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More Random Randomness

jfleck writes "According to the American Institute of Physics' Physics News Update, Kent State physicist James Gleeson has developed a technique for generating numbers approaching true randomness. His trick is to shine light through a liquid crystal, taking advantage of its turbulence and avoiding the inevitable risk of predictability in deterministic random number number algorithms."

13 of 80 comments (clear)

  1. silly by tps12 · · Score: 3, Insightful

    So it's a crystal and a light...a mechanical solution, in other words. Someone tell me how this is different from flipping a coin? True randomness has always been available in the physical world (hence the allure of horse racing). It's only in mathematics, and therefore computing science, that randomness cannot be achieved. And small though this "solution" may be, it doesn't quite count as an algorithm.

    --

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    1. Re:silly by photon317 · · Score: 3, Insightful


      I agree, but he may be onto something in that his solution may be easier than most to cheaply embed in low end computer hardware.

      Although I seem to remember hearing a long time ago how someone had built a circuit (which I presume could be put easily on an expansion card) that obtained entropy from the small (mostly temperature-fluctuation-induced) changes in capacitance and resistance on some standard crappy-grade capacitors and resistors in a simple circuit. While your case's overall temp might be a bit predictable to a tenth of a degree, I think this was supposed to be sensitive to the very small seemingly random fluctuations of a much smaller degree.

      --
      11*43+456^2
    2. Re:silly by GMontag451 · · Score: 3, Informative
      There are two different meanings of the phrase "random number". One is the coin-flipping variety, where any number within the range is possible, but is only as likely as every other number in the range. AFAICT, this isn't the kind of random numbers the article is talking about.

      The other kind of random number is a number that is entirely entropy. In other words, an uncompressible number. This type of number is extremely hard to generate, and by definition, cannot be generated by an algorithm shorter than the number because this would be a form of compression.

    3. Re:silly by flonker · · Score: 3, Insightful

      If your random number generator is incapable of generating a string of 256 0's in a row, there is something wrong with it.

      True randomness is defined by the fact that knowing all of the previous results gives you zero knowledge of the next result. Being difficult to compress is often a side effect of this, but is not a defining characteristic.

    4. Re:silly by GMontag451 · · Score: 3, Informative
      If your random number generator is incapable of generating a string of 256 0's in a row, there is something wrong with it.

      That is true for the first kind of random number generator that I talked about, not for the second kind.

      Maybe I can describe what I'm talking about better. There are two different types of random number generators. One kind is a generator that randomly produces numbers, which is what you are talking about. The other kind produces *random numbers*, which is something completely different. It is the difference between the generator being random, or the number itself being random no matter how it is generated.

      Randomly produced numbers are equidistributed along the range of the generator, usually from 0 to 1. Random numbers are numbers that are impossible to compress. A number is random no matter what the next result is, but is only randomly produced with respect to the numbers produced before and after it with the same algorithm.

  2. Why not Tea? by Anonymous Coward · · Score: 3, Funny
    I though the best way to get true random numbers was from watching brownian movement it a cup of tea.

    Anonymous only to avoid "-1 Redundant", I seem to get those when people miss the joke.

  3. in moderation by flux4 · · Score: 4, Funny

    Could this technology be used to moderate slashdot posts, in a manner even more astonishingly random than before?

    I mean, it's obviously in use in story-submission already. May as well be efficient.

  4. The big deal is... by lynx_user_abroad · · Score: 5, Insightful
    the bandwidth.

    It's fairly easy to generate truly random numbers in small quantities, but getting a sizable quantity of cryptographically true, cryptographically secure, cryptographically random numbers has always been a bit difficult. You almost have to do it in hardware, and you almost have to use something which is both isolated from external interference (so others can't load your dice) and doesn't bleed its information externally (so you can be sure you are the only one who knows the number). The first requirement rules out most things which rely on the external environment for input (like EM radiation). Add to this a third requirement for lots of randomness, (which rules out things like thermal junctions, or number of NT bluescreens per day) and a simple problem becomes hard.

