MersenneTwister
E440656
MersenneTwister is a widely used pseudorandom number generator algorithm known for its long period and high-quality statistical properties.
All labels observed (8)
How this entity was disambiguated
This entity first appeared as the object of triple T4443366 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MersenneTwister Context triple: [Random, exportsFunction, MersenneTwister]
-
A.
cuRAND
cuRAND is NVIDIA's GPU-accelerated random number generation library designed to efficiently produce high-quality random numbers for parallel applications using CUDA.
-
B.
Blum–Blum–Shub pseudorandom number generator
The Blum–Blum–Shub pseudorandom number generator is a cryptographically secure generator based on the hardness of factoring large composite numbers, widely studied in theoretical computer science and cryptography.
-
C.
Blum–Micali pseudorandom number generator
The Blum–Micali pseudorandom number generator is a foundational cryptographic algorithm that produces provably secure pseudorandom bits based on number-theoretic hardness assumptions.
-
D.
Monte Carlo
Monte Carlo is a famous district of Monaco renowned for its luxury casinos, upscale resorts, and role as a glamorous hub for high-end tourism and events like the Monaco Grand Prix.
-
E.
Monte Carlo method
The Monte Carlo method is a computational technique that uses random sampling to approximate numerical results, especially for complex integrals, simulations, and probabilistic systems.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MersenneTwister Target entity description: MersenneTwister is a widely used pseudorandom number generator algorithm known for its long period and high-quality statistical properties.
-
A.
cuRAND
cuRAND is NVIDIA's GPU-accelerated random number generation library designed to efficiently produce high-quality random numbers for parallel applications using CUDA.
-
B.
Blum–Blum–Shub pseudorandom number generator
The Blum–Blum–Shub pseudorandom number generator is a cryptographically secure generator based on the hardness of factoring large composite numbers, widely studied in theoretical computer science and cryptography.
-
C.
Blum–Micali pseudorandom number generator
The Blum–Micali pseudorandom number generator is a foundational cryptographic algorithm that produces provably secure pseudorandom bits based on number-theoretic hardness assumptions.
-
D.
Monte Carlo
Monte Carlo is a famous district of Monaco renowned for its luxury casinos, upscale resorts, and role as a glamorous hub for high-end tourism and events like the Monaco Grand Prix.
-
E.
Monte Carlo method
The Monte Carlo method is a computational technique that uses random sampling to approximate numerical results, especially for complex integrals, simulations, and probabilistic systems.
- F. None of above. chosen
Statements (50)
| Predicate | Object |
|---|---|
| instanceOf |
PRNG algorithm
ⓘ
pseudorandom number generator ⓘ |
| basedOn | Mersenne prime 2^19937 − 1 ⓘ |
| designedBy |
Makoto Matsumoto
ⓘ
Takuji Nishimura ⓘ |
| designYear | 1997 ⓘ |
| hasAbbreviation | MT ⓘ |
| hasAlgorithmStep |
tempering transformation
ⓘ
twist transformation ⓘ |
| hasEquidistribution |
311-dimensionally equidistributed for 64-bit output (MT19937-64)
ⓘ
623-dimensionally equidistributed for 32-bit output ⓘ |
| hasFullName |
Mersenne Twister pseudorandom number generator
ⓘ
linked to:
MersenneTwister
|
| hasLicense | permissive free software license ⓘ |
| hasOutputRange |
[0, 2^32 − 1] for MT19937
ⓘ
[0, 2^64 − 1] for MT19937-64 ⓘ |
| hasPeriod | 2^19937 − 1 ⓘ |
| hasProperty |
deterministic
ⓘ
fast generation speed ⓘ high-quality statistical properties ⓘ long period ⓘ not cryptographically secure ⓘ |
| hasPublicationTitle |
Mersenne Twister: A 623-dimensionally equidistributed uniform pseudorandom number generator
ⓘ
linked to:
MersenneTwister
|
| hasPublicationYear | 1998 ⓘ |
| hasSeedingRequirement | requires 624 32-bit integers for full state (MT19937) ⓘ |
| hasStateSizeBits | 19937 ⓘ |
| hasStateVectorLength | 624 ⓘ |
| hasVariant |
MT19937
ⓘ
linked to:
MersenneTwister
MT19937-64 ⓘ
linked to:
MersenneTwister
TinyMT ⓘ |
| hasWeakness |
poor behavior in some high-dimensional equidistribution tests for lower bits
ⓘ
predictable output if internal state is recovered ⓘ |
| hasWordSizeBits |
32
ⓘ
64 ⓘ |
| influenced |
development of SIMD-oriented Fast Mersenne Twister (SFMT)
ⓘ
development of TinyMT ⓘ |
| isImplementedIn |
C
ⓘ
C++ ⓘ Java ⓘ Python ⓘ many other programming languages ⓘ |
| isNotRecommendedFor | cryptographic applications ⓘ |
| isPublishedIn | ACM Transactions on Modeling and Computer Simulation ⓘ |
| isUsedIn |
C++ standard library <random> as std::mt19937
ⓘ
linked to:
MersenneTwister
MATLAB as one of the RNG options ⓘ PHP standard library as default RNG for mt_rand ⓘ Python random module (CPython) as core generator before Python 3.12 ⓘ R programming language as default RNG for many years ⓘ Ruby standard library as default RNG ⓘ many simulation and Monte Carlo applications ⓘ |
| temperingPurpose | improve equidistribution of output bits ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: MersenneTwister Description of subject: MersenneTwister is a widely used pseudorandom number generator algorithm known for its long period and high-quality statistical properties.
Referenced by (11)
Full triples — surface form annotated when it differs from this entity's canonical label.
linked to: MersenneTwister
subject linked to:
MersenneTwister
linked to: MersenneTwister
subject linked to:
MersenneTwister
linked to: MersenneTwister
subject linked to:
MersenneTwister
linked to: MersenneTwister
subject linked to:
MersenneTwister
linked to: MersenneTwister
Mersenne Twister
→
hasPublicationTitle
→
Mersenne Twister: A 623-dimensionally equidistributed uniform pseudorandom number generator
ⓘ
subject linked to:
MersenneTwister
linked to: MersenneTwister
linked to: MersenneTwister
linked to: MersenneTwister