No Arabic abstract
A quantum random-number generator (QRNG) can theoretically generate unpredictable random numbers with perfect devices and is an ideal and secure source of random numbers for cryptography. However, the practical implementations always contain imperfections, which will greatly influence the randomness of the final output and even open loopholes to eavesdroppers. Recently, Thewes et al. experimentally demonstrated a continuous-variable eavesdropping attack, based on heterodyne detection, on a trusted continuous-variable QRNG in Phys. Rev. A 100, 052318 (2019), yet like in many other practical continuous-variable QRNG studies, they always supposed the local oscillator was stable and ignored its fluctuation which might lead to security threats such as wavelength attack. In this work, based on the theory of the conditional min-entropy, imperfections of the practical security of continuous-variable QRNGs are systematically analyzed, especially the local oscillator fluctuation under imbalanced homodyne detection. Experiments of a practical QRNG based on vacuum fluctuation are demonstrated to show the influence of local oscillator fluctuation on the total measurement noise variances and the practical conditional min-entropy with beam splitters of different transmittances. Moreover, a local oscillator monitoring method is proposed for the practical continuous-variable QRNG, which can be used to calibrate the practical conditional min-entropy.
We reverse-engineer, test and analyse hardware and firmware of the commercial quantum-optical random number generator Quantis from ID Quantique. We show that > 99% of its output data originates in physically random processes: random timing of photon absorption in a semiconductor material, and random growth of avalanche owing to impact ionisation. We have also found minor non-random contributions from imperfections in detector electronics and an internal processing algorithm. Our work shows that the design quality of a commercial quantum-optical randomness source can be verified without cooperation of the manufacturer and without access to the engineering documentation.
Phase-randomized optical homodyne detection is a well-known technique for performing quantum state tomography. So far, it has been mainly considered a sophisticated tool for laboratory experiments but unsuitable for practical applications. In this work, we change the perspective and employ this technique to set up a practical continuous-variable quantum random number generator. We exploit a phase-randomized local oscillator realized with a gain-switched laser to bound the min-entropy and extract true randomness from a completely uncharacterized input, potentially controlled by a malicious adversary. Our proof-of-principle implementation achieves an equivalent rate of 270 Mbit/s. In contrast to other source-device-independent quantum random number generators, the one presented herein does not require additional active optical components, thus representing a viable solution for future compact, modulator-free, certified generators of randomness.
We study the impact of finite-size effect on continuous variable source-independent quantum random number generation. The central-limit theorem and maximum likelihood estimation theorem are used to derive the formula which could output the statistical fluctuations and determine upper bound of parameters of practical quantum random number generation. With these results, we can see the check data length and confidence probability has intense relevance to the final randomness, which can be adjusted according to the demand in implementation. Besides, other key parameters, such as sampling range size and sampling resolution, have also been considered in detail. It is found that the distribution of quantified output related with sampling range size has significant effects on the loss of final randomness due to finite-size effect. The overall results indicate that the finite-size effect should be taken into consideration for implementing the continuous variable source-independent quantum random number generation in practical.
The value of residual phase noise, after phase compensation, is one of the key limitations of performance improvement for continuous-variable quantum key distribution using a local local oscillator (LLO CV-QKD) system, since it is the major excess noise. However, due to the non-ideality of the realistic devices implemented in practice, for example, imperfect lasers, detectors and unbalanced interferometers, the value of residual phase noise in current system is still relatively large. Here, we develop a phase noise model to improve the phase noise tolerance of the LLO CV-QKD schemes. In our model, part of the phase-reference measurement noise associated with detection efficiency and electronic noise of Bobs detector as well as a real-time monitored phasereference intensity at Bobs side is considered trusted because it can be locally calibrated by Bob. We show that using our phase noise model can significantly improve the secure key rate and transmission distance of the LLO CV-QKD system. We further conduct an experiment to substantiate the superiority of the phase noise model. Based on experimental data of a LLO CV-QKD system in the 25 km optical fiber channel, we demonstrate that the secure key rate under our phase noise model is approximately 40% higher than that under the conventional phase noise model.
We present a scheme for a self-testing quantum random number generator. Compared to the fully device-independent model, our scheme requires an extra natural assumption, namely that the mean energy per signal is bounded. The scheme is self-testing, as it allows the user to verify in real-time the correct functioning of the setup, hence guaranteeing the continuous generation of certified random bits. Based on a prepare-and-measure setup, our scheme is practical, and we implement it using only off-the-shelf optical components. The randomness generation rate is 1.25 Mbits/s, comparable to commercial solutions. Overall, we believe that this scheme achieves a promising trade-off between the required assumptions, ease-of-implementation and performance.