    Remember, in this context the common definition of "random" meaning "I don't understand how it works" doesn't cut it. You need true "completely unpredictable by anyone" randomness for many security applications.

    --

    The thing about things we don't know is we often don't know we don't know them.

    1. Re:The big deal is... by rthille · · Score: 3, Funny

      > requirement for lots of randomness, (which rules out things like [...], or number of NT bluescreens per day)

      Hey, we're looking at Randomness, not infinities here!

      --
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  5. Hidden variables by MarkusQ · · Score: 3, Insightful

    This randomness is distinguishable from so-called "hidden variable" interpretations.

    Not quite. There's a hidden flaw in the argument against hidden variables; the "proof" subtily begs the question. To see this, imagine that there were a level of "hidden variables" complex enough that each quanta (quark, lepton, what have you) could have as much "state" as the entire universe as-we-know it. With such a system you could predetermine every "interaction" over the course of the whole history of the universe--there wouldn't be any "physics," just a mind bendingly huge collection of scripted motions.

    The point being, there's no way we could detect that this was the case...and thus there's know way we can prove that it isn't the case.

    Now, we are free to doubt that we live in such a universe (and believe in "truly random events") but this is just a belief, without any science to back it up.

    -- MarkusQ

  6. Problem with this method by Eagle5596 · · Score: 3, Interesting

    The primary problem with this method is that it is implemented in hardware, which produces quite a few problems.

    1) No known seed. One of the primary characteristics of a good random number generator is that the results are reproduceable. If I want to run the same experiment twice during some sort of simulation, I need to be able to generate the same stream of random numbers twice. Second it is always useful to have a random number generator with a [very large] full period, this obviously is not periodic, which makes it hard to determine if the system which is using the variate generation is chaotic or stable.

    2) Hardware random number generators are often difficult to port to all systems, and to interface with existing programming languages. A good solid pseudo-random number generator (like a Lehmer one) is based on a mathematical algorithm which is reproducable in just about any environment.

    There are many other problems with this approach as well, too numerous to name. In general hardware random number generators are a bad idea.

  7. Re:Here's a true randomness algorithm by sdjunky · · Score: 3, Insightful

    The problem with this is that if you have an idea of the algorithm used you can run through a subset of numbers and then find your seed value.

    e.g. if I know your app is pulling from time of day and my log entries show that it was at 9:55 AM Then I can run a range of all time values between say 9:50 and 10:00 including MS. In so doing you are tying your random number to a known thing which defeats the purpose.

    A truly random number would be one that can't be determined by outside factors ( especially time )

  8. Randomness is Not All That Random by jefu · · Score: 3, Interesting

    Randomness is a very complex subject with lots of odd facets. The article cited at the top of this topic may be a good way to generate more or less "true" random sequences (17 is, of course, the Only Random Number).

    Random sequences based on quantum (or similar effects) are useful primarily in cryptography where "true" randomness is important. Probably in video gambling devices as well (is there any good way to tell how they generate randomness).

    Random sequences based on deterministic generators are useful for lots of other things: simulation, pysol (including freecell), and a number of algorithms. These are not useless by any means and while they need to satisfy some fairly stringent statistical properties, they can be generated by well defined algorithms starting with seeds which may be reused.

    Randomness, its uses, implications, theory and even philosophy is a massive subject - probably more than a single lifetime's worth.

    In fact, its hard to even describe what randomness actually is and how you can tell is something is random.

    For starters try Knuth Chapter 3, go on to Greg Chaitin's work, and cryptography. Then continue with the appropriate bits and pieces of quantum physics and then go back and fill in all the holes. (Don't neglect using cryptographic algorithms to generate random numbers - as well as their uses the other way around, the digits of Pi, the Riemann Zeta function and, well, a lot else) You'll have lots of fun and push your brain quite a bit.