Research from the U.S. National Institute of Standards and Technology (NIST) has narrowed the theoretical limits for where the “speed limit" lies for solving problems on quantum computers.

NIST suggests that quantum processors will work more slowly than some research says. It offers up a specific description of how quickly information can travel in a system built of quantum particles, such as a group of individual atoms. This information will be important when engineers build quantum computers.

“While the new finding does not give an exact speed for how fast information will be able to travel in these as-yet-unbuilt computers—a longstanding question—it does place a far tighter constraint on where this speed limit could be," says NIST.

The research builds on findings dating back to the 1970's, when scientists discovered a limit on how quickly information could travel if suspended particles could only communicate directly with the particles next to them. Since then, technology has advanced to the point where scientists can now investigate whether a particle might directly influence others that are more distant.

The size of a quantum computer affects how quickly information can be distributed throughout it. Credit: NIST "Those results implied a quantum computer might be able to operate really fast, much faster than anyone had thought possible," says NIST's Michael Foss-Feig. "But over the next decade, no one saw any evidence that the information could actually travel that quickly."

Quantum computers will store data in a particle's quantum states—one of which is its spin, the property that confers magnetism. A quantum processor could suspend many particles in space in close proximity, and computing would involve moving data from particle to particle. Just as one magnet affects another, the spin of one particle influences its neighbor's, making quantum data transfer possible; however, one question is how fast this influence can work.

"On the other hand, the findings tell us something important about how entanglement works," says Foss-Feig. "They could help us understand how to model quantum systems more efficiently."