High-quality Random Number Generator Research Articles

Superior probabilistic computing using operationally stable probabilistic-bit constructed by manganite nanowire

Abstract Probabilistic computing has emerged as a viable approach to treat optimization problems. To achieve superior computing performance, the key aspect during computation is massive sampling and tuning on the probability states of each probabilistic bit (p-bit), demanding its high stability under extensive operations. Here, we demonstrate a p-bit constructed by manganite nanowire that shows exceptionally high stability. The p-bit contains an electronic domain that fluctuates between metallic (low resistance) and insulating (high resistance) states near its transition temperature. The probability for the two states can be directly controlled by nano-ampere electrical current. Under extensive operations, the standard error of its probability values is less than 1.3%. Simulations show that our operationally stable p-bit plays the key role to achieve correct inference in Bayesian network by strongly suppressing the relative error, displaying the potential for superior computing performance. Our p-bit also serves as high quality random number generator without extra data-processing, beneficial for cryptographic applications.

A High-Performance FPGA PRNG Based on Multiple Deep-Dynamic Transformations.

Pseudo-random number generators (PRNGs) are important cornerstones of many fields, such as statistical analysis and cryptography, and the need for PRNGs for information security (in fields such as blockchain, big data, and artificial intelligence) is becoming increasingly prominent, resulting in a steadily growing demand for high-speed, high-quality random number generators. To meet this demand, the multiple deep-dynamic transformation (MDDT) algorithm is innovatively developed. This algorithm is incorporated into the skewed tent map, endowing it with more complex dynamical properties. The improved one-dimensional discrete chaotic mapping method is effectively realized on a field-programmable gate array (FPGA), specifically the Xilinx xc7k325tffg900-2 model. The proposed pseudo-random number generator (PRNG) successfully passes all evaluations of the National Institute of Standards and Technology (NIST) SP800-22, diehard, and TestU01 test suites. Additional experimental results show that the PRNG, possessing high novelty performance, operates efficiently at a clock frequency of 150 MHz, achieving a maximum throughput of 14.4 Gbps. This performance not only surpasses that of most related studies but also makes it exceptionally suitable for embedded applications.

PiRATe: A Comprehensive Set of Statistical Tests for Evaluation of Quantum Random Number Generators

As true random numbers are essential for many applications, high-quality Random Number Generators (RNGs) are highly demanded. Several different statistical test suites have been developed to evaluate the quality of RNGs. However, some programming skills are required to work with these statistical tests as they are not available as self-contained software and often are without a Graphical User Interface (GUI). In this work, we have developed PiRATe (Pi Randomness Assessment Test) an easy-to-use wrapper software for the assessment of RNGs using a comprehensive set of statistical tests, including DIEHARDER, NIST SP800-22, NIST SP800-90B, Entropy-Nonlinearity-Test (ENT), Borel Normality, and four Chaitin-Schwartz-Solovay-Strassen tests. We then used PiRATe to evaluate the quality of five different (Commercial and Experimental) Quantum Random Number Generators (QRNGs).

Critical Ising system testing of high-quality random number generators

Specialized hardware implemented on field programmable gate array (FPGA) is used to simulate critical 2D Ising lattices up to 40962. Four mainstream, high-quality pseudorandom number generators (PRNGs) including Xorshift, Mersenne Twister, Xorwow, and ALFG are tested on this system, and three of them are found to misbehave with different degree of confidence levels. It is observed that PRNGs with quality issues tend to misbehave in critical Ising systems and the ones with bigger issues start to misbehave in smaller critical Ising systems and vice versa. The size at which a PRNG misbehaves is proposed as a measure of a PRNG’s quality.

