Quantum Random Number Generators

随机数对于包括彩票、统计抽样、计算机模拟和密码学在内的各种应用都是至关重要的。它们还可以用于在量子密钥分发（QKD）和量子力学基础的基本测试中做出随机决策。对于每个应用程序，对随机数的要求可能不同。对于某些应用程序，例如计算机模拟，只要数字具有所需的统计属性，而不需要它们是不可预测的，就足够了。然而，对于许多应用程序，特别是密码学，数字的不可预测性也是必不可少的。a . kerckhoffs表明，安全通信的问题可以简化为生成用作密钥的随机数。因此，现代密码学的安全性依赖于用于密钥、公钥生成、会话标识符等的随机数。因此，这些系统中的随机数生成器是一个潜在的灾难性安全弱点。现有随机数生成器（rng）的弱点不断被揭露，有人担心有些人可能会通过系统地削弱它们而引入后门来利用它们。潜在的问题是可信赖的熵供应不足。为了应对这种情况，监管机构、标准机构和加密产品认证越来越重视验证随机数生成的声明。产生随机数的技术范围很广。伪随机数生成器（prng）使用确定性算法生成随机数，由于其可预测性而不适合用于密码学。因此，我们转向真正的随机数生成器（trng），它测量不可预测或至少很难预测的物理过程的结果，并使用结果生成随机数。使用TRNG提供第三方无法知道或操纵的熵是非常具有挑战性的。在这方面，量子随机数生成器（qrng）基于量子力学过程的测量产生数字，比基于测量经典过程的trng具有明显的优势，因为它们的随机源通常是一个定义良好的量子现象。因此，即使在存在额外的经典噪声和潜在窃听者的情况下，也可以使用对随机源的精确描述来推导熵的边界。信息理论上安全的随机数可以通过后处理由测量产生的原始比特提取出来。该项目的主要目的是开发一种适合于密码学应用的快速安全的光子QRNG。

Random numbers are vital for a wide variety of applications including lotteries, statistical sampling, computer simulations and cryptography. They can also be used to make random decisions required in both quantum key distribution (QKD) and fundamental tests of the foundations of quantum mechanics.For each application the requirements on the random numbers may be different. For some applications, such as computer simulations, it is sufficient for the numbers to have the required statistical properties without any need for them to be unpredictable. However for many applications, especially cryptography, it is essential for the numbers to be unpredictable too.A.Kerckhoffs showed that the problem of secure communications could be reduced to the generation of random numbers for use as keys. Consequently, the security of modern cryptography rests on the random numbers used for secret keys, public key generation, session identifiers and more. The random number generators in these systems are therefore a potentially catastrophic security weakness. There has been a steady stream of revelations of weaknesses in existing random number generators (RNGs) and there are concerns that some can be exploited using backdoors introduced by systematically weakening them. The underlying problem is an insufficient supply of trustworthy entropy. In response to this regulators, standards bodies and certifications for cryptographic products are placing growing emphasis on validating claims for random number generation.There exist a wide range of techniques for generating random numbers. Pseudorandom number generators (PRNGs), which use deterministic algorithms to generate random numbers, are not suitable for use in cryptography due to their predictability. We therefore turn to truly random number generators (TRNGs) which measure the outcome of an unpredictable or at least very hard to predict physical process and use the results to generate random numbers.Providing entropy which cannot be known or manipulated by third parties using a TRNG is remarkably challenging. In this respect, quantum random number generators (QRNGs) which generate numbers based on measurements of quantum mechanical processes offer a clear advantage over TRNGs based on measuring classical processes in that their randomness source is typically a well defined quantum phenomenon. Consequently a precise description of the randomness source can be used to derive bounds on the entropy, even in the presence of additional classical noise and potential eavesdroppers. Information theoretically secure random numbers can then be extracted by post-processing the raw bits produced by the measurements. The main aim of this project will be to develop a fast and secure photonic QRNG suitable for use in cryptographic applications.