if you don’t have the starting seed, but if you and someone else use identical seeds you should get the same series of numbers.
A mechanical number generator is one that uses an external, unpredictable process to generate each number. A possible example of this is pointing a camera at a wall full of lava lamps, and then running a function over the resulting image data of a specific frame when a random number is needed. As lava lamps move in unpredictable ways, and very small changes to the visual state result in large changes to the result of a hashing function, this produces “true” random number generation. There are many physical processes that can be used this way – one could have a bunch of dice in a chamber that is regularly jostled, for instance, or you could measure radioactive decay patterns that happen at unpredictable intervals and trajectories.
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