<p>Yes, quantum computation allows the generation of truly random numbers, and the operations necessary are so simple companies like id Quantique are already selling quantum random number generators. It is even possible to generate random numbers in a way that proves to the person generating them that they are random (via a violation of Bell's inequality) but this does need a short seed for the proof to be complete (though the numbers are random anyway). Unfortunately commercial systems are not that sophisticated just yet, and so produce random numbers in a way that is difficult to test.</p>

CC BY-SA 3.0
2013-02-06T03:58:14.050Z
Is it possible/easy to make your first sentence mathematically precise? It doesn't seem obvious to me how to formalize the notion of ``true'' randomness here (or anywhere!). I am picturing a black box that pops out numbers, where $\Pr[\text{next number}] = \Pr[\text{next number} | X]$ where $X$ is anything outside the box.
usul
CC BY-SA 3.0
2013-02-06T04:57:03.167Z
@RickyDemer I believe Joe's referring to this paper: http://arxiv.org/abs/0911.3427 .
Yonatan N
CC BY-SA 3.0
2013-02-06T06:30:00.410Z
@RickyDemer, check these recent article by [Umesh Vazirani](http://www.cs.berkeley.edu/~vazirani/): "[Certifiable Quantum Dice](http://rsta.royalsocietypublishing.org/content/370/1971/3432.full.pdf+html)", "[Certifiable Quantum Dice: or, true random number generation secure against quantum adversaries](http://www.cs.berkeley.edu/~vazirani/pubs/dice0.pdf)"
Kaveh
CC BY-SA 3.0
2013-02-06T07:00:54.123Z
You can also check Umesh's talks on the topic, e.g. this one at Berkeley: [Certifiable Quantum Dice](http://www.youtube.com/watch?v=jcsqsb_7kPg).
Kaveh
CC BY-SA 3.0
2013-02-06T09:01:54.993Z
@usul: Consider a device which generates random numbers which has an internal state $\rho$, and the environment is in state $\epsilon$. Then for anything which can reasonably be called a random number generator, which has possible outcomes $x_i$ we have $P(x_i) \notin \[0,1\]$, since otherwise there is no randomness at all. For a pseudo random number generator, this equation is satisfied, but $P(x_i|\rho)\in \[0,1\]$. Hardware random number generators, such as in the other answer satisfy a stronger condition: $P(x_i|\rho)\notin \[0,1\]$.
Joe Fitzsimons
CC BY-SA 3.0
2013-02-06T09:04:29.893Z
(continued) However, these are generally based on processes which are deterministic, even though they outcome is not dictated solely by the state of the device, and so $P(x_i|\rho,\epsilon) \in \[0,1\]$. Quantum random number generators operate via a process which is inherently stochastic, and hence satisfy the strongest possible such definition of randomness: $P(x_i|\rho,\epsilon)\notin \[0,1\]$.
Joe Fitzsimons
CC BY-SA 3.0
2013-02-06T09:42:27.190Z
@JoeFitzsimons - Thanks! That is very clear!
usul
CC BY-SA 3.0
2014-10-07T14:24:04.090Z
@JoeFitzsimons. Nice answer. One comment: I think the answer to the OP's question depends partially on how well the quantum RNG devices can be trusted. Could you specify if you are making certain device-independence assumptions in your answer?
Juan Bermejo Vega
CC BY-SA 3.0
2014-10-09T18:42:53.943Z
@JuanBermejoVega: The commercial systems (i.e. id Quantique's RNG) are not yet at the stage of being able to do device independent randomness amplification, but it is something that is possible. There have been a bunch of papers in recent years showing how to extract more and more randomness from a short random seed in an entirely device independent manner. However, ultimately you do need a short seed to kick off the whole process, so you can only really hope to expand the randomness rather than generating it from nothing (at least if you want device independence).
Joe Fitzsimons
CC BY-SA 3.0
2013-02-06T02:36:36.780Z
2013-02-06T02:36:36.780Z
Joe Fitzsimons
<p>Besides what tylerl says, there's another reason why quantum computers aren't necessary for this.  The main difficulty today with implementing quantum computers is to make it be able to do computations on many qubits together.  We already have working quantum computers with only one or a few qubits.  Those simple systems are enough to produce true randomness of the kind you have requested.  In fact, the technology in the quantum cryptography hardware that are already commercially available is enough to produce random bits. </p>

