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List Of Pseudorandom Number Generators
Random number generation, Random number generators are important in many kinds of technical applications, including physics, engineering or Mathematics, mathematical computer studies (e.g., Monte Carlo method, Monte Carlo simulations), cryptography and gambling (on game servers). This list includes many common types, regardless of quality or applicability to a given use case. Pseudorandom number generators (PRNGs) The following algorithms are pseudorandom number generators. Cryptographic algorithms Cipher algorithms and cryptographic hashes can be used as very high-quality pseudorandom number generators. However, generally they are considerably slower (typically by a factor 2–10) than fast, non-cryptographic random number generators. These include: * Stream ciphers. Popular choices are Salsa20 or Salsa20#ChaCha variant, ChaCha (often with the number of rounds reduced to 8 for speed), ISAAC (cipher), ISAAC, HC-256, HC-128 and RC4#Pseudo-random generation algorithm (PRGA), ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Random Number Generation
Random number generation is a process by which, often by means of a random number generator (RNG), a sequence of numbers or symbols is generated that cannot be reasonably predicted better than by random chance. This means that the particular outcome sequence will contain some patterns detectable in hindsight but impossible to foresee. True random number generators can be ''Hardware random number generator, hardware random-number generators'' (HRNGs), wherein each generation is a function of the current value of a physical environment's attribute that is constantly changing in a manner that is practically impossible to model. This would be in contrast to so-called "random number generations" done by ''pseudorandom number generators'' (PRNGs), which generate numbers that only look random but are in fact predetermined—these generations can be reproduced simply by knowing the state of the PRNG. Various applications of randomness have led to the development of different methods for ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Microsoft Excel
Microsoft Excel is a spreadsheet editor developed by Microsoft for Microsoft Windows, Windows, macOS, Android (operating system), Android, iOS and iPadOS. It features calculation or computation capabilities, graphing tools, pivot tables, and a macro (computer science), macro programming language called Visual Basic for Applications (VBA). Excel forms part of the Microsoft 365 and Microsoft Office suites of software and has been developed since 1985. Features Basic operation Microsoft Excel has the basic features of all spreadsheets, using a grid of ''cells'' arranged in numbered ''rows'' and letter-named ''columns'' to organize data manipulations like arithmetic operations. It has a battery of supplied functions to answer statistical, engineering, and financial needs. In addition, it can display data as line graphs, histograms and charts, and with a very limited three-dimensional graphical display. It allows sectioning of data to view its dependencies on various factors ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
R (programming Language)
R is a programming language for statistical computing and Data and information visualization, data visualization. It has been widely adopted in the fields of data mining, bioinformatics, data analysis, and data science. The core R language is extended by a large number of R package, software packages, which contain Reusability, reusable code, documentation, and sample data. Some of the most popular R packages are in the tidyverse collection, which enhances functionality for visualizing, transforming, and modelling data, as well as improves the ease of programming (according to the authors and users). R is free and open-source software distributed under the GNU General Public License. The language is implemented primarily in C (programming language), C, Fortran, and Self-hosting (compilers), R itself. Preprocessor, Precompiled executables are available for the major operating systems (including Linux, MacOS, and Microsoft Windows). Its core is an interpreted language with a na ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Mersenne Twister
The Mersenne Twister is a general-purpose pseudorandom number generator (PRNG) developed in 1997 by and . Its name derives from the choice of a Mersenne prime as its period length. The Mersenne Twister was created specifically to address most of the flaws found in earlier PRNGs. The most commonly used version of the Mersenne Twister algorithm is based on the Mersenne prime 2^-1. The standard implementation of that, MT19937, uses a 32-bit word length. There is another implementation (with five variants) that uses a 64-bit word length, MT19937-64; it generates a different sequence. ''k''-distribution A pseudorandom sequence x_i of ''w''-bit integers of period ''P'' is said to be ''k-distributed'' to ''v''-bit accuracy if the following holds. : Let trunc''v''(''x'') denote the number formed by the leading ''v'' bits of ''x'', and consider ''P'' of the ''kv''-bit vectors :: (\operatorname_v(x_i), \operatorname_v(x_), \, \ldots, \operatorname_v(x_)) \quad (0\leq i. The Mersenn ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Complementary-multiply-with-carry
In computer science, multiply-with-carry (MWC) is a method invented by George Marsaglia for generating sequences of random integers based on an initial set from two to many thousands of randomly chosen seed values. The main advantages of the MWC method are that it invokes simple computer integer arithmetic and leads to very fast generation of sequences of random numbers with immense periods, ranging from around 2^ to 2^. As with all pseudorandom number generators, the resulting sequences are functions of the supplied seed values. General theory An MWC generator is a special form of Lehmer random number generator x_n = bx_ \bmod p which allows efficient implementation of a prime modulus p much larger than the machine word size. Normal Lehmer generator implementations choose a modulus close to the machine word size. An MWC generator instead maintains its state in base b, so multiplying by b is done implicitly by shifting one word. The base b is typically chosen to equal the compu ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
