Quantum random number generators (QRNGs) are crucial components for security applications, but the on-chip integration is often blocked by the incompatibility of mainstream optical schemes with standard Complementary Metal-Oxide-Semiconductor (CMOS) processes. In this study, artificially designed quantum dots are built in a low-doped silicon nanowire using local doping method. Which is fully CMOS-compatible. By manipulating the gate voltage (Vg) of the silicon nanowire device with a drain voltage (Vd) of 50 mV, a 1 1 high/low ratio is almost achieved as the quantum-induced random telegraph signal (RTS) at Vg = -270 mV. The binary sequence generated through sampling exhibits near-ideal Shannon entropy (binary: 0.999998, quaternary: 1.999996) and passed 88.89% of the tests in the NIST statistical test suite. This work provides a feasible design and fabrication strategy for RTS devices used as QRNGs, facilitating the observation of RTS at room temperature and ensuring compatibility with CMOS fabrication processes.
Quantum random number generators (QRNGs) are crucial components for security applications, but the on-chip integration is often blocked by the incompatibility of mainstream optical schemes with standard Complementary Metal-Oxide-Semiconductor (CMOS) processes. In this study, artificially designed quantum dots are built in a low-doped silicon nanowire using local doping method. Which is fully CMOS-compatible. By manipulating the gate voltage (Vg) of the silicon nanowire device with a drain voltage (Vd) of 50 mV, a 1 1 high/low ratio is almost achieved as the quantum-induced random telegraph signal (RTS) at Vg = -270 mV. The binary sequence generated through sampling exhibits near-ideal Shannon entropy (binary: 0.999998, quaternary: 1.999996) and passed 88.89% of the tests in the NIST statistical test suite. This work provides a feasible design and fabrication strategy for RTS devices used as QRNGs, facilitating the observation of RTS at room temperature and ensuring compatibility with CMOS fabrication processes.
The need for hardware random number generators (HRNGs) that can be integrated in a silicon (Si) complementary-metal–oxide–semiconductor (CMOS) platform has become increasingly important in the era of the Internet-of-Things (IoT). Si MOSFETs exhibiting random telegraph signals (RTSs) have been considered as such a candidate for HRNG, though its application has been hindered by RTS’s variability and uncontrollable, unpredictable characteristics. In this paper, we report the generation and randomness evaluation of random numbers from RTSs in a Si single electron pump (SEP) device at room temperature. SEP devices are known to consistently produce RTSs due to a quantum dot electrically defined by multi-layer polycrystalline Si gates. Using RTSs observed in our devices, random numbers were extracted by a classifier supported by supervised learning, where part of data was used to train the classifier before it is applied to the rest to generate random numbers. The random numbers generated from RTSs were used as inputs for the Monte Carlo method to calculate the values of π, and the distribution was compared against the result obtained from the Mersenne Twister, a representative pseudo-random number generator (PRNG), under the same condition. π was estimated more than 80 000 times, and the distribution of the estimated values has a central value of 3.14 with a variance of 0.273, which is only twice as large as the result from PRNG. Our result paves a way to fully electronic CMOS compatible HRNGs that can be integrated in a modern system-on-a-chip in IoT devices.
A random number generation approach comprising a silicon nanocrystals LED (Si-NCs LED), silicon single photon avalanche photodiode (Si SPAD) and a field-programmable gate array (FPGA) is introduced. The Si-NCs LED is the source of entropy with photon emission in the visible range detectable by silicon detectors allowing the fabrication of an all-silicon-based device. The proposed quantum random number generator (QRNG) is robust against variations of the internal and external parameters such as aging of the components, changing temperature, the ambient interferences and the silicon detector artifacts. The raw data show high quality of randomness and passed all the statistical tests in National Institute of Standards and Technology (NIST) tests suite without the application of a post-processing algorithm. The efficiency of random number generation is 4-bits per detected photon.
Different electronic devices nowadays exploit random number generators either to create the seed for simulations, for gaming or to encrypt the communications. Particularly for cryptography applications, there is an increasing effort to realize a truly random number generator, based not on mathematical algorithms but exploiting randomness of physical processes. Among them quantum processes, provide intrinsic unpredictability, for example exploiting the arrival time, the number or the properties of photons. In this work we focus on photonic quantum random number generator (QRNG), and we analyze different approaches and entropy extraction methods to realize a fully integrated, CMOS compatible, QRNG with photon-emitter realized on the same chip and very close to the detectors of single photons. Non-idealities of the emitter and the detector have to be studied and depends on the structure. They can be mitigated with robust extraction methods which however should not introduce complex algorithms or secondary entropy sources that can make the device no longer quantum based. The ultimate goal is to realize a CMOS building block that can be implemented as building block, with low power consumption and robust to environmental conditions.
