Quantum random number generator combines best of two approaches

A sketch of the new protocol for quantum random number generation (QRNG), in which the randomness can be estimated by measuring the entropy of the photon data, and then post-processing can be applied to extract a string of random numbers. Credit: Lunghi, et al. ©2015 American Physical Society

(Phys.org)—Science is a discipline that often seeks order and patterns in the world around us, but randomness also has its uses. Random numbers are a vital tool for areas such as cryptography, computer simulations, and statistical analysis. Generating long strings of truly random numbers is surprisingly difficult, yet necessary for achieving good performance and high security in these applications.

One way to generate involves taking advantage of the randomness inherent in known as "quantum noise." Quantum (QRNG) procedures often involve single-photon sources. Since single photons are usually emitted at random times, it is impossible to perfectly define the number of photons emitted in a given time, which results in measurement uncertainty and randomness.

Current QRNG approaches fall into two categories: device-dependent and device-independent. Device-dependent approaches, which are used by all commercial QRNGs, require a detailed knowledge of the functioning of the devices used in the protocol. They generate random numbers at a very high rate (4 million random bits per second) at a level of security that is much higher than that of classical pseudo-random number generators, but based on assumptions that are difficult to verify.

On the other hand, device-independent approaches do not require the same knowledge of the devices and offer even stronger security, but their practical implementation requires complex, state-of-the-art setups that can only achieve very low rates of random number generation.

In a new paper published in Physical Review Letters, physicists from the University of Geneva have developed a protocol that offers an intermediate approach to QRNG: it requires only a few general assumptions about the devices, but not a detailed model of their functioning. Its performance rate (23 random bits per second) and security are also in between the device-dependent and device-independent approaches, but like the former, the protocol can be implemented with standard technology.

"The main significance of the work is probably to investigate the certification of random number generation in a scenario where the devices suffer from technical imperfections, but are not maliciously conspiring against the user," coauthor Nicolas Brunner at the University of Geneva told Phys.org. "That is, a scenario somehow intermediate between the standard device-dependent one, where devices are assumed to be well-characterized, and the 'more paranoiac' device-independent case, where an adversary could in principle have prepared the devices."

The key improvement of the new protocol is that it is self-testing, meaning it can provide a real-time estimate of the randomness of the experimental photon data, as measured by the entropy. It can also distinguish this genuine randomness from other sources of randomness such as technical imperfections. When the amount of genuine randomness is known, then the raw data can be post-processed appropriately to generate strings of random numbers.

To demonstrate the self-testing ability, the researchers simply switched off the air conditioning in the room. Because quantum systems such as single-photon sources are so sensitive to their environments, the change in temperature impacts the alignment of the optical setup and the randomness of the emitted photons. The system could immediately recognize the change in randomness so that more post-processing could be applied, guaranteeing the continued generation of high-quality random numbers.

Overall, the new protocol offers a simplified QRNG method that, while not achieving rates as high as that of commercial QRNGs, delivers higher security without the need for a detailed characterization of the devices. This combination of features could prove useful for future applications.

"Randomness is a very important resource for many applications," Brunner said. "However, the certification of is still an important challenge, that is, to be able to estimate how random the output of some device is based on simple and verifiable assumptions about the device.

"Our goal is to develop better schemes, which are easier to implement and that achieve much higher rates. The main objective, however, is still to find the scenario offering the optimal trade-off between security and ease of implementation."

Explore further

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More information: Tommaso Lunghi, et al. "Self-Testing Quantum Random Number Generator." Physical Review Letters. DOI: 10.1103/PhysRevLett.114.150501
Journal information: Physical Review Letters

© 2015 Phys.org

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Apr 29, 2015
It depends upon what is possible. Is it possible to define charge? So every group is a set of those possibilities. i.e. the unknown-known, to quote a phrase. Is the magnitude of the group simply a function of the number of these undefinable particles, simply a function of a positive count from zero to infinity, defines matter. For a finite number, a finite number of groups. We can define these from the bottom up a lot easier than the top down. Simple simulator, running forever, from zero to infinity. Spitting out data continuously, get what you need before designing the experiment, or at least define the language based upon what set of truths; In other words, define what states are possible. This method, brilliant, but it's a countable set of things, takes too much energy in it's preparation with everything possible, but for what amount of time, and ... Oh, I off your point. I was imagining is randomness actually a possibility, physically, the world a countable and limited .

Apr 29, 2015
If the only way to generate truly random numbers or random choice is through a quantum device doesn't that imply the human brain's function must be based on quantum principles too?

Apr 29, 2015
So is it shoot first and ask questions later? Well, OK for games and Monte Carlo, but ...

Apr 29, 2015
Plus relative motion and the field. Definable!

Apr 29, 2015
The most logical use of a true RNG for encryption is for a "one time book". Two texts (or identical files of some sort) are shared by person to person transfer and later used to encrypt messages until the texts exhaust. It is never re-used. The security is unbreakable unless the code book is discovered. Not practical for high speed data streams. "Device-dependent approaches, which are used by all commercial QRNGs..." are more practical.

For Monte Carlo simulation, a very long RN file is useful, especially if the randomness is very strong. The only concern here is that several RN sets should be used on several runs to ensure aberration does not sneak in.

The very best RNGs used today are algorithms, which have various faults: (1) After very long periods, they repeat. (2) Depending on the algorithm, certain seeds render the method ineffective. (3) Mathematical methods may "crack" the method.

The QRNG posits that Quantum mechanics guarantees strong randomness which is not proven.

Apr 30, 2015
I am always suspicious when SCIENTISTS tell me that he/she does not have idea how things really work or even has a working hypothesis. An that's exactly what they say. Secondly, concept of pure randomness stem from mental experiments conducted by mathematicians dealing with probability theory assuming that there is no "generative procedure(s)" that produce observed outcomes. The stochastic randomness in contrast is based on well defined generative procedure but produces outcomes that cannot be determined assuming that cause and effect exists, like throwing the dice. We know that movement of our fingers and hands and specific construction and biases of the dice "cause" an outcome we observe hence generative procedure exists but we are unable to learn what is it exactly.If we knew it, it would not be random outcome. Quanta also will not give us pure randomness since it is theoretical.


Apr 30, 2015
Better put a back door into the algorithm or the NSA will complain.

(Like the NSA's bad random algorithm they gave to RSA a few years back)

Apr 30, 2015
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