Quantum random number generators are a burgeoning technology used for a variety of applications, including modern security and encryption systems. Typical methods exploit an entropy source combined with an extraction or bit generation circuit in order to produce a random string. In integrated designs there is often little modelling or analytical description of the entropy source, circuit extraction and post-processing provided. In this work, we first discuss theory on the quantum random flip-flop (QRFF), which elucidates the role of circuit imperfections that manifest themselves in bias and correlation. Then, a Verilog-AMS model is developed in order to validate the analytical model in simulation. A novel transistor implementation of the QRFF circuit is presented, which enables compensation of the degradation in entropy inherent to the finite non-symmetric transitions of the random flip-flop. Finally, a full system containing two independent arrays of the QRFF circuit is manufactured and tested in a 55 nm Bipolar-CMOS-DMOS (BCD) technology node, demonstrating bit generation statistics that are commensurate to the developed model. The full chip is able to generate 3.3 Gbps of data when operated with an external LED, whereas an individual QRFF can generate 25 Mbps each of random data while maintaining a Shannon entropy bound > 0.997, which is one of the highest per pixel bit generation rates to date. NIST STS is used to benchmark the generated bit strings, thereby validating the QRFF circuit as an excellent candidate for fully-integrated QRNGs.
Quantum random number generators are a burgeoning technology used for a variety of applications, including modern security and encryption systems. Typical methods exploit an entropy source combined with an extraction or bit generation circuit in order to produce a random string. In integrated designs there is often little modelling or analytical description of the entropy source, circuit extraction and post-processing provided. In this work, we first discuss theory on the quantum random flip-flop (QRFF), which elucidates the role of circuit imperfections that manifest themselves in bias and correlation. Then, a Verilog-AMS model is developed in order to validate the analytical model in simulation. A novel transistor implementation of the QRFF circuit is presented, which enables compensation of the degradation in entropy inherent to the finite non-symmetric transitions of the random flip-flop. Finally, a full system containing two independent arrays of the QRFF circuit is manufactured and tested in a 55 nm Bipolar-CMOS-DMOS (BCD) technology node, demonstrating bit generation statistics that are commensurate to the developed model. The full chip is able to generate 3.3 Gbps of data when operated with an external LED, whereas an individual QRFF can generate 25 Mbps each of random data while maintaining a Shannon entropy bound > 0.997, which is one of the highest per pixel bit generation rates to date. NIST STS is used to benchmark the generated bit strings, thereby validating the QRFF circuit as an excellent candidate for fully-integrated QRNGs.
Quantum random number generators (QRNGs) are a burgeoning technology used for a variety of applications, including modern security and encryption systems. Typical methods exploit an entropy source combined with an extraction or bit generation circuit in order to produce a random string. In integrated designs, there is often little modeling or analytical description of the entropy source, circuit extraction, and post-processing provided. In this work, we present a single-photon avalanche diode (SPAD)-based QRNG design, which utilizes the quantum random flip-flop (QRFF) method. Extensive modeling of detector and circuit imperfections that result in entropy degradation is performed. A new method to analytically model serial autocorrelations of the proposed bit generation method, which includes detector dead time, is proposed. Then, a Verilog-AMS model is developed in order to validate the analytical model in simulation. A novel transistor implementation of the QRFF circuit is presented, which enables compensation of the degradation in entropy inherent to the finite non-symmetric transitions of the random flip-flop. Finally, a full system containing two independent arrays of the QRFF circuit is manufactured and tested in a 55-nm bipolar–CMOS–DMOS (BCD) technology node, demonstrating bit generation statistics that are commensurate to the developed model. The full chip is able to generate 3.3 Gb/s of data when operated with an external LED. Pixelwise and spatial analysis of bias and correlation is performed. NIST STS (SP 800-22) and SP 800-90B are used to benchmark the generated bit strings.
For globally connected devices like smart phones, personal computers and Internet-of-things devices, the ability to generate random numbers is essential for execution of cryptographic protocols responsible for information security. Generally, a random number generator should be small, robust, utilize as few hardware and energy resources as possible, yet provide excellent randomness at a high enough speed (bitrate) for a given purpose. In this work we present a quantum random number generator (QRNG) which makes use of a photoelectric effect in single-photon avalanche diodes (SPADs) as a source of randomness and is scalable to any desired bitrate. We use the random flip-flop method in which random bits are obtained by periodic sampling of a randomly toggling flip-flop. For the first time we investigate this method in detail and find that, out of two main imperfections, bias is due only to hardware imperfections while autocorrelation predominantly resides with the method itself. SPADs are integrated on a silicon chip together with passive quenching and digital pulse-shaping circuitry, using a standard 180 nm CMOS process. A separate FPGA chip derives random numbers from the detection signals. The basic QRNG cell, made of only two SPADs and a few logic circuits, can generate up to 20 Mbit/s that pass NIST statistical tests without any further postprocessing. This technology allows integration of a QRNG on a single silicon chip using readily available industrial processes.
This brief presents a high-speed quantum random number generator (QRNG) based on the Quantum Random FlipFlop (QRFF) architecture, utilizing two single-photon avalanche diodes (SPADs) per pixel. The design is implemented using the Samsung 28 nm CMOS process. Each pixel integrates a pair of SPAD detectors, following the QRFF model, enabling a significant improvement in output speed compared to conventional QRFF configurations using a single detector. Experimental results demonstrate that a single pixel achieves a throughput of up to 2 Mbps. Furthermore, the generated random numbers successfully pass the NIST statistical test suite without requiring any postprocessing.
