Ike Chuang holds a pencil-thin test tube containing a bright orange solution of a billion billion molecules, the core of each one a combination of five fluorine and two carbon atoms. He slides the test tube into the chamber of a modified nuclear magnetic resonance (NMR) machine that looks like an enormous pressure cooker. Inside the machine, the sample is surrounded by radio frequency coils attached to amplifiers and signal generators "like those inside a cellphone, only much larger," Chuang says.
Chuang types "GA"-Go ahead-on a keyboard. With a bell-like sound the radio waves wash over the test tube, and the nuclei of the carbon and fluorine atoms begin to spin. And, as they precess about their axes, perform calculations. The computation-of the prime factors of the number 15-takes less than a second, and Chuang repeats the experiment 35 more times, averaging the results to control for errors.
Factoring 15 is a problem fit for grade school
students and cheap calculators, but it's not the size or speed of the calculation, merely the fact of it that matters in this case. Chuang's
seven-"qubit" quantum computer, at the moment the most powerful one ever built, provides concrete evidence of a proposition that scientists just a few years ago thought unworkable: that the properties of atoms at the quantum level can reliably be exploited for the brains of a working computer. Indeed, the work of Chuang and others suggests that quantum machines may one day be capable of massively parallel computing, in which billions of calculations happen at once-a feat that will never be possible with silicon chips.
"We want to go beyond the normal," says Chuang, who is now an associate professor at MIT's Center for Bits and Atoms, though he performed his seminal quantum computer experiments at IBM's Almaden Research Center in San Jose, California. "We want to shrink computing to a scale where it can be done in ways no one's ever thought of."
Chuang does not work alone. Dozens of research teams around the world are pouring hundreds of millions of dollars into proving that computing at very small scales holds unique promise. They're experimenting with carbon nanotubes, strands of DNA, and spinning nuclei. What they seek are computational devices that leapfrog over problems inherent in the "classical" chip-based computer, problems that have to do not only with size but with the serial nature of chip operation, in which one job follows the next in lock step. No matter how quickly a silicon chip completes each task, the sequential nature of its operation limits its power. (As the physicist Richard Feynman famously said, "the inside of a computer is as dumb as hell, but it goes like mad!" With certain problems, going like mad isn't good enough.)