CC BY-SA 3.0
2015-02-06T12:45:12.510Z
2015-02-06T12:45:12.510Z
Zsbán Ambrus
<p>Actually, today's computers <em>can</em> generate truly random data on their own, and many in fact do. The random data is produced as a byproduct of the physics of the components, not as the product of a given algorithm, so it necessarily has to be implemented in hardware. But the hardware is readily available. </p>

<p>The popular <a href="http://en.wikipedia.org/wiki/Trusted_Platform_Module" rel="nofollow">TPM</a> chip, for example, typically has an embedded <a href="http://en.wikipedia.org/wiki/TRNG" rel="nofollow">TRNG</a>, as do many security-oriented peripherals, such as some <a href="http://www.yubico.com/products/yubihsm/" rel="nofollow">authentication tokens</a>. </p>

<p>The actual mechanism used to harvest sources of entropy varies by component, but a simple-to-understand mechanism is the analysis of <a href="http://en.wikipedia.org/wiki/Noise_%28electronics%29#Avalanche_noise" rel="nofollow">noise generated</a> at the <a href="http://en.wikipedia.org/wiki/Avalanche_breakdown" rel="nofollow">avalanche breakdown</a> of a P-N junction of a diode or transistor. The noise from such a cascade is actually the amplification of the random movement of electrons at the junction - essentially amplifying the randomness of quantum mechanics to the level where it can be read by traditional electronics.</p>

<p>Obviously this isn't the only mechanism you can use to harvest randomness in today's computers, but it's an easy one to understand. In fact it's worth pointing out that the Intel's recent <a href="http://en.wikipedia.org/wiki/Ivy_Bridge_%28microarchitecture%29" rel="nofollow">Ivy Bridge</a> architecture introduced a new instruction: <strong>RDRAND</strong>, which yields the output of an on-chip TRNG. IEEE Spectrum has a <a href="http://spectrum.ieee.org/computing/hardware/behind-intels-new-randomnumber-generator/0" rel="nofollow">detailed write-up</a> of how it works.</p>

CC BY-SA 3.0
2013-02-06T05:33:38.180Z
As with the other answer, a definition of "truly random" would help me understand what this means a lot better! I would guess some might not classify these sources as "truly random" because someone might be able to guess the bits better than 50-50 if they know something about, say, the operations the CPU is doing or the current temperature in the transistor. Is that correct?
usul
CC BY-SA 3.0
2013-02-06T05:47:57.247Z
@usul Nope. With thermally-sensitive mechanisms you might be able to *affect* the randomness by cooling the device beyond its normal operating range such that it biases the output. But modifying the device to change its output is not the same thing as *predicting* its output. A simple way to protect against this type of attack is simply shut off the RNG when it is outside its normal operating temperature. And many RNGs are not temperature-sensitive; it's just straight quantum-random noise.
tylerl
CC BY-SA 3.0
2013-02-06T06:02:43.937Z
Also, note that there are two useful principles of randomness: unpredictably and normal distribution. Brownian noise is by definition random, but the distribution follows a strong bias toward lower frequencies. You want your random data to be "white noise" not "brown noise". The interesting thing is that you can algorithmically normalize the bit distribution: as long as you have a decent source of randomness to start with, your output will be random as well. Just pass your input data through a cryptographic algorithm (e.g. hashing or encryption) that has the output profile you want.
tylerl
CC BY-SA 3.0
2013-02-06T06:50:02.960Z
I think what Joe refers to is not just statistical test but *proofs* for really being random. The devices that you mention can seem to be unpredictable but it is not the same as proving they are truly random. See the problems section of the Wikipedia article that you have linked to. What Joe is referring to is a method to certify that numbers generated by a device (without knowing how it works internally) are random, i.e. a *user* can verify that the numbers generated by the device are really random without caring about how the device works.
Kaveh
CC BY-SA 3.0
2013-02-06T07:14:07.280Z
@Kaveh Bell's theorem mentioned by Joe states that **No physical theory of local hidden variables can ever reproduce all of the predictions of quantum mechanics.**, or as an extension: *true randomness is derived from quantum mechanics alone*. **All** true RNGs ultimately use quantum mechanics as their source of entropy; all that's left for the details is how to amplify that signal to a level that is detectable. The solution Joe mentioned is not fundamentally different; same rules, same caveats. And it has nothing at all to do with actual quantum computing (except for the word "quantum").
tylerl
CC BY-SA 3.0
2013-02-06T07:21:54.253Z
As Joe wrote: "*Unfortunately commercial systems are not that sophisticated just yet, and so produce random numbers in a way **that is difficult to test***". I think the method Joe is referring to is different, i.e. it is quite simple to test if the generated numbers are really random. See [this article](http://arxiv.org/abs/1111.6054) for more details.
Kaveh
CC BY-SA 3.0
2013-02-07T06:31:52.957Z
I guess I should jump in here and explain what I meant. Quantum mechanics allows for true randomness in the sense that the outcome of certain experiments is independent of the prior state of both the system and the environment. Most of the ways people currently generate randomness does not really come from this, but rather from either classical chaotic systems (where some minor uncontrolled imprecission in initial preparation leads to vastly different outcomes) or by extracting noise from the environment.
Joe Fitzsimons
CC BY-SA 3.0
2013-02-07T06:32:32.863Z
(Continued) The problem with these systems is illustrated nicely by Dilbert, here: http://dilbert.com/strips/comic/2001-10-25/ But while quantum mechanics can provide the same results, and may underly the randomness captured from the environment in other systems, there are certain quantum protocols, such as those pointed to by @Kaveh and YonatanN, which go further and actually provide an interactive protocol which proves randomness. This is something which is totally impossible classically, and which can't be mimiced by systems which extract noise from the environment alone.
Joe Fitzsimons
CC BY-SA 3.0
2015-02-06T05:49:28.620Z
As noted by one anonymous editor, the output of RDRAND is post-processed through a whitening mechanism. This does not set it apart from other TRNGS; whitening is a necessary aspect of turning any truly random bit generator into something cryptographically usable.
tylerl
CC BY-SA 3.0
2013-02-06T05:14:54.390Z
2015-02-06T05:28:18.383Z
2015-02-06T05:28:18.383Z
tylerl
<p>Obviously, regular computers can't generate random numbers on their own, since they're inherently systematic machines. Would quantum computing be able to run a true RNG without a seed based off user input (or any other external variables)?</p>