Abstract Random number generation plays a crucial role in modern cryptographic systems , where true randomness is required for secure key generation and data protection. Conventional pseudo random generators lack sufficient entropy and introduce predictability. Quantum Random Number Generators (QRNGs), based on quantum phenomena such as single photon detection and offer enhanced unpredictability and security. In this work, we present the design and hardware realization of a SPAD (Single Photon Avalanche Diode) based Quantum Random Number Generator using a complete RTL to GDS flow. A behavioural Verilog model of SPAD operation was developed, introducing photon pulse detection, dead time effects, and noise-based entropy monitoring. The design was simulated using several EDA tools are utilized to validate functionality. Subsequently, the RTL was Synthesized, Placed, Routed and verified to generate a GDSII layout. The proposed implementation demonstrates a feasible pathway for integrating quantum enhanced random ness into secure hardware systems. The RTL to GDSII realization confirms suitability for Application Specific Integration Circuit (ASIC) fabrication, enabling cryptographic applications such as Quantum Key Distribution (QKD) and hardware security module for low power circuits. By using Non-linear feedback shift Register (NLFSR) to enhance randomness extraction and output Bit rates. robust randomness statistics verified by NIST test, and a total power consumption of only 0.272 m Watts substantially lower than 1 conventional CMOS random number generators. This work establishes a scal-able framework for future quantum entropy sources in Secure embedded systems, validated by complete timing, power and random ness test results.
In today's digital life, security and encryption are becoming more and more important. As random number generators are a fundamental block of security and encryption, it is crucial to guarantee that these devices operate securely. Random numbers are usually generated in two ways; pseudo random number generators (PRNGs) and true random random number generators (TRNGs). PRNGs output a sequence based on a seed and a mathematical function. The deterministic nature of pseudo RNG devices can result in the PRNG not being applicable for all protocols, in which case TRNGs are needed. Almost all strong cryptography requires TRNGs to generate keys. The difference is that these devices instead rely on real world physics in order to generate a random number. The TRNG implementation explored in this thesis makes use of the quantum mechanical properties of photons. TRNGs making use of this principle of elementary quantum mechanical decision making are called quantum random number generators (QRNGs). This source of entropy provided by photons can be extracted by utilizing SPADs. QRNG devices based on SPADs have been made before in different ways, however there are still large grounds undiscovered when concerning SPAD based designs. As SPAD based QRNGs can be completely produced using CMOS technology, a world of possibilities open, including integration with already existing designs. Different aspects of SPAD QRNG designs will be discussed in this thesis; size, speed, hybrid designs and QRNG test-benching. The first part of the exploration focuses on creating an as small as possible QRNG. This resulted in a QRNG design which is as small as just one flip-flop and one SPAD, which is the smallest QRNG at the time of writing to the authors knowledge. Simulations show that the device is able to run up to 25 Mb/s using a SPAD with low deadtime. This device has been produced using 140nm technology by STMicroelectronics. The second part of the exploration, delves into how fast a SPAD based QRNG can be. The main goals here were to make the fastest possible QRNG with good scalability characteristics. This resulted in a design proposition based on the difference in the time of flight of two photons. This design is simulated using Matlab, and can reach 70 Mb/s per SPAD-duo depending on the deadtime of the SPAD used. When using a SPAD with a deadtime of 1us, the scaled up design needs only 16% of the SPADS needed by a state-of-the-art SPAD based QRNG design based on simulations. The amount of SPADs needed however schales almost linearly with a lower deadtime, having the potential to need only a fraction of the SPADs needed by the state-of-the-art in order to reach the same speeds. Then the concept of hybrid devices is explored, making use of a combination of PRNG and QRNG systems. The first hybrid design proposed is a design in which a very small QRNG is used to generate the key for multiple secure PRNG systems. The PRNG system used in this design is a trivium stream cypher. The design is completely written in VHDL except for the external QRNG. It then has been compiled and simulated using ModelSim, again using 140nm technology by STMicroelectronics. This resulted in a design which is able to reach speeds of 640 Gb/s, while using a total area of 99936 um2. The second hybrid device proposes a LFSR based design, which makes use of multiple very small QRNG devices to influence the function that the LFSR implements in order to increase the security. The last part of the exploration explores how it can be made easier and faster to test QRNG designs in an early design stage more accurately. As the source of entropy is quantum, the only risk of affecting the randomness is purely in which form the data of the photons is processed. By creating a chip which is able to extract the time of flight and the exact location of where the photon hit, testing potential QRNG devices can already be done in an early design stage with real-time data. A part of the chip that measures the time of flight of the photons arriving, has been designed in 40nm technology by STMicroelectronics. This part is a novel counter based on the principle of Gray counting, and is simulated extensively using extracted layout simulations. These simulations show that the device is able to run at speeds up to 3.6 GHz.
The security of electronic devices has become a key requisite for the rapidly-expanding pervasive and hyper-connected world. Robust security protocols ensuring secure communication, device's resilience to attacks, authentication control and users privacy need to be implemented. Random Number Generators (RNGs) are the fundamental primitive in most secure protocols but, often, also the weakest one. Establishing security in billions of devices requires high quality random data generated at a sufficiently high throughput. On the other hand, the RNG should exhibit a high integration level with on-chip extraction to remove, in real time, potential imperfections. We present the first integrated Quantum RNG (QRNG) in a standard CMOS technology node. The QRNG is based on a parallel array of independent Single-Photon Avalanche Diodes (SPADs), homogeneously illuminated by a DC-biased LED, and co-integrated logic circuits for postprocessing. We describe the randomness generation process and we prove the quantum origin of entropy. We show that co-integration of combinational logic, even of high complexity, does not affect the quality of randomness. Our CMOS QRNG can reach up to 400 Mbit/s throughput with low power consumption. Thanks to the use of standard CMOS technology and a modular architecture, our QRNG is suitable for a highly scalable solution.