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278个均匀分布随机数 Uniformly distributed random numbers with a sample size 278

摘要 Abstract：我们用数字计算机程序生成了278个均分布的伪随机数。请用各种方法检验它们对真随机数的差别。We generated uniformly distributed PSEUDO-random numbers with a sample size 278 by a digital computer program. Please use various methods to test the differences between them and true random numbers.

关键词 Key words：伪随机数, 数字计算机程序, 真随机数, 时间复杂性, 算法, 实数, PSEUDO-random numbers, digital computer program, true random numbers, time complexity, algorithm, real numbers

   下面的数字是实数[0, 1]区间上的均匀分布伪随机数。是用我们提出的时间复杂性为O(NlogN)的“新”算法通过数字计算机程序生成的，N是伪随机数的数目。它们似乎比由“物理设备”生成的“真随机数”要好。

   感谢您用各种方法对这278个伪随机数进行测试，以定量检验它们对理想的“实数[0, 1]区间上的均匀分布真随机数”的差别。

   The following numbers are uniformly distributed PSEUDO-random numbers in the interval of real numbers [0, 1]. They are generated by a digital computer program using our “new” algorithm with a time complexity  O(NlogN), N is the sample size of the PSEUDO-random numbers. They seem to be better than the “true random numbers” generated by “physical devices”. 

   Thank you very much for using various methods to test the 278 PSEUDO-random numbers in order to estimate quantitatively the differences between them and the ideal “true random numbers in the interval of real numbers [0, 1]”.

Uniformly_distributed_PSEUDO_random_numbers_278 = [

0.0415209370456177

0.390441800354970

0.930010145678711

0.782528131290222

0.00554971402403497

0.462384246398136

0.976772735606769

0.577492160067200

0.322096476613963

0.991161224815402

0.0559094262542508

0.0990748938801501

0.311305109707488

0.415621656470078

0.671017339923316

0.163823095318999

0.242959785966481

0.196197196038423

0.419218778772236

0.365261944239862

0.253751152872956

0.138643239203891

0.512743958628352

0.642240361506049

0.404830289563603

0.807707987405330

0.602672016182308

0.742959785966481

0.394038922657129

0.0127439586283515

0.581089282369359

0.447995757189503

0.746556908268639

0.440801512585186

0.530729570139143

0.354470577333387

0.307707987405330

0.653031728412524

0.656628850714683

0.401233167261445

0.498355469419718

0.235765541362164

0.174614462225474

0.685405829131949

0.933607267980870

0.840082088124754

0.696197196038423

0.0487151816499343

0.214182807549215

0.124254749995258

0.710585685247057

0.606269138484467

0.724974174455690

0.314902232009646

0.332887843520438

0.735765541362164

0.455190001793819

0.397636044959287

0.793319498196697

0.217779929851373

0.476772735606769

0.789722375894539

0.825693598916121

0.275333886685905

0.836484965822596

0.800513742801013

0.491161224815402

0.120657627693100

0.667420217621157

0.0954777715779918

0.689002951434107

0.649434606110366

0.224974174455690

0.624254749995258

0.232168419060006

0.804110865103172

0.145837483808208

0.944398634887344

0.843679210426913

0.868859066542021

0.545118059347776

0.465981368700294

0.883247555750654

0.854470577333388

0.160225973016841

0.638643239203891

0.609866260786625

0.426413023376553

0.0667007931607256

0.0738950377650422

0.951592879491661

0.0379238147434594

0.771736764383747

0.293319498196697

0.106269138484467

0.228571296757848

0.135046116901733

0.886844678052812

0.732168419060006

0.983966980211085

0.635046116901733

0.678211584527632

0.505549714024035

0.994758347117560

0.570297915462884

0.178211584527632

0.699794318340582

0.153031728412524

0.541520937045618

0.300513742801013

0.955190001793819

0.494758347117560

0.433607267980869

0.599074893880150

0.850873455031229

0.926413023376553

0.412024534167920

0.588283526973675

0.0451180593477760

0.0846864046715170

0.764542519779431

0.861664821937704

0.922815901074395

0.336484965822596

0.757348275175114

0.897636044959287

0.879650433448495

0.0271324478369846

0.318499354311805

0.775333886685905

0.555909426254251

0.714182807549215

0.250154030570798

0.131448994599575

0.563103670858567

0.728571296757848

0.663823095318999

0.239362663664323

0.617060505390941

0.998355469419718

0.980369857908927

0.149434606110366

0.890441800354970

0.947995757189503

0.940801512585186

0.591880649275834

0.915621656470078

0.768139642081589

0.0595065485564091

0.361664821937704

0.552312303952093

0.0882835269736753

0.282528131290222

0.343679210426913

0.818499354311805

0.627851872297416

0.350873455031229

0.958787124095977

0.156628850714682

0.113463383088783

0.721377052153531

0.523535325534826

0.167420217621157

0.516341080930510

0.117060505390941

0.264542519779431

0.408427411865762

0.171017339923316

0.760945397477272

0.458787124095977

0.566700793160726

0.858067699635546

0.969578491002452

0.519938203232668

0.753751152872956

0.246556908268639

0.894038922657129

0.487564102513244

0.451592879491661

0.973175613304610

0.750154030570798

0.0307295701391429

0.386844678052812

0.919218778772236

0.0343266924413012

0.358067699635546

0.829290721218280

0.962384246398136

0.706988562944898

0.286125253592380

0.189002951434107

0.347276332729071

0.260945397477272

0.904830289563603

0.796916620498855

0.703391440642740

0.537923814743459

0.0199382032326681

0.142240361506049

0.692600073736265

0.509146836326193

0.271736764383747

0.127851872297416

0.325693598916121

0.912024534167920

0.0918806492758335

0.368859066542021

0.0163410809305098

0.908427411865762

0.340082088124754

0.0631036708585673

0.473175613304611

0.221377052153531

0.631448994599575

0.00914683632619324

0.786125253592380

0.257348275175114

0.814902232009647

0.268139642081589

0.534326692441301

0.872456188844179

0.987564102513244

0.527132447836985

0.296916620498855

0.379650433448495

0.847276332729071

0.0810892823693587

0.480369857908927

0.289722375894539

0.0702979154628839

0.192600073736265

0.573895037765042

0.613463383088783

0.483966980211085

0.210585685247057

0.383247555750654

0.965981368700294

0.548715181649934

0.822096476613963

0.620657627693100

0.717779929851373

0.0235353255348263

0.372456188844179

0.422815901074395

0.660225973016841

0.584686404671517

0.595477771577992

0.865261944239862

0.203391440642740

0.185405829131949

0.901233167261445

0.181808706829790

0.501952591721877

0.811305109707488

0.376053311146337

0.645837483808208

0.430010145678711

0.0523123039520925

0.469578491002452

0.832887843520438

0.559506548556409

0.937204390283028

0.329290721218280

0.778931008988064

0.674614462225474

0.0774921600672004

0.278931008988064

0.199794318340582

0.444398634887344

0.304110865103172

0.206988562944898

0.681808706829790

0.109866260786625

0.437204390283028

0.102672016182308

0.00195259172187670

0.739362663664323

0.876053311146337

];

相关链接：

[1] 2021-01-30，100个均匀分布随机 100 uniformly distributed random numbers

https://blog.sciencenet.cn/blog-107667-1269737.html

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