CC BY-SA 3.0
2013-02-05T20:45:14.603Z
Are you talking about usual models of quantum computing (such as quantum circuits and quantum Turing machines) or physical implementations of quantum computers?
Tsuyoshi Ito
CC BY-SA 3.0
2013-02-05T20:46:42.210Z
In which sense is this question a [soft question](http://cstheory.stackexchange.com/questions/tagged/soft-question)?
Tsuyoshi Ito
CC BY-SA 3.0
2013-02-05T21:12:18.310Z
@TsuyoshiIto I'm talking about the physical implementations, although the usual models sound interesting as well.
Jules
CC BY-SA 3.0
2013-02-05T21:17:02.613Z
We do not know how scalable quantum computers will look like, and therefore the question is in the realm of future prediction or fortune telling.  But my guess is that quantum computers will be controlled by classical computers, and that it is plausible that these classical computers require some randomness.
Tsuyoshi Ito
CC BY-SA 3.0
2013-02-06T07:23:59.540Z
Stupid question: isn't plain old radioactive decay the canonical source of true randomness? I mean, yeah, decay happens due to quantum *physics*, but it's so simple it hardly seems like quantum *computation*.
Neel Krishnaswami
CC BY-SA 3.0
2013-02-06T09:11:04.443Z
@NeelKrishnaswami: Yes, but actually you can do a little better. Radioactive decay can actually be triggered deliberately, so it doesn't necessarily serve as a way to generate randomness in a sufficiently adversarial setting. The recent work on randomness certified by Bell's theorem actually gives you something stronger. You have a protocol which treats the devices as black boxes, but still convinces you the string is random (without you ever needing to open the box).The way this works is to generate correlations which are not possible by classical pre-agreement,and which hence must be random.
Joe Fitzsimons
CC BY-SA 3.0
2013-02-06T15:00:15.527Z
Note that at least one of the very first commercially available computers included a (true) random number generator.  (According to George Dyson in _Turing's Cathedral_.)  So that "obviously" in your leading sentence seems misplaced.
András Salamon
CC BY-SA 3.0
2014-10-02T04:22:01.973Z
The only true possibility of true randomness will be with quantum because as far as we can tell it is random but even it has a pattern. Using things like noise and temperature is indeed probably the best way we have to date to produce random numbers but even it is still NOT true randomness. It may be nearly impossible to predict but that doesn't make it random. I believe the 2nd answer is far more correct then the 3rd. It is a theory that randomness may not even exist at all. It isn't a bad idea to keep the mind open on this.. Here is a video i recommend on this:
https://www.youtube.com/watch?
user2455808
CC BY-SA 3.0
2014-10-07T14:20:13.287Z
Why is this question so downvoted? It looks in scope to me. Random number generation is a hot topic in quantum information presently; ditto for randomness amplification and randomness extraction. The ability of quantum computers to generate true randomness (in a device independent fashion) is, as far as I know, still not 100% understood and is a subject of active research.
Juan Bermejo Vega
CC BY-SA 3.0
2015-02-07T19:00:36.307Z
agreed this seems on topic, maybe someone can reask in a way that is "less questionable" (controversial). reminds me of a recent paper [One-way-ness in the input-saving (Turing) machine / de Castro](http://www.alice.cnptia.embrapa.br/bitstream/doc/994523/1/onewaness.pdf)
vzn
CC BY-SA 4.0
2019-05-18T21:42:35.593Z
It's a popular myth that what makes quantum "special" is true randomness. What makes it special is *coherence*, namely the super-additive superposition of numerous amplitudes onto the desired outcome. To what extent it is possible to design an algorithm that efficiently lands on the solution depends on the problem.
Kevin Kostlan
<quantum-computing><randomness>
Will quantum computing pave the way for native, true RNGs?
Jules
# Will quantum computing pave the way for native, true RNGs?

