Using Lasers To Generate Random Numbers Faster 149
Pranav writes "Using semiconductor lasers, scientists from Takushoku University, Saitama University, and NTT Corporation achieved random number rates of up to 1.7 gigabits per second, which is about 10 times higher than the second-best rate, produced using a physical phenomenon. Future work may center on devising laser schemes that can achieving rates as high as 10 Gbps."
Re:Obligatory joke (Score:5, Insightful)
stop reading DIGG
Re:Attention Slashdotters... (Score:3, Insightful)
Minor flamebait, maybe. But the thrust of the post is still worth reading. Austin Powers came out over 10 years ago. At some point (and that point was years ago), making references to it every time you see either the word shark or the word laser becomes old. It's really not funny.
Random generator needed in semi-conductors (Score:4, Insightful)
We really, really need more hardware random number generators (RNG's) within CPU's. I think this is one of the more important things for Intel and AMD to work on (VIA and Intel have already working hardware RNG's for x86 as far as I know, with Intel though it is only for an embedded processor).
Otherwise we will have to rely on "commodity" hardware to generate enough randomness to seed our pseudo-RNG's. And since a keyboard, harddisk and video cannot be trusted to be in a machine, and since using the NIC has too big a tie with the outside world, we are quickly running out of entropy sources. So a hardware RNG is definitely a very good idea.
That does not mean that these guys have struck gold. There are already fine RNG's available for use within CPU's. I don't know how secure their device is (what happens when it is underpowered/cooled etc) but speed is not really a problem right now. Of course, if it is easy to implement in current designs: why not?
Re:A Solution in Search of a Problem (Score:3, Insightful)
If, as poster states, (Score:4, Insightful)
But theory and practice are often vastly different. In a case like this, the information necessary to account for all the relevant initial conditions, and the calculations necessary to go from there to final result, are so vast as to make it ludicrous to even consider trying such a feat. Further, we don't even have the expertise to make such calculations even if we had such "perfect" information.
Think about it: even with classic physics, this is an awesome candidate for the "butterfly effect", in which miniscule differences in initial conditions could cause highly significant differences in the outcome.
See, you don't just need to know the mass of the ball, and its velocity, and such. You would have to know the exact size and mass of the bearings, and exactly how much lubricant had been applied. You would have to know the exact size and shape of the little fences between the numbers on the wheel (air resistance), and calculate Reynolds numbers for them. You would have to know how many people are around the wheel (if any) and how they are breathing. Is someone wearing perfume? Will that affect someone else's breathing? Even without people, did someone add a little bit extra glue at this particular spot, during the manufacturing process?
And so on.
It simply would not be a practical excercise. Even in controlled conditions, and without confounding factors, two well-lubed roulette wheels are almost certain to give you significantly different results, no matter how you try.
Theory is great, but reality trumps.
Re:A Solution in Search of a Problem (Score:3, Insightful)
That's all great until that paper comes out explaining the failings of the *P*RNG you've been using, invalidating years of research.
It might be a good idea to validate the results of the PRNG runs with some verifiably random data. Alternatively, you could inject entropy periodically in a computationally efficient fashion using the truly random data and improve things some.