Design and FPGA Implementation of a Pseudorandom Number Generator Based on a Four-Wing Memristive Hyperchaotic System and Bernoulli Map

Random numbers are widely used in the fields of computer, digital signature, secure communication and information security. Especially in recent years, with the large-scale application of smart card and the demand of information security, the demand for high-quality random number generator is increasingly urgent. With the development of the theory of non-linear systems, the design of pseudorandom number generator (PRNG) for chaotic behavior of non-linear systems provides a new theoretical basis and implementation method. This paper presents a PRNG based on a no-equilibrium four-wing memristive hyperchaotic system (FWMHS) and its implementation on Field Programmable Gate Array (FPGA) board. In order to increase the output throughput and the statistical quality of the generated bit sequences, we propose the PRNG design which uses a dual entropy sources architecture with FWMHS and Bernoulli map. Simulation and experimental results verifying the feasibility of the FWMHS are also given. Then, the proposed PRNG system is modeled and simulated on the Vivado 2018.3 platform, and implemented on the Xilinx ZYNQ-XC7Z020 FPGA evaluation board. The maximum operating frequency has been achieved as 135.04 MHz with a speed of 62.5 Mbit/s. Finally, we have experimentally verified that the binary data obtained by this dual entropy sources architecture pass the tests of NIST 800.22, ENT and AIS.31 statistical test suites with XOR function post-processing for a high throughput speed. The security analysis is carried out by means of dynamical degradation, key space, key sensitivity, correlation and information entropy. Statistical tests and security analysis show that it has good pseudorandom characteristics and can be used in chaos-based cryptographic applications at hardware or software implementation.

Quantum-key-distribution protocol with pseudorandom bases

Quantum key distribution (QKD) offers a way for establishing information-theoretically secure communications. An important part of QKD technology is a high-quality random number generator (RNG) for quantum states preparation and for post-processing procedures. In the present work, we consider a novel class of prepare-and-measure QKD protocols, utilizing additional pseudorandomness in the preparation of quantum states. We study one of such protocols and analyze its security against the intercept-resend attack. We demonstrate that, for single-photon sources, the considered protocol gives better secret key rates than the BB84 and the asymmetric BB84 protocol. However, the protocol strongly requires single-photon sources.

A revision of the subtract-with-borrow random number generators

The most popular and widely used subtract-with-borrow generator, also known as RANLUX, is reimplemented as a linear congruential generator using large integer arithmetic with the modulus size of 576 bits. Modern computers, as well as the specific structure of the modulus inferred from RANLUX, allow for the development of a fast modular multiplication — the core of the procedure. This was previously believed to be slow and have too high cost in terms of computing resources. Our tests show a significant gain in generation speed which is comparable with other fast, high quality random number generators. An additional feature is the fast skipping of generator states leading to a seeding scheme which guarantees the uniqueness of random number sequences. Program summary/New version program summaryProgram Title: RANLUX++Licensing provisions: GPLv3Programming language: C++, C, Assembler

FPGA Implementation of High Quality Random Number Generator Using LUT Based Shift Registers

Random numbers are required for wide range of applications such as in encryption of data, testing and Monte-Carlo simulations. So, hardware implementation of random number generator is inevitable. FPGA Optimized RNGs are more efficient in terms of resource than software based RNGs. The LUT-SR RNG, a type of FPGA RNG in which LUTs are configured into shift registers with varying length. The existing work provides a midpoint between LUT-OPT RNG and LUT-FIFO RNG. In the enhancement work, we proposed modified LUT-SR RNG which provides more randomness, quality and minimum resource utilization than the existing LUT-SR generator. Inorder to improve the randomness quadratic residue method is employed. Linear Congruential Generator (LCG) algorithm, one of the oldest and well known algorithm is also used in modified LUT-SR RNG to enhance the performance. Here design was made by VHDL programming language by using Xilinx software.

A Fully Pipelined Power-Optimization Implementation of Monte Carlo Based SSTA on FPGA

Monte Carlo based SSTA serves as the golden standard against the alternative SSTA algorithms. The efficient implementation of MC-SSTA is performed by repeatedly executing ordinary STA using a set of randomly generated delay samples. The FPGA device is used as a target device onto which the RTL description is mapped, which acts as a dedicated STA engine. We leverage the path level and gate level parallelisms and the power optimizations of normal distribution random number generators based on central limit theorem. The accuracy is compared with the Mersenne Twister and Box Muller Methods which are high quality random number generators.