(Asked by: username_0 on 2013-02-05)

Obviously, regular computers can't generate random numbers on their own, since they're inherently systematic machines. Would quantum computing be able to run a true RNG without a seed based off user input (or any other external variables)?

**Tags:** quantum-computing, randomness
> **Comments:**
> **username_1**: Are you talking about usual models of quantum computing (such as quantum circuits and quantum Turing machines) or physical implementations of quantum computers?  
> **username_1**: In which sense is this question a [soft question](http://cstheory.stackexchange.com/questions/tagged/soft-question)?  
> **username_0**: @TsuyoshiIto I'm talking about the physical implementations, although the usual models sound interesting as well.  
> **username_1**: We do not know how scalable quantum computers will look like, and therefore the question is in the realm of future prediction or fortune telling.  But my guess is that quantum computers will be controlled by classical computers, and that it is plausible that these classical computers require some randomness.  
> **username_2**: Stupid question: isn't plain old radioactive decay the canonical source of true randomness? I mean, yeah, decay happens due to quantum *physics*, but it's so simple it hardly seems like quantum *computation*.  
> **username_3**: @NeelKrishnaswami: Yes, but actually you can do a little better. Radioactive decay can actually be triggered deliberately, so it doesn't necessarily serve as a way to generate randomness in a sufficiently adversarial setting. The recent work on randomness certified by Bell's theorem actually gives you something stronger. You have a protocol which treats the devices as black boxes, but still convinces you the string is random (without you ever needing to open the box).The way this works is to generate correlations which are not possible by classical pre-agreement,and which hence must be random.  
> **username_4**: Note that at least one of the very first commercially available computers included a (true) random number generator.  (According to George Dyson in _Turing's Cathedral_.)  So that "obviously" in your leading sentence seems misplaced.  
> **username_5**: The only true possibility of true randomness will be with quantum because as far as we can tell it is random but even it has a pattern. Using things like noise and temperature is indeed probably the best way we have to date to produce random numbers but even it is still NOT true randomness. It may be nearly impossible to predict but that doesn't make it random. I believe the 2nd answer is far more correct then the 3rd. It is a theory that randomness may not even exist at all. It isn't a bad idea to keep the mind open on this.. Here is a video i recommend on this: https://www.youtube.com/watch?  
> **username_6**: Why is this question so downvoted? It looks in scope to me. Random number generation is a hot topic in quantum information presently; ditto for randomness amplification and randomness extraction. The ability of quantum computers to generate true randomness (in a device independent fashion) is, as far as I know, still not 100% understood and is a subject of active research.  
> **username_7**: agreed this seems on topic, maybe someone can reask in a way that is "less questionable" (controversial). reminds me of a recent paper [One-way-ness in the input-saving (Turing) machine / de Castro](http://www.alice.cnptia.embrapa.br/bitstream/doc/994523/1/onewaness.pdf)  
> **username_8**: It's a popular myth that what makes quantum "special" is true randomness. What makes it special is *coherence*, namely the super-additive superposition of numerous amplitudes onto the desired outcome. To what extent it is possible to design an algorithm that efficiently lands on the solution depends on the problem.  

