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![]() | Text and/or other creative content from Hardware_random_number_generator was copied or moved into Draft:Comparison_of_hardware_random_number_generators. The former page's history now serves to provide attribution for that content in the latter page, and it must not be deleted as long as the latter page exists. |
http://freehg.org/u/olau/random/ there pornosite now —Preceding unsigned comment added by 94.45.73.56 ( talk) 18:38, 13 May 2011 (UTC) What
What's your problem with porn?
This article needs lots of work: it's full of half-truths. — Preceding unsigned comment added by Unknown user ( talk • contribs)
I quote the article in its current state: "Let the probability of a bit stream producing a 1 be 1/2 + e, where -1/2 < e < 1/2. Then e is the bias of the bitstream. If two bit uncorrelated bit streams with bias e are exclusive-or-ed together, then the bias of the result will be 2e^2."
In fact, the actual answer is -2e^2. For example, suppose you XOR two bitstreams together which have a bias of e=1/2. By the definition above, this means that both bitstreams produce ones every time. Since 1 XOR 1 = 0, the resulting bitstream would have a bias of -1/2, which is equal to -2e^2. You can prove the general case youself easily.
A while ago, I fixed the answer in this article to be -2e^2 but Matt Crypto reverted my change. He incorrectly cited the Piling-up Lemma. But the piling up lemma defines the bias differently: in the Piling-up lemma, the bias is e if the probability of the bitstream producing a 0 is 1/2+e, whereas this article defines the bias as e if the probabilitiy of produccing a 1 is 1/2+e.
I have corrected the article again. Hopefully Matt Crypto will read more carefully before reverting good changes in the future.
-- DavidGrayson 17:58, 19 February 2006 (UTC)
This section claims you can improve a near-random bit stream by XORing with the output of a Blum-Blum-Shub generator or a good stream cipher. This does make the stream, seen by a naive observer, have good statistical properties. But it is not cryptographically useful, since, in the absence of a secret seed for the auxiliary generator, an attacker can simply remove the effect of the auxiliary generator and take advantage of the known bias and correlation of the hardware generator.
I started to edit the article, casting the suggestion as a "proposed improvement", and explaining the above, but then I realized that a variant strategy would be to take a prefix of the hardware generated entropy and use it to seed the PRNG. This got too complicated to explain to Wikipedia quality in the time I have at hand. But I urge somebody to do something about this misinformation. Maybe the paragraph should just be deleted.
DMJ001 ( talk) 23:48, 9 January 2009 (UTC)
article contains the phrase:
I am not sure what number the author refers to by phi. Phi is somtimes used the represent the number called the 'devine ration' or 'golden section'. That number is not a trancendental number but a simple algebraic number.
I haven't edited, because I don't know if phi also refers to some well known trancendental number.
Hello. This is an interesting article. I have reworked the introduction. The main change has been to emphasize hardware rng in the intro; the previous rev had a lot of stuff about pseudo-rng's, which is interesting but a digression in the intro. Yes, it is necessary at some point to contrast the two, but putting that before a description of hardware rng's seems to be putting the cart before the horse. -- There is also a depreciative tone in the comparison with pseudo-rng's, to the effect that pseudo-rng's are bad because they're not really random. Well, that's a feature, not a bug; whether it's a problem depends on the purpose for which numbers are needed, and this article needn't, and shouldn't, take a stance one way or another. Happy editing, Wile E. Heresiarch 14:58, 31 Mar 2004 (UTC)
I made a pass at editing it. I moved the section about attacks on RNGs to the random number generator attack article. I also deleted the paragraph on using lossless compressing to improve entropy. I am not aware of anyone who does that and I'm not sure it would work on a stream that was close to random.
