The HotBits service at Fourmilab in Switzerland is an excellent example of a random number generator that uses this technique. Another suitable physical phenomenon is atmospheric noise, which is quite easy to pick up with a normal radio.
You could also use background noise from an office or laboratory, but you'll have to watch out for patterns. The fan from your computer might contribute to the background noise, and since the fan is a rotating device, chances are the noise it produces won't be as random as atmospheric noise. Thunderstorms generate atmospheric noise.
As long as you are careful, the possibilities are endless. Undoubtedly the visually coolest approach was the lavarand generator , which was built by Silicon Graphics and used snapshots of lava lamps to generate true random numbers. Unfortunately, lavarand is no longer operational, but one of its inventors is carrying on the work without the lava lamps at the LavaRnd web site. ORG, but also from web page hits received by the EntropyPool's own web server. Regardless of which physical phenomenon is used, the process of generating true random numbers involves identifying little, unpredictable changes in the data.
ORG uses little variations in the amplitude of atmospheric noise. They are also nondeterministic , meaning that a given sequence of numbers cannot be reproduced, although the same sequence may of course occur several times by chance.
TRNGs have no period. These characteristics make TRNGs suitable for roughly the set of applications that PRNGs are unsuitable for, such as data encryption, games and gambling. Conversely, the poor efficiency and nondeterministic nature of TRNGs make them less suitable for simulation and modeling applications, which often require more data than it's feasible to generate with a TRNG. The following table contains a summary of which applications are best served by which type of generator:.
One characteristic that builders of TRNGs sometimes discuss is whether the physical phenomenon used is a quantum phenomenon or a phenomenon with chaotic behaviour. There is some disagreement about whether quantum phenomena are better or not, and oddly enough it all comes down to our beliefs about how the universe works. The key question is whether the universe is deterministic or not, i. Determinism is a difficult subject that has been the subject of quite a lot of philosophical inquiry, and the problem is far from as clear cut as you might think.
I will try and explain it here, but would also like to point out that Wikipedia has a concise account of the debate. Quantum mechanics is a branch of theoretical physics that mathematically describes the universe at the atomic and subatomic levels. Random number generators based on quantum physics use the fact that subatomic particles appear to behave randomly in certain circumstances.
There appears to be nothing we know of that causes these events, and they are therefore believed by many to be nondeterministic. In comparison, chaotic systems are those in which tiny changes in the initial conditions can result in dramatic changes of the overall behaviour of the system. Weather systems are a good example of this, and you may have heard of the butterfly effect , a thought experiment in which a butterfly beating its wings in Brazil is able to affect the winds subtly but critically, just enough to cause a tornado in Texas.
Proponents of random number generators of the quantum variety argue that quantum physics is inherently nondeterministic, whereas systems governed by physics are essentially deterministic. I am personally undecided as to where I stand on the determinism-nondeterminism scale, but for the sake of argument, I will put on my determinist hat and use RANDOM. ORG as an example. ORG numbers can be viewed as a chaotic but deterministic system.
Hence, if you knew enough about the processes that cause atmospheric noise e. However, to do this, you would probably need knowledge of the position and velocity of every single molecule in the planet's weather systems. This is of course infeasible, and the inaccuracy of weather forecasts is a good example of how difficult it is to give even a rough estimate of the behaviour of weather systems.
ORG, even for a determinist. A similar case on a different scale could be made for random number generators based on lava lamps. Now, you may think that since there's dispute about the suitability of chaotic phenomena for generating randomness, then why not just stick with quantum physics? That would seem to be the safe bet. However, quantum generators aren't safe from critique either. Hard determinists will claim that subatomic particle behaviour isn't really random but rather exactly as predetermined as everything else in the universe has been since the Big Bang.
The reason we think these specific particles behave randomly is simply that no human measurement has been able to account for their behaviour. In this view, subatomic events do indeed have a prior cause, but we just don't understand it yet , and the events therefore seem random to us. To a hard determinist, quantum physics is exactly as suited for random number generation as is atmospheric noise or lava lamps.
This is only one possible argument, and there are many others. When it comes down to it, I think the most meaningful definition of randomness is that which cannot be predicted by humans.
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Designing a Random Number Generator - Designing a Random Number Generator Introduction Random Number Generator is a computational routine or a physical device that produces numbers which don’t have any pattern in them. however, it is important that the numbers used to generate keys are not just seemingly random; they must be truly unpredictable. * This vignette for the R package random is a transcribed version of the original essay by Mads Haahr that was.