---

## 3 answers

### Answer by username_13 on 2013-02-06. Score: 14 | Accepted answer

Actually, today's computers *can* generate truly random data on their own, and many in fact do. The random data is produced as a byproduct of the physics of the components, not as the product of a given algorithm, so it necessarily has to be implemented in hardware. But the hardware is readily available.

The popular [TPM](http://en.wikipedia.org/wiki/Trusted_Platform_Module) chip, for example, typically has an embedded [TRNG](http://en.wikipedia.org/wiki/TRNG), as do many security-oriented peripherals, such as some [authentication tokens](http://www.yubico.com/products/yubihsm/).

The actual mechanism used to harvest sources of entropy varies by component, but a simple-to-understand mechanism is the analysis of [noise generated](http://en.wikipedia.org/wiki/Noise_%28electronics%29#Avalanche_noise) at the [avalanche breakdown](http://en.wikipedia.org/wiki/Avalanche_breakdown) of a P-N junction of a diode or transistor. The noise from such a cascade is actually the amplification of the random movement of electrons at the junction - essentially amplifying the randomness of quantum mechanics to the level where it can be read by traditional electronics.

Obviously this isn't the only mechanism you can use to harvest randomness in today's computers, but it's an easy one to understand. In fact it's worth pointing out that the Intel's recent [Ivy Bridge](http://en.wikipedia.org/wiki/Ivy_Bridge_%28microarchitecture%29) architecture introduced a new instruction: **RDRAND**, which yields the output of an on-chip TRNG. IEEE Spectrum has a [detailed write-up](http://spectrum.ieee.org/computing/hardware/behind-intels-new-randomnumber-generator/0) of how it works.

> **Comments:**
> **username_9**: As with the other answer, a definition of "truly random" would help me understand what this means a lot better! I would guess some might not classify these sources as "truly random" because someone might be able to guess the bits better than 50-50 if they know something about, say, the operations the CPU is doing or the current temperature in the transistor. Is that correct?  
> **username_13**: @usul Nope. With thermally-sensitive mechanisms you might be able to *affect* the randomness by cooling the device beyond its normal operating range such that it biases the output. But modifying the device to change its output is not the same thing as *predicting* its output. A simple way to protect against this type of attack is simply shut off the RNG when it is outside its normal operating temperature. And many RNGs are not temperature-sensitive; it's just straight quantum-random noise.  
> **username_13**: Also, note that there are two useful principles of randomness: unpredictably and normal distribution. Brownian noise is by definition random, but the distribution follows a strong bias toward lower frequencies. You want your random data to be "white noise" not "brown noise". The interesting thing is that you can algorithmically normalize the bit distribution: as long as you have a decent source of randomness to start with, your output will be random as well. Just pass your input data through a cryptographic algorithm (e.g. hashing or encryption) that has the output profile you want.  
> **username_11**: I think what Joe refers to is not just statistical test but *proofs* for really being random. The devices that you mention can seem to be unpredictable but it is not the same as proving they are truly random. See the problems section of the Wikipedia article that you have linked to. What Joe is referring to is a method to certify that numbers generated by a device (without knowing how it works internally) are random, i.e. a *user* can verify that the numbers generated by the device are really random without caring about how the device works.  
> **username_13**: @Kaveh Bell's theorem mentioned by Joe states that **No physical theory of local hidden variables can ever reproduce all of the predictions of quantum mechanics.**, or as an extension: *true randomness is derived from quantum mechanics alone*. **All** true RNGs ultimately use quantum mechanics as their source of entropy; all that's left for the details is how to amplify that signal to a level that is detectable. The solution Joe mentioned is not fundamentally different; same rules, same caveats. And it has nothing at all to do with actual quantum computing (except for the word "quantum").  
> **username_11**: As Joe wrote: "*Unfortunately commercial systems are not that sophisticated just yet, and so produce random numbers in a way **that is difficult to test***". I think the method Joe is referring to is different, i.e. it is quite simple to test if the generated numbers are really random. See [this article](http://arxiv.org/abs/1111.6054) for more details.  
> **username_3**: I guess I should jump in here and explain what I meant. Quantum mechanics allows for true randomness in the sense that the outcome of certain experiments is independent of the prior state of both the system and the environment. Most of the ways people currently generate randomness does not really come from this, but rather from either classical chaotic systems (where some minor uncontrolled imprecission in initial preparation leads to vastly different outcomes) or by extracting noise from the environment.  
> **username_3**: (Continued) The problem with these systems is illustrated nicely by Dilbert, here: http://dilbert.com/strips/comic/2001-10-25/ But while quantum mechanics can provide the same results, and may underly the randomness captured from the environment in other systems, there are certain quantum protocols, such as those pointed to by @Kaveh and YonatanN, which go further and actually provide an interactive protocol which proves randomness. This is something which is totally impossible classically, and which can't be mimiced by systems which extract noise from the environment alone.  
> **username_13**: As noted by one anonymous editor, the output of RDRAND is post-processed through a whitening mechanism. This does not set it apart from other TRNGS; whitening is a necessary aspect of turning any truly random bit generator into something cryptographically usable.  

