|
List Of Random Number Generators
Random number generators are important in many kinds of technical applications, including physics, engineering or mathematical computer studies (e.g., Monte Carlo simulations), cryptography and gambling (on game servers). This list includes many common types, regardless of quality. Pseudorandom number generators (PRNGs) Whenever using a pseudorandom number generator, keep in mind John von Neumann's dictum "Anyone who considers arithmetical methods of producing random digits is, of course, in a state of sin." 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 ChaCha (often with the number of rounds reduced to 8 for speed), ISAAC, HC-128 an ... [...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 that cannot be reasonably predicted better than by random chance is generated. This means that the particular outcome sequence will contain some patterns detectable in hindsight but unpredictable to foresight. True random number generators can be '' hardware random-number generators'' (HRNGS) that generate random numbers, 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) that generate numbers that only look random but are in fact pre-determined—these generations can be reproduced simply by knowing the state of the PRNG. Various applications of randomness have led to the development of several different metho ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Microsoft Excel
Microsoft Excel is a spreadsheet developed by Microsoft for Microsoft Windows, Windows, macOS, Android (operating system), Android and iOS. 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 Office suite of software. 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 for different perspectives (using ''pivot tables'' and the ''sce ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
R (programming Language)
R is a programming language for statistical computing and graphics supported by the R Core Team and the R Foundation for Statistical Computing. Created by statisticians Ross Ihaka and Robert Gentleman, R is used among data miners, bioinformaticians and statisticians for data analysis and developing statistical software. Users have created packages to augment the functions of the R language. According to user surveys and studies of scholarly literature databases, R is one of the most commonly used programming languages used in data mining. R ranks 12th in the TIOBE index, a measure of programming language popularity, in which the language peaked in 8th place in August 2020. The official R software environment is an open-source free software environment within the GNU package, available under the GNU General Public License. It is written primarily in C, Fortran, and R itself (partially self-hosting). Precompiled executables are provided for various operating systems. R ... [...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 fact that its period length is chosen to be a Mersenne prime. The Mersenne Twister was designed specifically to rectify most of the flaws found in older 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. Application Software The Mersenne Twister is used as default PRNG by the following software: * Programming languages: Dyalog APL, IDL, R, Ruby, Free Pascal, PHP, Python (also available in NumPy, however the default was changed to PCG64 instead as of version 1.17),, CMU Common Lisp, Embeddable Common Lisp, Steel Bank Common Lisp, Julia (up to Julia 1.6 LTS, still available in lat ... [...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 com ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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 com ... [...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 generat ... [...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 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 Theorem which states that if ''p'' is an odd prime and 2''p'' + 1 is also prime, then ''p'' must divide ''x'', ''y'', or ''z.'' Otherwise, x^n + y^n \neq z^n. This case where ''p'' does not divide ''x'', ''y'', or ''z'' i ... [...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 and ... References External links * English-language journals Physics journals Elsevier academic journals Publications established in 1966 Biweekly 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. 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 CLHEP (short for ''A Class Library ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
ACORN PRNG
The ACORN or ″Additive Congruential Random Number″ generators are a robust family of PRNGs ( pseudorandom number generators) 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 simulation Monte Carlo methods, or Monte Carlo experiments, are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. The underlying concept is to use randomness to solve problems that might be determini ...s, 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 ens ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
C++11
C++11 is a version of the ISO/IEC 14882 standard for the C++ programming language. C++11 replaced the prior version of the C++ standard, called 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 of mathematical special functions. C++11 was published as ''ISO/IEC 14882:2011'' in September 2011 and is available for a fee. The worki ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