It could still be tighter. -- agr 21:41, 9 Dec 2004 (UTC)
Why isn't this located at True random-number generator? -- Smack 23:26, 22 Dec 2004 (UTC)
I've moved this back from "Hardware random-number generator"; usage seems to favour leaving out the hyphen. See this Google test. — Matt Crypto 19:04, 23 Dec 2004 (UTC)
I removed the annon. question "This also raises the question whether true randomness exists?" from the "Contrast with pseudo-random number generators" section. A theoretical basis for the existance of true randomness lies in the laws of Physics. See the articles and discussions on Quantum Mechanics and in particular the Bell test experiments. -- agr 11:34, 16 May 2005 (UTC)
At the quantum level, nature is not deterministic, and unlike dice and roulette wheels, which are strictly chaotic (deterministic but unpredictable on long timescales). However, it is a philosophical point whether the unrepeatable nature of quantum observations is due to true randomness or merely the fact we can't know all the initial conditions perfectly (due to the Heisenberg uncertainty principle). — Preceding unsigned comment added by 92.27.55.215 ( talk) 15:11, 26 April 2012 (UTC)
I hate to be a drive-by editor, but reading this page gives me enough of a headache to want to fix it. Most Wikipedia articles grow without bounds and this one is no exception.
I can't even tell if it's trying to be about hardware RNGs attached to a computer (that seems to be the intent and would be how I'd classify a hardware RNG) yet it has significant discussion of traditional random sources such as cards and dice. I hate to do a hack-n-slash job on the article, but that's what I'm sorely tempted to do.
The text about early uses of random number tables belongs somewhere but it has little to do with hardware RNGs. Ditto with the comment about Galton, applications of random numbers, etc. Is there a need for an article on the history and uses of random numbers? I could start one; it would be an interesting topic to research. There are several articles where snippets of random number history are randomly duplicated, and such an article would also give the "state of sin" people a place to get the von Neumann quote off their chest once and for all. (That joke's a funny-once... at best.)
The information about bias, software whitening, etc. seems a bit too detailed for this article. It's interesting (and perhaps useful) without a doubt, I just feel it's overkill for an overview-level article about hardware RNGs. Again, worthy of a place, just probably not here and certainly not at the level it's currently at. 12.103.251.203 01:15, 2 April 2006 (UTC)
The section on the physical basis for randomness had some negative information content, confusing quantum and thermal noise. I revised it, but it could use some more work; e.g., I didn't find a precise citation in the statistical mechanics articles for the statement I wanted, namely that every degree of freedom of a physical system at thermal equilibrium has a particular amount of randomness. All this information comes from an undergraduate physics education, but surely one can find articles that give a more complete discussion. -- Dylan Thurston 06:18, 10 April 2006 (UTC)
The section "Physical phenomena with quantum-random properties" should only contain Physical phenomena with quantum-random properties. Other phenomena should go into other sections, or the section "Physical phenomena with quantum-random properties" should be renamed. I can't tell them apart. I'd like to know, if my avalanche diode noise is theoretically unpredictable or not, but the current mess doesn't tell. I'll now split the section above the thermal phenomena and if any phenomenon is in the wrong section, someone hopefully will move it. It won't get any wronger this way. Darsie42 ( talk) 15:35, 16 September 2009 (UTC)
This was added 20 June 06. Seems rather questionable to me. any comments? ww 16:55, 20 June 2006 (UTC)
I've reworded the mention of this module in the article. It originally said that the module created real random numbers. Someone changed it to say it created pseudorandom numbers. I settled on saying that the writers claim it does real random. Can anyone say for sure? -- BillWeiss | Talk 06:36, 5 October 2006 (UTC)
An implementation that can be run on a fifth generation (Pentium class) or higher computer is provided by ComScire with their PCQNG software. The PCQNG uses the noise component or jitter produced by Phased Locked Loop circuits in the PC. This implementation is protected by one or more of the following Patents: U.S. Patent No(s).: 6,324,558; 6,763,364; 6,862,605; 7,096,242. See also Design Principles and Testing of PCQNG 2.0. -- 24.18.145.244 ( talk) 05:51, 13 July 2008 (UTC)
I don't know who first invented this first. At AT&T Bell Labs, I wrote a clock-drift RNG in April of 1984 that used SIGALRM to interrupt a "for (;;) count++" loop. This counted at about 1 MHz on the VAX 11/780, and I called it four times to accumulate a 32-bit number. In 1995, I wrote an improved version that used the millisecond Sleep() routine to sample QueryPerformanceCounter() in Windows, basically exploiting drift between the pentium CPU clock and the system time clock. DonPMitchell ( talk) 16:02, 18 June 2009 (UTC)
unsigned ML_TrueRandomUnsigned() { static LARGE_INTEGER nPerformanceCount; static unsigned n; BOOL bResult; int i; for (i = 0; i < 32; i += 8) { bResult = QueryPerformanceCounter(&nPerformanceCount); Sleep(1L); n = (n << 8) | (n >> 24); n ^= nPerformanceCount.LowPart; } return n; }
Oh, OK, I see the article includes a discussion about truerand in Cryptolib. That's what I was talking about above, it uses SIGALRM. I believe my performance-counter version above is superior to the one I wrote for CryptoLib. DonPMitchell ( talk) 02:48, 19 June 2009 (UTC)
This section contains material about Tippett's 1927 book of 41,600 digits taken from census records. That does not belong in this article, since it is not about hardware (i.e. physical) methods of generating random numbers.
