Google has provided the first clear proof of quantum computers outperforming a classical one.
Like the first digital computers, quantum computers offer the possibility of technology exponentially more powerful than current systems. They stand to change companies, entire industries, and the world by solving problems that seem impossible today.
A recent report by Gartner states that by 2023, 20% of organizations will be budgeting for quantum computing projects. As this new technology develops, organizations will face a shortage of quantum computing experts.
Quantum computers store and process data in a way completely different from the ones we’re all used to. In theory, they could tackle certain classes of problems that even the most powerful classical supercomputer imaginable would take millennia to solve, like breaking today’s cryptographic codes or simulating the precise behavior of molecules to help discover new drugs and materials.
There have been working quantum computers for several years, but it’s only under certain conditions that they outperform classical ones, and in October 2019, Google claimed the first such demonstration of “quantum supremacy.” A computer with 53 qubits—the basic unit of quantum computation—did a calculation in a little over three minutes that, by Google’s reckoning, would have taken the world’s biggest supercomputer 10,000 years, or 1.5 billion times as long.
IBM challenged Google’s claim, saying the speedup would be a thousandfold at best; even so, it was a milestone, and each additional qubit will make the computer twice as fast.
However, Google’s demo was strictly a proof of concept—the equivalent of doing random sums on a calculator and showing that the answers are right. The goal now is to build machines with enough qubits to solve useful problems. This is a formidable challenge: the more qubits you have, the harder it is to maintain their delicate quantum state. Google’s engineers believe the approach they’re using can get them to somewhere between 100 and 1,000 qubits, which may be enough to do something useful—but nobody is quite sure what.
And beyond that?
Machines that can crack today’s cryptography will require millions of qubits; it will probably take decades to get there. But one that can model molecules should be easier to build.