The generation of random numbers is a task of paramount importance in modern science. A central problem for both classical and quantum randomness generation is to estimate the entropy of the data generated by a given device. Here we present a protocol for self-testing quantum random number generation, in which the user can monitor the entropy in real time. Based on a few general assumptions, our protocol guarantees continuous generation of high quality randomness, without the need for a detailed characterization of the devices. Using a fully optical setup, we implement our protocol and illustrate its self-testing capacity. Our work thus provides a practical approach to quantum randomness generation in a scenario of trusted but error-prone devices.
The generation of random numbers is a task of paramount importance in modern science. A central problem for both classical and quantum randomness generation is to estimate the entropy of the data generated by a given device. Here we present a protocol for self-testing quantum random number generation, in which the user can monitor the entropy in real time. Based on a few general assumptions, our protocol guarantees continuous generation of high quality randomness, without the need for a detailed characterization of the devices. Using a fully optical setup, we implement our protocol and illustrate its self-testing capacity. Our work thus provides a practical approach to quantum randomness generation in a scenario of trusted but error-prone devices.
Quantum random number generators (QRNGs) use the inherent unpredictability of quantum mechanics to generate true randomness, as opposed to classical random number generators. However, ensuring the authenticity of this randomness still requires robust verification. Self-testing QRNGs address this need by enabling the validation of the randomness produced based on the observed data from the experiment while requiring few assumptions. In this work, we present a practical, self-testing QRNG designed to operate with an untrusted measurement device and a partially characterized source, allowing the user to check the adequate functioning of the setup in real time. Our experiment yields a rate of certified random bits of 450 kbps.
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.
We introduce a scheme for a self-testing quantum random-number generator and demonstrate it experimentally. Compared to the fully device-independent model, our scheme requires an extra natural assumption, namely, that the mean number of photons of the signal optical modes 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. The scheme is based on a prepare-and-measure setup, which we implement in a proof-of-principle experiment 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.
Self-testing and semi-device independent protocols are becoming the preferred choice for quantum technologies, being able to certify their quantum nature with few assumptions and simple experimental implementations. In particular, for quantum random number generators, the possibility of monitoring, in real time, the entropy of the source only by measuring the input/output statistics is a characteristic that no other classical system could provide. The cost of this possibility is not necessarily increased complexity and reduced performance. Indeed, here we show that with a simple optical setup consisting of commercially available components, a high bit generation rate can be achieved. We manage to certify 145.5 MHz of quantum random bit generation rate.
Self-testing and semi-device independent protocols are becoming the preferred choice for quantum technologies, being able to certify their quantum nature with few assumptions and simple experimental implementations. In particular, for quantum random number generators, the possibility of monitoring, in real time, the entropy of the source only by measuring the input/output statistics is a characteristic that no other classical system could provide. The cost of this possibility is not necessarily increased complexity and reduced performance. Indeed, here we show that with a simple optical setup consisting of commercially available components, a high bit generation rate can be achieved. We manage to certify 145.5 MHz of quantum random bit generation rate.
Abstract Quantum physics can be exploited to generate true random numbers, which have important roles in many applications, especially in cryptography. Genuine randomness from the measurement of a quantum system reveals the inherent nature of quantumness—coherence, an important feature that differentiates quantum mechanics from classical physics. The generation of genuine randomness is generally considered impossible with only classical means. On the basis of the degree of trustworthiness on devices, quantum random number generators (QRNGs) can be grouped into three categories. The first category, practical QRNG, is built on fully trusted and calibrated devices and typically can generate randomness at a high speed by properly modelling the devices. The second category is self-testing QRNG, in which verifiable randomness can be generated without trusting the actual implementation. The third category, semi-self-testing QRNG, is an intermediate category that provides a tradeoff between the trustworthiness on the device and the random number generation speed.