Random numbers find applications in a range of different fields, from quantum key distribution and classical cryptography to fundamental science.They also find extensive use in gambling and lotteries.By exploiting the probabilistic nature of Quantum Mechanics, quantum random number generators (QRNGs) provide a secure and efficient means to produce random numbers.Most of the quantum random number generators demonstrated so far have been built in bulk optics, either using free space or fibre-optic components.While showing good performance, most of these demonstrations are strongly limited in real life applications, due to issues such as size, costs and the manufacturing process.In this thesis I report the demonstration of three different QRNGs based on integrated photonics.First, I demonstrated a QRNG based on homodyne measurement of optical vacuum states on a Silicon-on-insulator (SOI) chip.Second, I developed a SOI QRNG based on phase fluctuations from a laser diode.In these two schemes all the optical and opto-electronic components, excluding the laser, were integrated onto a silicon-on-insulator device.These schemes, being built on a silicon-on-insulator chip are potentially CMOS compatible and pave the way for being integrated onto other more complex systems.These QRNGs showed Gbps generation rates and passed the statistical tests provided by NIST.Third, I report the preliminary study of a QRNG based on homodyne measurement of optical vacuum states onto a Indium Phosphide (InP) chip.In this third experiment, all the components, including a laser diode, were monolithically integrated in the same chip, which provide a great advantage in terms of the overall size of the optics of the device.First, I would like to thank Jonathan, for the opportunity to pursue my PhD and for guiding my research in these four years.Thank you for giving me the chance to follow my curiosity and for pushing me to get the best out of my research.Thank you, Dylan, for being so helpful, always ready to answer my questions.I would like to thank Giacomo for sharing a big part of my research in these years
Random numbers are fundamental elements in different fields of science and technology such as computer simulation like Monte Carlo-method simulation, statistical sampling, cryptography, games and gambling, and other areas where unpredictable results are necessary. Random number generators (RNG) are generally classified as “pseudo”-random number generators (PRNG) and "truly" random number generators (TRNG). Pseudo random numbers are generated by computer algorithms with a (random) seed and a specific formula. The random numbers produced in this way (with a small degree of unpredictability) are good enough for some applications such as computer simulation. However, for some other applications like cryptography they are not completely reliable. When the seed is revealed, the entire sequence of numbers can be produced. The periodicity is also an undesirable property of PRNGs that can be disregarded for most practical purposes if the sequence recurs after a very long period. However, the predictability still remains a tremendous disadvantage of this type of generators. Truly random numbers, on the other hand, can be generated through physical sources of randomness like flipping a coin. However, the approaches exploiting classical motion and classical physics to generate random numbers possess a deterministic nature that is transferred to the generated random numbers. The best solution is to benefit from the assets of indeterminacy and randomness in quantum physics. Based on the quantum theory, the properties of a particle cannot be determined with arbitrary precision until a measurement is carried out. The result of a measurement, therefore, remains unpredictable and random. Optical phenomena including photons as the quanta of light have various random, non-deterministic properties. These properties include the polarization of the photons, the exact number of photons impinging a detector and the photon arrival times. Such intrinsically random properties can be exploited to generate truly random numbers. Silicon (Si) is considered as an interesting material in integrated optics. Microelectronic chips made from Si are cheap and easy to mass-fabricate, and can be densely integrated. Si integrated optical chips, that can generate, modulate, process and detect light signals, exploit the benefits of Si while also being fully compatible with electronic. Since many electronic components can be integrated into a single chip, Si is an ideal candidate for the production of small, powerful devices. By complementary metal-oxide-semiconductor (CMOS) technology, the fabrication of compact and mass manufacturable devices with integrated components on the Si platform is achievable. In this thesis we aim to model, study and fabricate a compact photonic quantum random number generator (QRNG) on the Si platform that is able to generate high quality, "truly" random numbers. The proposed QRNG is based on a Si light source (LED) coupled with a Si single photon avalanche diode (SPAD) or an array of SPADs which is called Si photomultiplier (SiPM). Various implementations of QRNG have been developed reaching an ultimate geometry where both the source and the SPAD are integrated on the same chip and fabricated by the same process. This activity was performed within the project SiQuro—on Si chip quantum optics for quantum computing and secure communications—which aims to bring the quantum world into integrated photonics. By using the same successful paradigm of microelectronics—the study and design of very small electronic devices typically made from semiconductor materials—, the vision is to have low cost and mass manufacturable integrated quantum photonic circuits for a variety of different applications in quantum computing, measure, sensing, secure communications and services. The Si platform permits, in a natural way, the integration of quantum photonics with electronics. Two methodologies are presented to generate random numbers: one is based on photon counting measurements and another one is based on photon arrival time measurements. The latter is robust, masks all the drawbacks of afterpulsing, dead time and jitter of the Si SPAD and is effectively insensitive to ageing of the LED and to its emission drifts related to temperature variations. The raw data pass all the statistical tests in national institute of standards and technology (NIST) tests suite and TestU01 Alphabit battery without a post processing algorithm. The maximum demonstrated bit rate is 1.68 Mbps with the efficiency of 4-bits per detected photon. In order to realize a small, portable QRNG, we have produced a compact configuration consisting of a Si nanocrystals (Si-NCs) LED and a SiPM. All the statistical test in the NIST tests suite pass for the raw data with the maximum bit rate of 0.5 Mbps. We also prepared and studied a compact chip consisting of a Si-NCs LED and an array of detectors. An integrated chip, composed of Si p+/n junction working in avalanche region and a Si SPAD, was produced as well. High quality random numbers are produced through our robust methodology at the highest speed of 100 kcps. Integration of the source of entropy and the detector on a single chip is an efficient way to produce a compact RNG. A small RNG is an essential element to guarantee the security of our everyday life. It can be readily implemented into electronic devices for data encryption. The idea of "utmost security" would no longer be limited to particular organs owning sensitive information. It would be accessible to every one in everyday life.
Random numbers are essential resources in science and engineering, with indispensable applications in simulation, cybersecurity, and finance. Quantum random number generators (QRNGs), based on the principles of quantum mechanics, ensure genuine randomness and unpredictability. Silicon photonics enables the large-scale deployment of integrated QRNGs due to its low cost, miniaturization, and compatibility with CMOS technology. However, current integrated QRNGs are typically based on perfect or partially perfect device models, deviating from real-world devices, which compromises the unpredictability of quantum random numbers. In this study, we implemented a silicon-based QRNG that makes no assumptions about the source and only uses trusted but uncharacterized measurement devices. In experimental demonstration, we show that our setup can generate secure random numbers with different choices of intensities of laser light, and achieve an optimized random number generation rate of up to 4.04 Mbps. Our work significantly advances the security, practicality, and commercial development of QRNGs by employing imperfect devices.