High speed continuous variable source-independent quantum random number generation

Abstract

As a fundamental phenomenon in nature, randomness has a wide range of applications in the fields of science and engineering. Among different types of random number generators (RNG), quantum random number generator (QRNG) is a kind of promising RNG as it can provide provable true random numbers based on the inherent randomness of fundamental quantum processes. Nevertheless, the randomness from a QRNG can be diminished (or even destroyed) if the devices (especially the entropy source devices) are not perfect or ill-characterized. To eliminate the practical security loopholes from the source, sourceindependent QRNGs, which allow the source to have arbitrary and unknown dimensions, have been introduced and become one of the most important semi-device-independent QRNGs. Herein a method that enables ultra-fast unpredictable quantum random number generation from quadrature fluctuations of quantum optical field without any assumptions on the input states is proposed. Particularly, to estimate a lower bound on the extractable randomness that is independent from side information held by an eavesdropper, a new security analysis framework is established based on the extremality of Gaussian states, which can be easily extended to design and analyze new semi-device-independent continuous variable QRNG protocols. Moreover, the practical imperfections of the QRNG including the effects of excess noise, finite sampling range, finite resolution and asymmetric conjugate quadratures are taken into account and quantitatively analyzed. Finally, the proposed method is experimentally demonstrated to obtain high secure random number generation rates of 15.07 Gbits/s in off-line configuration and can potentially achieve 6 Gbits/s by real-time post-processing.High Speed Continuous Variable Source-Independent Quantum Random Number Generation 2 IntroductionRandom numbers are of extreme importance for a wide range of applications in both scientific and commercial fields [1], such as numerical simulations, lottery games and cryptography. A significant example is the quantum key distribution (QKD), in which the true random numbers are essential for both quantum states preparation and detection to guarantee unconditional security [2][3][4]. Classical pseudo random number generators (PRNG), which are based on the computational algorithms, have been widely used in modern information systems. However, due to the deterministic and thus predictable features of the algorithms, PRNG are not suitable for certain applications where true randomness is required. Distinct from the PRNG, true random number generators (TRNG) extract randomness from physical random processes [5]. An important type of TRNGs is the quantum random number generator (QRNG), which is based on the intrinsic randomness of fundamental quantum processes and can provide truly unpredictable and irreproducible random numbers [6][7][8].The existing QRNG protocols can be mainly classified into three different categories as in Ref.[7], i.e. the practical, device-independent and semi-device-ind...

Quantum sampling and entropic uncertainty

“…Several security models exist ranging from the very weak fully-trusted scenario to the very strong device independent (DI) model [15,16] (which, though having strong security guarantees, is slow to implement in practice [17,18]). In between is the source independent (SI) model whereby only the source is untrusted, but the measurement devices are characterized [19,20,21,22]. See [23] for a general survey of QRNGs and their security models.…”

A Phase Fluctuation Based Practical Quantum Random Number Generator Scheme with Delay-Free Structure

“…In contrast, quantum random number generators (QRNG) [7][8][9], based on the intrinsic random nature of quantum processes, stand out as a promising alternative for its non-deterministic and unpredictable characteristics. QRNG schemes are classified into three categories, based on various requirements of physical devices, namely full-device-independent [10][11][12], semi-deviceindependent [13][14][15][16][17][18], and full-trusted-device, i.e., practical QRNG schemes. Among the three categories, practical QRNG has been developed rapidly due to its convenience and huge demand.…”

Bias-free source-independent quantum random number generator

“…Up to now, vacuum fluctuation [7][8][9][10] and phase noise [11][12][13][14] are two main continuous-variable quantum sources for random number generation, where vacuum fluctuation has become a research focus recently because the model of SI-QRNG based on measuring vacuum fluctuation is relatively simple and it supports the implementation of a stable and integrated SI-QRNG system that is insensitive to the detection efficiency. As a promising quantum random source, vacuum fluctuation has already Existing SI-QRNGs assume a constant intensity of local oscillator (LO) [15,16], which is not consistent with the facts and detailed analysis of eliminating the LO fluctuation in the SI-QRNG scenario is still absent. The residual common mode noise introduced by the fluctuated LO in the biased system will inevitably lead to the overestimation of true randomness, which will definitely compromise the security of generated random numbers.…”