In contrast, the RAND book of 1000000 random digits is appropriate, since those were generated by a physical means: "a random frequency pulse source, providing on the average about 100000 pulses per second, gated about once per second by a constant frequency pulse." And so is the stuff about the lottery technique.
I propose that the mention of Tippett's digits from the census tables be removed. If I don't see any objections in a month or so, I'll do it.
DMJ001 ( talk) 04:15, 10 January 2009 (UTC)
DMJ001 ( talk) 07:14, 13 January 2009 (UTC)
This whole section is not relevant to hardware random number generators. I propose in be reduced to just a couple of sentences to help the reader know the distinction between a hardware random number generator and a pseudo-random number generator. It might well lose its status as a section, and just be worked into the text of the introduction. DMJ001 ( talk) 04:04, 29 January 2009 (UTC)
The link in the external references section that says "An article on the history of generating random numbers" is broken. I tried to find the article at American Scientist, but was not successful. If anyone knows what this is supposed to point to, please fix the link. DMJ001 ( talk) 04:18, 29 January 2009 (UTC)
I suggest merging the section one-time pad#Achieving Shannon security, which appears to talk about hardware random number generators, into the hardware random number generator article. -- 68.0.124.33 ( talk) 03:01, 27 March 2009 (UTC)
I agree with the previous. Although the One-Time Pad CAN be implemented in hardware, it can also be implemented in software. It could also be implemented by hand! The one-time pad is NOT synonymous to Hardware Random Number Generator. Do not merge. —Preceding unsigned comment added by 66.29.182.58 ( talk) 04:42, 2 May 2009 (UTC)
I concur. Do not merge. Two articles can talk about similar things. Sukiari ( talk) 00:20, 22 October 2009 (UTC)
Would it be acceptable to put information about automatic dice rolling machines into this article? Fully referenced of course. Colincbn ( talk) 12:14, 13 November 2009 (UTC)
I have removed the following statement from the article because it is evidently incorrect:
The term [shot noise] is a clipping of the term " Schottky noise," referring to the scientist who first published regarding this phenomenon.
There is no source for the statement on clipping, the main article Shot noise doesn't mention it, and moreover the name IS inspired on behavior of real shot (pellet) ammunition. That is evident from the German term, de:Schrotrauschen, which directly translates to "shot noise" - "Schrot" means "shot" (the ammunition type.) -- Arny ( talk) 16:30, 5 November 2015 (UTC)
The article describes a "simple algorithm": "John von Neumann invented a simple algorithm to fix simple bias and reduce correlation. It considers two bits at a time (non-overlapping), taking one of three actions: when two successive bits are equal, they are discarded; a sequence of 1,0 becomes a 1; and a sequence of 0,1 becomes a zero. It thus represents a falling edge with a 1, and a rising edge with a 0. This eliminates simple bias, and is easy to implement as a computer program or in digital logic. This technique works no matter how the bits have been generated." What is being described always produces a bit stream 1 0 1 0 1 0 etc. ... which is not very random. What is missing from the description? A5 ( talk) 20:54, 10 June 2019 (UTC)
A _hardware_ random number generator can be either true or pseudo-random. For example, an LFSR implemented on an FPGA is both a hardware and pseudo-random number generator. If the page is about true random number generators, as it seems to be, it should be titled "True Random Number Generator." 129.31.224.110 ( talk) 17:01, 12 July 2020 (UTC)
A discussion is taking place to address the redirect
QRNG. The discussion will occur at
Wikipedia:Redirects for discussion/Log/2021 December 8#QRNG until a consensus is reached, and readers of this page are welcome to contribute to the discussion.
