2 Capitalization, mostly
source | link

somewhatSomewhat like sorting algorithms in this regard, there is no "one size fits all" PRNG. differentDifferent ones are used for different purposes and there is a wide variety of design criteria and uses. itIt is possible to misapply PRNGs, such as using one for cryptography that it is not designed for. wikipediasWikipedia's entry on Mersenne twisterTwister also mentions that it was not designed for "Monte Carlo tests-Carlo simulations that require independent PRNGs"random number generators".

asAs noted on wikipediaWikipedia, this PRNG is indeed used in a large number of programming languages and applications even as a default PRNG. itIt would take a near-sociological analysis to explain why one PRNG is favored. someSome possible factors that may be contributing to this PRNG:

  • authorThe Author has good/ strong scientific credentials in area and has been working in PRNGs for decades.

  • itIt was specifically designed to be superior to other methods at the time.

  • The author is engaged in implementations and tracking them, also contributing to them. someSome PRNGs are more theoretical and the authors do not always concern themselves with actual implementations.

  • theThe system is well supported/ updatedupdated on a web page.

  • newNew versions of the PRNG have been developed to deal with weaknesses. thereThere is not one single Mersenne Twister algorithm, its more like different versions and a family of variants which can handle different needs.

  • itIt has been extensively analyzed/ testedtested by standard randomness analysis software and passed, by independent authorities.

  • thereThere is a known effect measured with egfor web sites and many other contexts eglike scientific citations etc called "preferential attachment" which can be measured; itsmeasured. It's basically where long established historical sources accrue further usage. suchSuch an effect could explain PRNG choices over time.

inIn other words, you are asking about a phenomenon of "popularity" which is associated and interrelated with human choices and is not strictly tied to particular qualities, but is a sort of complex/ emergentemergent property and interplay between different algorithms, users, and environment/ usageusage contexts etc.

hereHere is one such independent analysis of the algorithm Mersenne Twister – A Pseudo Random Number Generator and its Variants by Jagannatam (15p). theThe concluding paragraph is essentially an answer to your question. quoting only the 1st few sentences:

Mersenne Twister is theoretically proven to be a good PRNG, with a long period and high equidistribution. It is extensively used in the fields of simulation and modulation. The defects found by the users have been corrected by the inventors. MT has been upgraded, to use and to be compatible with the newly emerging technologies of CPU’s such as SIMD and parallel pipelines in its version of SFMT.

somewhat like sorting algorithms in this regard, there is no "one size fits all" PRNG. different ones are used for different purposes and there is a wide variety of design criteria and uses. it is possible to misapply PRNGs such as using one for cryptography that it is not designed for. wikipedias entry on Mersenne twister also mentions that it was not designed for "Monte Carlo tests that require independent PRNGs".

as noted on wikipedia this PRNG is indeed used in a large number of programming languages and applications even as a default PRNG. it would take a near-sociological analysis to explain why one PRNG is favored. some possible factors that may be contributing to this PRNG:

  • author has good/ strong scientific credentials in area and has been working in PRNGs for decades

  • it was specifically designed to be superior to other methods at the time

  • author is engaged in implementations and tracking them, also contributing to them. some PRNGs are more theoretical and the authors do not always concern themselves with actual implementations.

  • the system is well supported/ updated on a web page

  • new versions of the PRNG have been developed to deal with weaknesses. there is not one single Mersenne Twister algorithm, its more like different versions and a family of variants which can handle different needs.

  • it has been extensively analyzed/ tested by standard randomness analysis software and passed, by independent authorities

  • there is a known effect measured with eg web sites and many other contexts eg scientific citations etc called "preferential attachment" which can be measured; its basically where long established historical sources accrue further usage. such an effect could explain PRNG choices over time.

in other words, you are asking about a phenomenon of "popularity" which is associated and interrelated with human choices and is not strictly tied to particular qualities, but is a sort of complex/ emergent property and interplay between different algorithms, users, and environment/ usage contexts etc.

here is one such independent analysis of the algorithm Mersenne Twister – A Pseudo Random Number Generator and its Variants by Jagannatam (15p). the concluding paragraph is essentially an answer to your question. quoting only the 1st few sentences:

Mersenne Twister is theoretically proven to be a good PRNG, with a long period and high equidistribution. It is extensively used in the fields of simulation and modulation. The defects found by the users have been corrected by the inventors. MT has been upgraded, to use and to be compatible with the newly emerging technologies of CPU’s such as SIMD and parallel pipelines in its version of SFMT.

