「華人戴明學院」是戴明哲學的學習共同體 ,致力於淵博型智識系統的研究、推廣和運用。 The purpose of this blog is to advance the ideas and ideals of W. Edwards Deming.

2018年6月30日 星期六

New Method of Producing Random Numbers. A Million Random Digits THE SEQUEL: with Perfectly Uniform Distribution. Why are countries creating public random number generators?

Why are countries creating public random number generators?

In Chile, politicians resent the Comptroller General, which audits government officials to prevent corruption. The audits are supposed to be random—but scrutinized officials sometimes complain about unfair targeting. "The auditors have to convince the public they're doing their work honestly," says Alejandro Hevia, a computer scientist at the University of Chile in Santiago. Along with researchers around the world, he is developing technology that could persuade critics that audits are truly random: public random number generators.
On 10 July, Hevia's team will unveil an online random number service. Later in July, the U.S. National Institute of Standards and Technology (NIST) will launch its Randomness Beacon as a permanent service, upgrading a pilot program that began in 2013. Brazil, too, is planning a beacon, by the end of 2019. All aim to improve on commercial random number generators, not only by being free, but by generating the random numbers through transparent protocols and permanently archiving them. The services could benefit everyday applications such as cryptography and lotteries—and also research. Some scientific simulation methods rely on random numbers, and clinicians could use them in drug trials to fairly assign who gets a treatment or placebo.
"We want to put randomness on the internet for people to use in whatever way they can find," says Rene Peralta, a computer scientist at NIST in Gaithersburg, Maryland, who leads the U.S. effort. "I think of it as digital infrastructure."


A Million Random Digits THE SEQUEL: with Perfectly Uniform Distribution [Paperback] David Dubowski (Author)
Finally, after 56 years the saga continues! Here is the next book of random numbers, pseudorandom actually, this time generated purely by mathematics. The familiar table form continues, but this set has perfectly uniform distribution. Using the Pi Crust Shuffler algorithm, a modern PC quietly churned out these 400 pages of delightful digits, ready for action in the real world. Any math lover would be delighted to receive this book as a gift! The algorithm's BASIC source code is included.

These Amazon Products Are No Joke, But the Online Reviews Are
Whether on Books About Random Digits Or Toilet Seats, Everybody's a Comedian
What is it about the book "A Million Random Digits With 100,000 Normal Deviates" that brings out the wiseguy in people?

Smart-aleck customers are flexing their comedy muscles on Amazon, with snarky reviews and silly photos of products like banana slicers and fresh whole rabbit. WSJ's Michael M. Phillips reports.
Rand Corp.'s 600-page paperback, which delivers exactly what it promises, sells for $64.60 on Amazon.com AMZN -2.20% . Yet 400 people have submitted online Amazon reviews, most of them mocking the 60-year-old reference book for mathematicians, pollsters and lottery administrators.
"Almost perfect," said one reviewer. "But with so many terrific random digits, it's a shame they didn't sort them, to make it easier to find the one you're looking for."
Five stars from this commenter: "[T]he first thing I thought to myself after reading chapter one was, 'Look out, Harry Potter!' "
Several reviewers complained that while most of the numbers in the book appeared satisfactorily random, the pages themselves were in numerical order.
Amazon's online superstore has become the unlikely stage for 21st-century amateur comedy, where thousands of customers have submitted reviews for products ranging from the self-explanatory explanatory book "How to Avoid Huge Ships" to the Hutzler 571 banana slicer, a yellow plastic banana-shaped device that cuts bananas into even slices.
Rand said its long list of random numbers, first published in 1955, is one of its all-time best sellers. "It's a tool of some sort, but it's beyond my clear understanding," a Rand spokesman admitted.
One Amazon reviewer panned a real-life copycat publication called "A Million Random Digits THE SEQUEL: with Perfectly Uniform Distribution." "Let's be honest, 4735942 is just a rehashed version of 64004382, and 32563233 is really nothing more than 97132654 with an accent."
"We are always amazed by the creativity of our customers," said an Amazon spokeswoman...

 more: http://online.wsj.com/article/SB10001424127887323528404578454763919379102.html?mod=djemITPE_h


New Method of Producing Random Numbers Could Improve ...


May 16, 2016 - Computer science professor David Zuckerman and graduate student Eshan Chattopadhyay will present research about their method in June at ...

Academics Make Theoretical Breakthrough in Random Number ...


May 17, 2016 - David Zuckerman, a computer science professor, and Eshan Chattopadhyay, a graduate student, published a paper in March that will be ...

隨機亂數生成演算法獲突破 五月 28, 2016 (photo by James Bowe)

本文來自於 sciencenews.org《New technique produces real randomness》,36氪翻譯



不過最近德州大學的兩位電腦科學家 Eshan Chattopadhyay 和 David Zuckerman 開發出了一種改進的隨機抽樣器,這種算法只需要兩種隨機性不強的來源即可生成真正隨機的數字,被認為是基礎算法取得的一大突破。


而隨機抽取器則是通過這些隨機性較弱的來源來發掘隨機性。用 MIT 電腦科學家 Dana Moshkovitz 的話來說,隨機性是一種資源,獲取隨機性的過程就像是挖金礦一樣—先開採礦石,然後排沙篩金。

而兩位科學家的算法是對隨機抽樣器的改進。這種隨機抽取器將兩種獨立的弱隨機亂數來源組合為一個接近隨機的集合,並且只有細微偏差。然後再利用彈性函數(一種訊息組合方法)將一串數字轉化為真正的隨機位 —1 或 0。

利用彈性函數進行訊息組合可以防止偏差的出現。比方說在大選裡面,一些蓄意的投票者有可能會把結果引向想要的方向。但彈性函數可以保護誠實的投票者。因為它不是選取簡單多數,而是先把數據分成 3 組,然後選取每組中的多數,再把選出來的數分成 3 組然後再抽取每組中的多數,以此類推直到最後。這種做法使得選舉可以容忍大量盲點的存在,而在隨機亂數生成方面,這種做法可以把偏差數過濾掉。


The technical details are described in the academics’ paper “Explicit Two-Source Extractors and Resilient Functions.” The academics’ introduction of resilient functions into their new algorithm built on numerous previous works to arrive at landmark moment in theoretical computer science. Already, one other leading designer of randomness extractors, Xin Li, has built on their work to create sequences of many more random numbers.

See more at: Academics Make Theoretical Breakthrough in Random Number Generation https://wp.me/p3AjUX-uJE