Chumpih. (
talk)
08:02, 8 December 2021 (UTC)
This article is about a particular device that is used in real-life applications. A myriad of physical processes exist that exhibit stochastic behavior; many easily observed macroscopic phenomena are not deterministic on a sufficiently long timescale (cf. chaos theory), for example, the weather is not really predictable. In my humble opinion, we should not list these processes here just because they exist, unless they are actually used for the purpose, so the sources for this article should always mention actual implementations that are used (or were being used) to actually generate random numbers for some application, and not just describe the research on randomness of some process. Same approach should be taken for the quantum phenomena. For example, it is hard to imagine Geiger counters placed into electronic systems at a time when a tiny piece of silicon, many orders of magnitude smaller and cheaper, can deliver the same results. Dimawik ( talk) 22:36, 6 August 2023 (UTC)
I have removed a couple of sections explaining how to generate entropy without using dedicated hardware. Since this article is about dedicated hardware, the sections were out of scope (and practically unsourced). Feel free to voice objections, but IMHO these snippets of text belong to a completely different article, non-physical nondeterministic random bit generator that is yet to be written. Dimawik ( talk) 03:02, 10 September 2023 (UTC)
The section "Dealing with bias" listed old algorithms that can improve some properties of the random stream. The problem with this (unsourced) section was in the fact that these algorithm would not simplify the reasoning about the randomness (and might actually hurt during the validation process of an actual device). The vetted "conditioning" in, say, SP800-90B is very different. I decided to simply remove this text that touches the subject of this article only tangentially anyhow; if someone wants to restore text, it should be moved to the "History" section and very carefully aligned with modern sources (we cannot bluntly state, for example, that von Neumann debiasing is simply OK, and any source stating that it is, is actually obsolete). The need for conditioning is described in the lead. Dimawik ( talk) 06:44, 11 September 2023 (UTC)
Does the RFC 4086 define any actual tests to be performed? If not, mention if it IMHO it should be removed from the section "Perfprmance test". Dimawik ( talk) 17:03, 24 December 2023 (UTC)
![]() | This article is rated C-class on Wikipedia's
content assessment scale. It is of interest to the following WikiProjects: | |||||||||||||
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![]() | Text and/or other creative content from Hardware_random_number_generator was copied or moved into Draft:Comparison_of_hardware_random_number_generators. The former page's history now serves to provide attribution for that content in the latter page, and it must not be deleted as long as the latter page exists. |
http://freehg.org/u/olau/random/ there pornosite now —Preceding unsigned comment added by 94.45.73.56 ( talk) 18:38, 13 May 2011 (UTC) What
What's your problem with porn?
This article needs lots of work: it's full of half-truths. — Preceding unsigned comment added by Unknown user ( talk • contribs)
I quote the article in its current state: "Let the probability of a bit stream producing a 1 be 1/2 + e, where -1/2 < e < 1/2. Then e is the bias of the bitstream. If two bit uncorrelated bit streams with bias e are exclusive-or-ed together, then the bias of the result will be 2e^2."
In fact, the actual answer is -2e^2. For example, suppose you XOR two bitstreams together which have a bias of e=1/2. By the definition above, this means that both bitstreams produce ones every time. Since 1 XOR 1 = 0, the resulting bitstream would have a bias of -1/2, which is equal to -2e^2. You can prove the general case youself easily.
A while ago, I fixed the answer in this article to be -2e^2 but Matt Crypto reverted my change. He incorrectly cited the Piling-up Lemma. But the piling up lemma defines the bias differently: in the Piling-up lemma, the bias is e if the probability of the bitstream producing a 0 is 1/2+e, whereas this article defines the bias as e if the probabilitiy of produccing a 1 is 1/2+e.
I have corrected the article again. Hopefully Matt Crypto will read more carefully before reverting good changes in the future.
-- DavidGrayson 17:58, 19 February 2006 (UTC)
This section claims you can improve a near-random bit stream by XORing with the output of a Blum-Blum-Shub generator or a good stream cipher. This does make the stream, seen by a naive observer, have good statistical properties. But it is not cryptographically useful, since, in the absence of a secret seed for the auxiliary generator, an attacker can simply remove the effect of the auxiliary generator and take advantage of the known bias and correlation of the hardware generator.
