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Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE

A robust approach to the generation of high-quality random numbers

Zahra Bisadi, Giorgio Fontana, Enrico Moser, Georg Pucker, Lorenzo Pavesi

Published Oct 24, 2016• 1 citation
Publisher

Abstract

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.

DOI
10.1117/12.2242000

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A quantum random number generator (QRNG) based on a silicon nanocrystals (Si-NCs) light emitting device (LED) coupled with a silicon single photon avalanche photodiode (Si-SPAD) is presented. A simple setup is used for the generation of random bits. The modeled approach assures a negligible bias on datasets of 100 Mbits length. The raw data pass all the statistical tests in the National Institute of Standards and Technology (NIST) suite without any post-processing operations. The bit-rate of 0.6 Mbps is achieved. The information-theoretically provable randomness extractor of Toeplitz-hashing function is applied to longer datasets (1 Gbits) to extract the randomness, to minimize the bias, and consequently pass all the NIST tests. Stabilizing the temperature, resetting the applied current to the LED, or a feedback system can also be used as parameter control solutions to generate good quality, long datasets of random numbers suitable for cryptographic applications.
A robust quantum random number generation methodology has been developed and tested. The physical setup is based on a silicon nanocrystals light source coupled with a Si single photon avalanche diode driving a fully synchronous digital logic in a field-programmable gate array. After detailed analyses of the source and the detector, methods have been developed to make the nonidealities of the system and their consequent drawbacks decoupled from the quality of the generated random numbers. All the statistical tests in the national institute of standards and technology tests suite and the TestU01 Alphabit battery are consistently passed without a postprocessing operation on the raw data and without any feedback action on the photon source or any other parameter of the system. The maximum demonstrated bit-rate reaches 1.68 Mb/s, with an efficiency of 4 bits per detected photon. The modeling proves that the system is not influenced by variations of the internal and external parameters, such as the aging of the components and changing temperature.
A small-sized photonic quantum random number generator, easy to be implemented in small electronic devices for secure data encryption and other applications, is highly demanding nowadays. Here, we propose a compact configuration with Silicon nanocrystals large area light emitting device (LED) coupled to a Silicon photomultiplier to generate random numbers. The random number generation methodology is based on the photon arrival time and is robust against the non-idealities of the detector and the source of quantum entropy. The raw data show high quality of randomness and pass all the statistical tests in national institute of standards and technology tests (NIST) suite without a post-processing algorithm. The highest bit rate is 0.5 Mbps with the efficiency of 4 bits per detected photon.
We present a new compact photonic quantum random number generator based on an emitter (source of entropy) and a single-photon detector integrated in the same silicon chip. Not only they are integrated one close to the other, but also they are fabricated with the same fabrication process. The emitter is a small silicon photomultiplier, composed of passively-quenched single photon avalanche diodes (SPADs), having the same layout of the single SPAD used as the detector. The emitter is a reverse-biased silicon p-n junction, generating photons mainly due to impact ionization during the avalanche breakdown process. The detector is shielded from ambient light by a top metal layer: only photons from the emitter are detected, making this integrated approach more robust. The random bits are extracted with a robust methodology based on the measurement of photon arrival times, using discrete time bins, in a time frame cyclically repeated in time. No postprocessing is required for the raw data to pass the statistical tests.
Quantum random number generators (QRNGs) leverage the inherent unpredictability of quantum mechanical phenomena to produce random numbers. However, the performance of many QRNGs is hindered by limitations such as low generation rates and the bulkiness of systems utilizing single-photon detectors (SPDs). In this study, we present a QRNG that addresses these challenges by using a micro-LED as an entropy source, utilizing the intensity fluctuations of spontaneous emissions. By applying post-processing techniques, our 5 × 5 µm 2 micro-LED-based system achieves a PD bandwidth-limited generation rate of 9.375 Gbit/s while successfully passing the required randomness tests outlined by the National Institute of Standards and Technology (NIST). Importantly, systematic testing across micro-LEDs of varying sizes demonstrates consistently high performance, highlighting the robustness of this approach. The compact, small footprint, scalable design, and surface emission characteristics of micro-LEDs pave the way for the development of parallel QRNG-integrated chips, which hold the potential to deliver ultra-high random number generation rates in practical, miniaturized platforms.