KISS (algorithm)
KISS ( Keep it Simple Stupid) is a family of pseudorandom number generators introduced by George Marsaglia. Starting from 1998 Marsaglia posted on various newsgroups including sci.math, comp.lang.c, comp.lang.fortran and sci.stat.math several versions of the generators. All KISS generators combine three or four independent random number generators with a view to improving the quality of randomness. KISS generators produce 32-bit or 64-bit random integers, from which random floating-point numbers can be constructed if desired. The original 1993 generator is based on the combination of a linear congruential generator and of two linear feedback shift-register generators. It has a period 295, good speed and good statistical properties; however, it fails the LinearComplexity test in the Crush and BigCrush tests of the TestU01 suite. A newer version from 1999 is based on a linear congruential generator, a 3-shift linear feedback shift-register and two multiply-with-carry generator ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Sophie Germain Prime
In number theory, a prime number ''p'' is a if 2''p'' + 1 is also prime. The number 2''p'' + 1 associated with a Sophie Germain prime is called a . For example, 11 is a Sophie Germain prime and 2 × 11 + 1 = 23 is its associated safe prime. Sophie Germain primes and safe primes have applications in public key cryptography and primality testing. It has been conjectured that there are infinitely many Sophie Germain primes, but this remains unproven. Sophie Germain primes are named after French mathematician Sophie Germain, who used them in her investigations of Fermat's Last Theorem. One attempt by Germain to prove Fermat’s Last Theorem was to let ''p'' be a prime number of the form 8''k'' + 7 and to let ''n'' = ''p'' – 1. In this case, x^n + y^n = z^n is unsolvable. Germain’s proof, however, remained unfinished. Through her attempts to solve Fermat's Last Theorem, Germain developed a result now known as Germain's Theore ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Journal Of Computational Physics
The ''Journal of Computational Physics'' is a bimonthly scientific journal covering computational physics that was established in 1966 and is published by Elsevier. As of 2015, its editor-in-chief is Rémi Abgrall (University of Zurich). According to the ''Journal Citation Reports'', ''Journal of Computational Physics'' has a 2021 impact factor of 4.645, ranking it third out of 56 in the category ''Physics, Mathematical''. See also *List of fluid mechanics journals This is a list of scientific journals related to the field of fluid mechanics. {{columns-list, colwidth=30em, *'' AIAA Journal'' *'' Annual Review of Fluid Mechanics'' *'' Experiments in Fluids'' *'' Fluid Dynamics Research'' *'' Flow, Turbulence ... References External links * English-language journals Physics journals Elsevier academic journals Academic journals established in 1966 Biweekly journals Computational modeling journals {{physics-journal-stub ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
MIXMAX Generator
The MIXMAX generator is a family of pseudorandom number generators (PRNG) and is based on Anosov C-systems (Anosov diffeomorphism) and Kolmogorov K-systems ( Kolmogorov automorphism). It was introduced in a 1986 preprint by G. Savvidy and N. Ter-Arutyunyan-Savvidy and published in 1991. A fast implementation in C/ C++ of the generator was developed by Konstantin Savvidy. It is genuine 64-bit generator. The period of the generator is 10^ and the Kolmogorov entropy is 8679.2 for the matrix size N = 240. That generator occupies less than 2 kb, and if a smaller generator state is required, a ''N'' = 17 version with less than 200 bytes memory requirement also exists. The generator works on most 64-bit systems, including 64-bit Linux flavors and Intel Mac. It has also been tested on PPC and ARM architectures. The latest version also runs on 32-bit systems and on Windows. The generator is equally usable with C++ programs, has been chosen as the default generator in CLHEP for u ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
ACORN PRNG
The ACORN or ″Additive Congruential Random Number″ generators are a robust family of pseudorandom number generators (PRNGs) for sequences of uniformly distributed pseudo-random numbers, introduced in 1989 and still valid in 2019, thirty years later. Introduced by R.S.Wikramaratna,Wikramaratna, R.S. (1989). ACORN — A new method for generating sequences of uniformly distributed Pseudo-random Numbers. Journal of Computational Physics. 83. 16-31. ACORN was originally designed for use in geostatistical and geophysical Monte Carlo simulations, and later extended for use on parallel computers.R.S. Wikramaratna, Pseudo-random number generation for parallel processing — A splitting approach, SIAM News 33 (9) (2000). Over the ensuing decades, theoretical analysis (formal proof of convergence and statistical results), empirical testing (using standard test suites), and practical application work have continued, despite the appearance and promotion of other better-known ut not ne ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
C++11
C++11 is a version of a joint technical standard, ISO/IEC 14882, by the International Organization for Standardization (ISO) and International Electrotechnical Commission (IEC), for the C++ programming language. C++11 replaced the prior version of the C++ standard, named C++03, and was later replaced by C++14. The name follows the tradition of naming language versions by the publication year of the specification, though it was formerly named ''C++0x'' because it was expected to be published before 2010. Although one of the design goals was to prefer changes to the libraries over changes to the core language, C++11 does make several additions to the core language. Areas of the core language that were significantly improved include multithreading support, generic programming support, uniform initialization, and performance. Significant changes were also made to the C++ Standard Library, incorporating most of the C++ Technical Report 1 (TR1) libraries, except the library ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