I started to edit the article, casting the suggestion as a "proposed improvement", and explaining the above, but then I realized that a variant strategy would be to take a prefix of the hardware generated entropy and use it to seed the PRNG. This got too complicated to explain to Wikipedia quality in the time I have at hand. But I urge somebody to do something about this misinformation. Maybe the paragraph should just be deleted.
DMJ001 ( talk) 23:48, 9 January 2009 (UTC)
article contains the phrase:
I am not sure what number the author refers to by phi. Phi is somtimes used the represent the number called the 'devine ration' or 'golden section'. That number is not a trancendental number but a simple algebraic number.
I haven't edited, because I don't know if phi also refers to some well known trancendental number.
Hello. This is an interesting article. I have reworked the introduction. The main change has been to emphasize hardware rng in the intro; the previous rev had a lot of stuff about pseudo-rng's, which is interesting but a digression in the intro. Yes, it is necessary at some point to contrast the two, but putting that before a description of hardware rng's seems to be putting the cart before the horse. -- There is also a depreciative tone in the comparison with pseudo-rng's, to the effect that pseudo-rng's are bad because they're not really random. Well, that's a feature, not a bug; whether it's a problem depends on the purpose for which numbers are needed, and this article needn't, and shouldn't, take a stance one way or another. Happy editing, Wile E. Heresiarch 14:58, 31 Mar 2004 (UTC)
I made a pass at editing it. I moved the section about attacks on RNGs to the random number generator attack article. I also deleted the paragraph on using lossless compressing to improve entropy. I am not aware of anyone who does that and I'm not sure it would work on a stream that was close to random.
It could still be tighter. -- agr 21:41, 9 Dec 2004 (UTC)
Why isn't this located at True random-number generator? -- Smack 23:26, 22 Dec 2004 (UTC)
I've moved this back from "Hardware random-number generator"; usage seems to favour leaving out the hyphen. See this Google test. — Matt Crypto 19:04, 23 Dec 2004 (UTC)
I removed the annon. question "This also raises the question whether true randomness exists?" from the "Contrast with pseudo-random number generators" section. A theoretical basis for the existance of true randomness lies in the laws of Physics. See the articles and discussions on Quantum Mechanics and in particular the Bell test experiments. -- agr 11:34, 16 May 2005 (UTC)
At the quantum level, nature is not deterministic, and unlike dice and roulette wheels, which are strictly chaotic (deterministic but unpredictable on long timescales). However, it is a philosophical point whether the unrepeatable nature of quantum observations is due to true randomness or merely the fact we can't know all the initial conditions perfectly (due to the Heisenberg uncertainty principle). — Preceding unsigned comment added by 92.27.55.215 ( talk) 15:11, 26 April 2012 (UTC)
I hate to be a drive-by editor, but reading this page gives me enough of a headache to want to fix it. Most Wikipedia articles grow without bounds and this one is no exception.
I can't even tell if it's trying to be about hardware RNGs attached to a computer (that seems to be the intent and would be how I'd classify a hardware RNG) yet it has significant discussion of traditional random sources such as cards and dice. I hate to do a hack-n-slash job on the article, but that's what I'm sorely tempted to do.
The text about early uses of random number tables belongs somewhere but it has little to do with hardware RNGs. Ditto with the comment about Galton, applications of random numbers, etc. Is there a need for an article on the history and uses of random numbers? I could start one; it would be an interesting topic to research. There are several articles where snippets of random number history are randomly duplicated, and such an article would also give the "state of sin" people a place to get the von Neumann quote off their chest once and for all. (That joke's a funny-once... at best.)
