RANDOMNESS IS A valuable commodity. Computer models of complex systems ranging from the weather to the stockmarket are voracious consumers of random numbers. Cryptography, too, relies heavily on random numbers for the generation of unbreakable keys. Better, cheaper ways of generating and handling such numbers are therefore always welcome. And doing just that is the goal of a project with the slightly tongue-in-cheek name of COINFLIPS, which allegedly stands for Co-designed Improved Neural Foundations Leveraging Inherent Physics Stochasticity.

COINFLIPS operates under the aegis of Brad Aimone, a theoretical neuroscientist at Sandia National Laboratories (originally one of America’s nuclear-weapons laboratories, but which has now branched out into other areas, too). Dr Aimone’s starting-point is the observation that, unlike the circuits of digital computers, which will, if fed a given input, respond with a precise and predictable output, the link between input to and output from a nerve cell is more haphazard—or, in the jargon, “stochastic”. He wants to imitate this stochastic behaviour in something less squishy than a nerve cell. By doing so, he thinks he might be able to tune the distribution of digits that a random-number generator spits out, without affecting their underlying randomness.