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Quantum Random Number Generator: Difference between revisions
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Generating random number of the one of the most important goals of computer scientist because of its wide range of applications such as scientific simulations, lotteries, physics tests and of course CRYPTOGRAPHY. QRNGs use quantum mechanical effects to generate random numbers and have applications that range from simulation to cryptography. QRNGs are also used for quantum protocols such as BB84 Quantum Key Distribution and device independent quantum internet protocols. Random number are generated by classic computers are not secure enough even generating randomly. Because of this reason we need to generate quantum random numbers. | Generating random number of the one of the most important goals of computer scientist because of its wide range of applications such as scientific simulations, lotteries, physics tests and of course CRYPTOGRAPHY. QRNGs use quantum mechanical effects to generate random numbers and have applications that range from simulation to cryptography. QRNGs are also used for quantum protocols such as BB84 Quantum Key Distribution and device independent quantum internet protocols. Random number are generated by classic computers are not secure enough even generating randomly. Because of this reason we need to generate quantum random numbers. | ||
Randomness is a fundamental feature of quantum mechanics, therefore quantum processes can be used to manipulate randomness sources in ways that classical methods cannot. Moreover, quantum solutions exist to games that classically are not solvable. By combining these features, it is possible to amplify weak sources of randomness and expand strong sources of randomness in a manner which provides guarantees against hidden dishonesty and eavesdropping. | |||
==Outline== | ==Outline== | ||
Aim of QRNG is producing unpredictable and securest number. It has three main steps. | Aim of QRNG is producing unpredictable and securest number. It has three main steps. | ||
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In a similar vein, it is only possible to extract uniform, private randomness by combining multiple weak sources together classically. Randomness amplification enables the extraction of such randomness from only a single weak source - useful in any situation where only some randomness has been provided but absolute security is required. | In a similar vein, it is only possible to extract uniform, private randomness by combining multiple weak sources together classically. Randomness amplification enables the extraction of such randomness from only a single weak source - useful in any situation where only some randomness has been provided but absolute security is required. | ||
==Protocols== | |||
* [[Certified finite randomness expansion]] | |||
* [[Certified infinite randomness expansion]] | |||
* [[Randomness amplification (8 devices)]] | |||
==Notations== | ==Notations== | ||
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#[https://arxiv.org/abs/1604.03304 Collantes and Escartin (2016)] | #[https://arxiv.org/abs/1604.03304 Collantes and Escartin (2016)] | ||
#[https://www.nature.com/articles/npjqi201621 Ma et al (2016)] | #[https://www.nature.com/articles/npjqi201621 Ma et al (2016)] | ||
<div style='text-align: right;'>''contributed by Gözde Üstün''</div> | <div style='text-align: right;'>''contributed by Gözde Üstün and Neil Mcblane''</div> | ||