The information about bias, software whitening, etc. seems a bit too detailed for this article. It's interesting (and perhaps useful) without a doubt, I just feel it's overkill for an overview-level article about hardware RNGs. Again, worthy of a place, just probably not here and certainly not at the level it's currently at. 12.103.251.203 01:15, 2 April 2006 (UTC)
The section on the physical basis for randomness had some negative information content, confusing quantum and thermal noise. I revised it, but it could use some more work; e.g., I didn't find a precise citation in the statistical mechanics articles for the statement I wanted, namely that every degree of freedom of a physical system at thermal equilibrium has a particular amount of randomness. All this information comes from an undergraduate physics education, but surely one can find articles that give a more complete discussion. -- Dylan Thurston 06:18, 10 April 2006 (UTC)
The section "Physical phenomena with quantum-random properties" should only contain Physical phenomena with quantum-random properties. Other phenomena should go into other sections, or the section "Physical phenomena with quantum-random properties" should be renamed. I can't tell them apart. I'd like to know, if my avalanche diode noise is theoretically unpredictable or not, but the current mess doesn't tell. I'll now split the section above the thermal phenomena and if any phenomenon is in the wrong section, someone hopefully will move it. It won't get any wronger this way. Darsie42 ( talk) 15:35, 16 September 2009 (UTC)
This was added 20 June 06. Seems rather questionable to me. any comments? ww 16:55, 20 June 2006 (UTC)
I've reworded the mention of this module in the article. It originally said that the module created real random numbers. Someone changed it to say it created pseudorandom numbers. I settled on saying that the writers claim it does real random. Can anyone say for sure? -- BillWeiss | Talk 06:36, 5 October 2006 (UTC)
An implementation that can be run on a fifth generation (Pentium class) or higher computer is provided by ComScire with their PCQNG software. The PCQNG uses the noise component or jitter produced by Phased Locked Loop circuits in the PC. This implementation is protected by one or more of the following Patents: U.S. Patent No(s).: 6,324,558; 6,763,364; 6,862,605; 7,096,242. See also Design Principles and Testing of PCQNG 2.0. -- 24.18.145.244 ( talk) 05:51, 13 July 2008 (UTC)
I don't know who first invented this first. At AT&T Bell Labs, I wrote a clock-drift RNG in April of 1984 that used SIGALRM to interrupt a "for (;;) count++" loop. This counted at about 1 MHz on the VAX 11/780, and I called it four times to accumulate a 32-bit number. In 1995, I wrote an improved version that used the millisecond Sleep() routine to sample QueryPerformanceCounter() in Windows, basically exploiting drift between the pentium CPU clock and the system time clock. DonPMitchell ( talk) 16:02, 18 June 2009 (UTC)
unsigned ML_TrueRandomUnsigned() { static LARGE_INTEGER nPerformanceCount; static unsigned n; BOOL bResult; int i; for (i = 0; i < 32; i += 8) { bResult = QueryPerformanceCounter(&nPerformanceCount); Sleep(1L); n = (n << 8) | (n >> 24); n ^= nPerformanceCount.LowPart; } return n; }
Oh, OK, I see the article includes a discussion about truerand in Cryptolib. That's what I was talking about above, it uses SIGALRM. I believe my performance-counter version above is superior to the one I wrote for CryptoLib. DonPMitchell ( talk) 02:48, 19 June 2009 (UTC)
This section contains material about Tippett's 1927 book of 41,600 digits taken from census records. That does not belong in this article, since it is not about hardware (i.e. physical) methods of generating random numbers.
In contrast, the RAND book of 1000000 random digits is appropriate, since those were generated by a physical means: "a random frequency pulse source, providing on the average about 100000 pulses per second, gated about once per second by a constant frequency pulse." And so is the stuff about the lottery technique.
I propose that the mention of Tippett's digits from the census tables be removed. If I don't see any objections in a month or so, I'll do it.
DMJ001 ( talk) 04:15, 10 January 2009 (UTC)
DMJ001 ( talk) 07:14, 13 January 2009 (UTC)
This whole section is not relevant to hardware random number generators. I propose in be reduced to just a couple of sentences to help the reader know the distinction between a hardware random number generator and a pseudo-random number generator. It might well lose its status as a section, and just be worked into the text of the introduction. DMJ001 ( talk) 04:04, 29 January 2009 (UTC)
The link in the external references section that says "An article on the history of generating random numbers" is broken. I tried to find the article at American Scientist, but was not successful. If anyone knows what this is supposed to point to, please fix the link. DMJ001 ( talk) 04:18, 29 January 2009 (UTC)
I suggest merging the section one-time pad#Achieving Shannon security, which appears to talk about hardware random number generators, into the hardware random number generator article. -- 68.0.124.33 ( talk) 03:01, 27 March 2009 (UTC)
I agree with the previous. Although the One-Time Pad CAN be implemented in hardware, it can also be implemented in software. It could also be implemented by hand! The one-time pad is NOT synonymous to Hardware Random Number Generator. Do not merge. —Preceding unsigned comment added by 66.29.182.58 ( talk) 04:42, 2 May 2009 (UTC)
I concur. Do not merge. Two articles can talk about similar things. Sukiari ( talk) 00:20, 22 October 2009 (UTC)
Would it be acceptable to put information about automatic dice rolling machines into this article? Fully referenced of course. Colincbn ( talk) 12:14, 13 November 2009 (UTC)
I have removed the following statement from the article because it is evidently incorrect:
The term [shot noise] is a clipping of the term " Schottky noise," referring to the scientist who first published regarding this phenomenon.