---

### Answer by username_3 on 2013-02-06. Score: 10

Yes, quantum computation allows the generation of truly random numbers, and the operations necessary are so simple companies like id Quantique are already selling quantum random number generators. It is even possible to generate random numbers in a way that proves to the person generating them that they are random (via a violation of Bell's inequality) but this does need a short seed for the proof to be complete (though the numbers are random anyway). Unfortunately commercial systems are not that sophisticated just yet, and so produce random numbers in a way that is difficult to test.

> **Comments:**
> **username_9**: Is it possible/easy to make your first sentence mathematically precise? It doesn't seem obvious to me how to formalize the notion of ``true'' randomness here (or anywhere!). I am picturing a black box that pops out numbers, where $\Pr[\text{next number}] = \Pr[\text{next number} | X]$ where $X$ is anything outside the box.  
> **username_10**: @RickyDemer I believe Joe's referring to this paper: http://arxiv.org/abs/0911.3427 .  
> **username_11**: @RickyDemer, check these recent article by [Umesh Vazirani](http://www.cs.berkeley.edu/~vazirani/): "[Certifiable Quantum Dice](http://rsta.royalsocietypublishing.org/content/370/1971/3432.full.pdf+html)", "[Certifiable Quantum Dice: or, true random number generation secure against quantum adversaries](http://www.cs.berkeley.edu/~vazirani/pubs/dice0.pdf)"  
> **username_11**: You can also check Umesh's talks on the topic, e.g. this one at Berkeley: [Certifiable Quantum Dice](http://www.youtube.com/watch?v=jcsqsb_7kPg).  
> **username_3**: @usul: Consider a device which generates random numbers which has an internal state $\rho$, and the environment is in state $\epsilon$. Then for anything which can reasonably be called a random number generator, which has possible outcomes $x_i$ we have $P(x_i) \notin \[0,1\]$, since otherwise there is no randomness at all. For a pseudo random number generator, this equation is satisfied, but $P(x_i|\rho)\in \[0,1\]$. Hardware random number generators, such as in the other answer satisfy a stronger condition: $P(x_i|\rho)\notin \[0,1\]$.  
> **username_3**: (continued) However, these are generally based on processes which are deterministic, even though they outcome is not dictated solely by the state of the device, and so $P(x_i|\rho,\epsilon) \in \[0,1\]$. Quantum random number generators operate via a process which is inherently stochastic, and hence satisfy the strongest possible such definition of randomness: $P(x_i|\rho,\epsilon)\notin \[0,1\]$.  
> **username_9**: @JoeFitzsimons - Thanks! That is very clear!  
> **username_6**: @JoeFitzsimons. Nice answer. One comment: I think the answer to the OP's question depends partially on how well the quantum RNG devices can be trusted. Could you specify if you are making certain device-independence assumptions in your answer?  
> **username_3**: @JuanBermejoVega: The commercial systems (i.e. id Quantique's RNG) are not yet at the stage of being able to do device independent randomness amplification, but it is something that is possible. There have been a bunch of papers in recent years showing how to extract more and more randomness from a short random seed in an entirely device independent manner. However, ultimately you do need a short seed to kick off the whole process, so you can only really hope to expand the randomness rather than generating it from nothing (at least if you want device independence).  

---

### Answer by username_12 on 2015-02-06. Score: 0

Besides what tylerl says, there's another reason why quantum computers aren't necessary for this. The main difficulty today with implementing quantum computers is to make it be able to do computations on many qubits together. We already have working quantum computers with only one or a few qubits. Those simple systems are enough to produce true randomness of the kind you have requested. In fact, the technology in the quantum cryptography hardware that are already commercially available is enough to produce random bits.


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