@article{Hellekalek1998,
  langid = {english},
  title = {Good Random Number Generators Are (Not so) Easy to Find},
  volume = {46},
  issn = {03784754},
  doi = {10.1016/S0378-4754(98)00078-0},
  abstract = {Every random number generator has its advantages and deficiencies. There are no ``safe'' generators. The practitioner's problem is how to decide which random number generator will suit his needs best. In this paper, we will discuss criteria for good random number generators: theoretical support, empirical evidence and practical aspects. We will study several recent algorithms that perform better than most generators in actual use. We will compare the different methods and supply numerical results as well as selected pointers and links to important literature and other sources. Additional information on random number generation, including the code of most algorithms discussed in this paper is available from our web-server under the address http://random.mat.sbg.ac.at/ \# 1998 IMACS/Elsevier Science B.V.},
  number = {5-6},
  journaltitle = {Math. Comput. Simul.},
  date = {1998-06},
  pages = {485-505},
  author = {Hellekalek, P.},
  file = {/home/malcolm/Zotero/storage/BIQCSA35/Hellekalek - 1998 - Good random number generators are (not so) easy to.pdf;/home/malcolm/Zotero/storage/KS954DX7/Hellekalek_1998_Good random number generators are (not so) easy to find.pdf;/home/malcolm/Zotero/storage/4HQC3S84/S0378475498000780.html}
}

@article{Entacher,
  langid = {english},
  title = {A Collection of Selected Pseudorandom Number Generators with Linear Structures},
  abstract = {This is a collection of selected linear pseudorandom number that were implemented in commercial software, used in applications, and some of which have extensively been tested. The quality of these generators is examined using scatter plots and the spectral test. In addition, the spectral test is applied to study the applicability of linear congruential generators on parallel architectures.},
  pages = {25},
  author = {Entacher, Karl},
  file = {/home/malcolm/Zotero/storage/P4B92XA3/Entacher - A collection of selected pseudorandom number gener.pdf}
}

@article{LEcuyer,
  langid = {english},
  title = {A {{Software Library}} in {{ANSI C}} for {{Empirical Testing}} of {{Random Number Generators}}},
  pages = {219},
  author = {L’Ecuyer, Pierre and Simard, Richard},
  file = {/home/malcolm/Zotero/storage/ZVVXPT78/L’Ecuyer and Simard - A Software Library in ANSI C for Empirical Testing.pdf}
}

@article{LEcuyer2007,
  title = {{{TestU01}}: {{A C Library}} for {{Empirical Testing}} of {{Random Number Generators}}},
  volume = {33},
  issn = {0098-3500},
  doi = {10.1145/1268776.1268777},
  shorttitle = {{{TestU01}}},
  abstract = {We introduce TestU01, a software library implemented in the ANSI C language, and offering a collection of utilities for the empirical statistical testing of uniform random number generators (RNGs). It provides general implementations of the classical statistical tests for RNGs, as well as several others tests proposed in the literature, and some original ones. Predefined tests suites for sequences of uniform random numbers over the interval (0, 1) and for bit sequences are available. Tools are also offered to perform systematic studies of the interaction between a specific test and the structure of the point sets produced by a given family of RNGs. That is, for a given kind of test and a given class of RNGs, to determine how large should be the sample size of the test, as a function of the generator's period length, before the generator starts to fail the test systematically. Finally, the library provides various types of generators implemented in generic form, as well as many specific generators proposed in the literature or found in widely used software. The tests can be applied to instances of the generators predefined in the library, or to user-defined generators, or to streams of random numbers produced by any kind of device or stored in files. Besides introducing TestU01, the article provides a survey and a classification of statistical tests for RNGs. It also applies batteries of tests to a long list of widely used RNGs.},
  number = {4},
  journaltitle = {ACM Trans Math Softw},
  date = {2007-08},
  pages = {22:1--22:40},
  keywords = {random number generators,random number tests,Statistical software,statistical test},
  author = {L'Ecuyer, Pierre and Simard, Richard},
  file = {/home/malcolm/Zotero/storage/F8SW23HY/L'Ecuyer_Simard_2007_TestU01.pdf}
}

@article{ONeill2014,
  title = {{{PCG}}: {{A}} Family of Simple Fast Space-Efficient Statistically Good Algorithms for Random Number Generation},
  shorttitle = {{{PCG}}},
  journaltitle = {ACM Trans. Math. Softw.},
  date = {2014},
  author = {O’Neill, Melissa E.},
  file = {/home/malcolm/Zotero/storage/3NNGWIHH/O’Neill_2014_PCG.pdf;/home/malcolm/Zotero/storage/AL9N9CVI/O'Neill - PCG A Family of Simple Fast Space-Efficient Stati.pdf},
  ids = {ONeill}
}

@patent{Noll1998,
  title = {Method for Seeding a Pseudo-Random Number Generator with a Cryptographic Hash of a Digitization of a Chaotic System},
  number = {5732138A},
  type = {patentus},
  urldate = {2019-08-26},
  date = {1998-03-24},
  keywords = {comprised,number generator,pseudo,random number,seed},
  author = {Noll, Landon Curt and Mende, Robert G. and Sisodiya, Sanjeev},
  holder = {{Graphics Properties Holdings Inc}},
  file = {/home/malcolm/Zotero/storage/5HMFXZ7N/Noll et al_1998_Method for seeding a pseudo-random number generator with a cryptographic hash.pdf}
}