A Fully Integrated HF-Band Passive RFID Tag IC Using 0.18-$\mu\hbox{m}$ CMOS Technology for Low-Cost Security Applications

We present a fully integrated small-size HF-band passive RF identification (RFID) tag chip with authentication and security functions. The design of the RF transceiver and digital control of the tag IC is based on the International Organization for Standardization-14443 type-B protocol. The design of the key analog part of the tag IC is presented, which includes a robust demodulator for 10% amplitude shift keying envelope detection, a high-quality random number generator, and a voltage regulator that can handle a range of output load currents. To implement the secure data transaction with a reader, a 128-b advanced encryption standard (AES) with a new cyclic key generation is used for the data encryption and decryption. An on-chip 4-kb electrically erasable programmable ROM (EEPROM) is used to support the AES operation, tag identification, and tag self-destruction. The read and write accesses of the EEPROM are performed using a 128-b wide buffer with self-timed bursts. The tag chip is fabricated in a one-poly six-metal low-power 0.18-μm CMOS process with a CoSi <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> Schottky diode and EEPROM process. Using the scaled-down CMOS technology, the size of the tag chip is only 1.1 × 1 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , providing a cost-effective solution for everyday RFID applications.

Single-electron random-number generator (RNG) for highly secure ubiquitous computing applications

Since the security of all modern cryptographic techniques relies on unpredictable and irreproducible digital keys generated by random-number generators (RNGs), the realization of high-quality RNG is essential for secure communications. In this report, a new RNG, which utilizes single-electron phenomena, is proposed. A room-temperature operating silicon single-electron transistor (SET) having nearby an electron pocket is used as a high-quality, ultra-small RNG. In the proposed RNG, stochastic single-electron capture/emission processes to/from the electron pocket are detected with high sensitivity by the SET, and result in giant random telegraphic signals (GRTS) on the SET current. It is experimentally demonstrated that the single-electron RNG generates extremely high-quality random digital sequences at room temperature, in spite of its simple configuration. Because of its small-size and low-power properties, the single-electron RNG is promising as a key nanoelectronic device for future ubiquitous computing systems with highly secure mobile communication capabilities.

Some long-period random number generators using shifts and xors

Marsaglia recently introduced a class of `xorshift' random number generators with periods \(2^n-1\) for \(n = 32, 64,\ldots\). Here Marsaglia's xorshift generators are generalised to obtain fast and high quality random number generators with extremely long periods. Whereas random number generators based on primitive trinomials may be unsatisfactory, because a trinomial has very small weight, these new generators can be chosen so that their minimal polynomials have a large number of non-zero terms and, hence, a large weight. A computer search using Magma found good random number generators for\(~n\) a power of two up to 4096. These random number generators are implemented in a free software package \texttt{xorgens}.

An efficient high quality random number generator for multi-programmed systems

This document presents an efficient, high quality random number generator for multi-programmed environments, in particular for UNIX/Linux and Windows systems. The algorithm uses a system's notion of the time, given by a high-precision real-time count

An efficient high quality random number generator for multi-programmed systems

This document presents an efficient, high quality random number generator for multi-programmed environments, in particular for UNIX/Linux and Windows systems. The algorithm uses a system's notion o...

Moly flow..er—the computer program for calculation of vacuum system conductance

The paper presents a new computer program for calculating a conductance with a high precision, based on the Monte-Carlo (MC) method. The high accuracy of the calculations has been obtained by using high-quality random number generators (RNG), specially selected for this purpose. This allows us to extend the application field of the MC simulations and to reduce the uncertainty of the results to below 10 −5. The paper describes the principles of the program conception, compares the results obtained for various classes of RNG and also gives the values of the Clausing-type factors for elementary shapes.

TESTS OF RANDOM NUMBER GENERATORS USING ISING MODEL SIMULATIONS

Large-scale Monte Carlo simulations require high-quality random number generators to ensure correct results. The contrapositive of this statement is also true — the quality of random number generators can be tested by using them in large-scale Monte Carlo simulations. We have tested many commonly-used random number generators with high precision Monte Carlo simulations of the 2-d Ising model using the Metropolis, Swendsen-Wang, and Wolff algorithms. This work is being extended to the testing of random number generators for parallel computers. The results of these tests are presented, along with recommendations for random number generators for high-performance computers, particularly for lattice Monte Carlo simulations.

A portable high-quality random number generator for lattice field theory simulations

The theory underlying a proposed random number generator for numerical simulations in elementary particle physics and statistical mechanics is discussed. The generator is based on an algorithm introduced by Marsaglia and Zaman, with an important added feature leading to demonstrably good statistical properties. It can be implemented exactly on any computer complying with the IEEE-754 standard for single-precision floating-point arithmetic.