Random numbers are invaluable. They’re used in the encryption that makes online banking secure. Economists, physicists, pollsters, and casinos rely on them. Yet until recently, producing large sets of truly random digits has been hard to do.
Human bias can skew the process (that’s why just thinking them up isn’t reliable). Labs once used dice and playing cards—time-consuming methods when you need hundreds or thousands of values. In 1927, British statistician L. H. C. Tippett produced a table of 41,600 digits by culling the middle numerals from the area measurements of English parishes. By the ’40s, demand had exploded—vast quantities of random numbers were needed for modeling nuclear weapons. In 1947, RAND amassed a list for the Air Force by measuring a string of electronic pulses. Eight years later it was published in a $10 hardcover titled A Million Random Digits With 100,000 Normal Deviates. (A 2001 edition sold for $90.)
The age of computers solved all of this, right? Wrong. The best that CPUs can generate are pseudo-random numbers, churned out by running a seed number through a complex algorithm, then running the solution through the same operation over and over again. However, anyone who uncovers the algorithm and seed can generate the same sequence of numbers.
But now scientists at the Australian National University have introduced a technique for generating 5.7 billion truly random values per second. They do it by harnessing the fundamental uncertainty of the universe. Their technique measures quantum phenomena in a box completely devoid of photons, where ghostly virtual particles randomly burble in and out of existence 24/7. “God does not play dice,” Einstein famously quipped in response to evidence that randomness rules the cosmos. Luckily, he was wrong.
Go Back to Top. Skip To: Start of Article.