Somewhat like sorting algorithms in this regard, there is no "one size fits all" PRNG. Different ones are used for different purposes and there is a wide variety of design criteria and uses. It is possible to misapply PRNGs, such as using one for cryptography that it is not designed for. Wikipedia's entry on Mersenne Twister also mentions that it was not designed for "Monte-Carlo simulations that require independent random number generators".

As noted on Wikipedia, this PRNG is indeed used in a large number of programming languages and applications even as a default PRNG. It would take a near-sociological analysis to explain why one PRNG is favored. Some possible factors that may be contributing to this PRNG:

  • The Author has good/ strong scientific credentials in area and has been working in PRNGs for decades.

  • It was specifically designed to be superior to other methods at the time.

  • The author is engaged in implementations and tracking them, also contributing to them. Some PRNGs are more theoretical and the authors do not always concern themselves with actual implementations.

  • The system is well supported/updated on a web page.

  • New versions of the PRNG have been developed to deal with weaknesses. There is not one single Mersenne Twister algorithm, its more like different versions and a family of variants which can handle different needs.

  • It has been extensively analyzed/tested by standard randomness analysis software and passed, by independent authorities.

  • There is a known effect measured with for web sites and many other contexts like scientific citations called "preferential attachment" which can be measured. It's basically where long established historical sources accrue further usage. Such an effect could explain PRNG choices over time.

In other words, you are asking about a phenomenon of "popularity" which is associated and interrelated with human choices and is not strictly tied to particular qualities, but is a sort of complex/emergent property and interplay between different algorithms, users, and environment/usage contexts.

Here is one such independent analysis of the algorithm Mersenne Twister – A Pseudo Random Number Generator and its Variants by Jagannatam (15p). The concluding paragraph is essentially an answer to your question. quoting only the 1st few sentences:

Mersenne Twister is theoretically proven to be a good PRNG, with a long period and high equidistribution. It is extensively used in the fields of simulation and modulation. The defects found by the users have been corrected by the inventors. MT has been upgraded, to use and to be compatible with the newly emerging technologies of CPU’s such as SIMD and parallel pipelines in its version of SFMT.

1
source | link

somewhat like sorting algorithms in this regard, there is no "one size fits all" PRNG. different ones are used for different purposes and there is a wide variety of design criteria and uses. it is possible to misapply PRNGs such as using one for cryptography that it is not designed for. wikipedias entry on Mersenne twister also mentions that it was not designed for "Monte Carlo tests that require independent PRNGs".

as noted on wikipedia this PRNG is indeed used in a large number of programming languages and applications even as a default PRNG. it would take a near-sociological analysis to explain why one PRNG is favored. some possible factors that may be contributing to this PRNG:

  • author has good/ strong scientific credentials in area and has been working in PRNGs for decades

  • it was specifically designed to be superior to other methods at the time

  • author is engaged in implementations and tracking them, also contributing to them. some PRNGs are more theoretical and the authors do not always concern themselves with actual implementations.

  • the system is well supported/ updated on a web page

  • new versions of the PRNG have been developed to deal with weaknesses. there is not one single Mersenne Twister algorithm, its more like different versions and a family of variants which can handle different needs.

  • it has been extensively analyzed/ tested by standard randomness analysis software and passed, by independent authorities

  • there is a known effect measured with eg web sites and many other contexts eg scientific citations etc called "preferential attachment" which can be measured; its basically where long established historical sources accrue further usage. such an effect could explain PRNG choices over time.

in other words, you are asking about a phenomenon of "popularity" which is associated and interrelated with human choices and is not strictly tied to particular qualities, but is a sort of complex/ emergent property and interplay between different algorithms, users, and environment/ usage contexts etc.

here is one such independent analysis of the algorithm Mersenne Twister – A Pseudo Random Number Generator and its Variants by Jagannatam (15p). the concluding paragraph is essentially an answer to your question. quoting only the 1st few sentences:

Mersenne Twister is theoretically proven to be a good PRNG, with a long period and high equidistribution. It is extensively used in the fields of simulation and modulation. The defects found by the users have been corrected by the inventors. MT has been upgraded, to use and to be compatible with the newly emerging technologies of CPU’s such as SIMD and parallel pipelines in its version of SFMT.