Quantum computers are just weird, with data processed by qubits that can store ones and zeros at the same time. But they're like regular "classical" computers in one obvious way: Their designers want them to run faster.
Now, with machines like its Q System One, IBM has not only proposed a convenient single number to calibrate a speedometer but also laid out an ambitious dotted line stretching across a road map into the future. The course it's charting aims to double performance each year so quantum computers can achieve what Big Blue calls quantum advantage, in which quantum computers are faster or more efficient at a task than a classical computer or accomplish something a classical computer simply can't.
The speedometer is calibrated in a figure called quantum volume that measures not only how many qubits a quantum computer has -- a key measure of its data-processing ability -- but also how much use the computer can get out of the notoriously unstable qubits. IBM quantum computers reached quantum volume of 4 in 2017, then 8 in 2018, and now 16 with the Q System One.
That doubling is a quantum parallel to Moore's Law, the famous observation by Intel co-founder Gordon Moore about the exponential progress of conventional computer chips. Moore's Law held steady for decades, but it's faltering now as miniaturizing processor circuitry gets harder and harder -- a reality that's making quantum computing more important as a possible way to continue progress in the industry.
If IBM's idea catches on with other quantum computing companies like Microsoft, Google and Rigetti Computing, it could give people who don't have a Ph.D. in quantum physics a better idea about progress in this difficult subject. If not, well, at least it gives us a clear way to see if IBM is passing the milestones toward commercial use of quantum computing.
IBM revealed the results at the 2019 American Physical Society March Meeting, That venue shows just how far quantum computing has to go before it moves from physics research to more down-to-earth engineering and computer science.