There is no source for the statement on clipping, the main article Shot noise doesn't mention it, and moreover the name IS inspired on behavior of real shot (pellet) ammunition. That is evident from the German term, de:Schrotrauschen, which directly translates to "shot noise" - "Schrot" means "shot" (the ammunition type.) -- Arny ( talk) 16:30, 5 November 2015 (UTC)
The article describes a "simple algorithm": "John von Neumann invented a simple algorithm to fix simple bias and reduce correlation. It considers two bits at a time (non-overlapping), taking one of three actions: when two successive bits are equal, they are discarded; a sequence of 1,0 becomes a 1; and a sequence of 0,1 becomes a zero. It thus represents a falling edge with a 1, and a rising edge with a 0. This eliminates simple bias, and is easy to implement as a computer program or in digital logic. This technique works no matter how the bits have been generated." What is being described always produces a bit stream 1 0 1 0 1 0 etc. ... which is not very random. What is missing from the description? A5 ( talk) 20:54, 10 June 2019 (UTC)
A _hardware_ random number generator can be either true or pseudo-random. For example, an LFSR implemented on an FPGA is both a hardware and pseudo-random number generator. If the page is about true random number generators, as it seems to be, it should be titled "True Random Number Generator." 129.31.224.110 ( talk) 17:01, 12 July 2020 (UTC)
A discussion is taking place to address the redirect
QRNG. The discussion will occur at
Wikipedia:Redirects for discussion/Log/2021 December 8#QRNG until a consensus is reached, and readers of this page are welcome to contribute to the discussion.
Chumpih. (
talk)
08:02, 8 December 2021 (UTC)
This article is about a particular device that is used in real-life applications. A myriad of physical processes exist that exhibit stochastic behavior; many easily observed macroscopic phenomena are not deterministic on a sufficiently long timescale (cf. chaos theory), for example, the weather is not really predictable. In my humble opinion, we should not list these processes here just because they exist, unless they are actually used for the purpose, so the sources for this article should always mention actual implementations that are used (or were being used) to actually generate random numbers for some application, and not just describe the research on randomness of some process. Same approach should be taken for the quantum phenomena. For example, it is hard to imagine Geiger counters placed into electronic systems at a time when a tiny piece of silicon, many orders of magnitude smaller and cheaper, can deliver the same results. Dimawik ( talk) 22:36, 6 August 2023 (UTC)
I have removed a couple of sections explaining how to generate entropy without using dedicated hardware. Since this article is about dedicated hardware, the sections were out of scope (and practically unsourced). Feel free to voice objections, but IMHO these snippets of text belong to a completely different article, non-physical nondeterministic random bit generator that is yet to be written. Dimawik ( talk) 03:02, 10 September 2023 (UTC)
The section "Dealing with bias" listed old algorithms that can improve some properties of the random stream. The problem with this (unsourced) section was in the fact that these algorithm would not simplify the reasoning about the randomness (and might actually hurt during the validation process of an actual device). The vetted "conditioning" in, say, SP800-90B is very different. I decided to simply remove this text that touches the subject of this article only tangentially anyhow; if someone wants to restore text, it should be moved to the "History" section and very carefully aligned with modern sources (we cannot bluntly state, for example, that von Neumann debiasing is simply OK, and any source stating that it is, is actually obsolete). The need for conditioning is described in the lead. Dimawik ( talk) 06:44, 11 September 2023 (UTC)
Does the RFC 4086 define any actual tests to be performed? If not, mention if it IMHO it should be removed from the section "Perfprmance test". Dimawik ( talk) 17:03, 24 December 2023 (UTC)