Going inside any startup or university lab where quantum computers are being constructed is like time traveling to the 1960s, the time of mainframe computing. Inside these labs are groups of technicians managing the machines the size of entire rooms.
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Each kind of equipment, ranging from super-accurate lasers to supercooled refrigerators, is needed in harnessing the forces of quantum mechanics for data processing.
Cables connecting various bits of gear form multicolored spaghetti that spills over floors and runs across ceilings. Physicists and engineers swarm around banks of screens, constantly monitoring and tweaking the performance of the computers.
Mainframes ushered in the information revolution, and the hope is that quantum computers will prove game-changers too. Their immense processing power promises to outstrip that of even the most capable conventional supercomputers, potentially delivering advances in everything from drug discovery to materials science and artificial intelligence.
The huge challenge in this developing industry, however, is creating machines which can be scaled up both reliably and relatively cheaply.
Generating and managing the quantum bits, or qubits, that carry information in the computers is hard. Even the tiniest vibrations or changes in temperature—phenomena known as “noise” in quantum jargon—can cause qubits to lose their fragile quantum state. And when that happens, errors creep into calculations.
The common response to this problem is to create quantum computers with as many qubits as possible on a single chip. However, the error rates become extreme. The largest chips of today have fewer than a hundred qubits, but if scientists want to produce the same result as a single error-free qubit, thousands or even tens of thousands of qubits would be needed. What’s more, since each qubit needs its own control wiring, the system becomes more complex and more difficult to manage as more qubits are added. Not only does the system become more complex; it also becomes more costly.
A Yale professor named Robert Schoelkopf, believes that there is a better way to approach this challenge. Instead of trying to pack lots of qubits onto a single chip, Quantum Circuits, a startup which Schoelkopf started in 2017, is developing mini quantum machines which “can be networked together via specialized interfaces, a bit like very high-tech Lego bricks.”
Schoelkopf says this approach helps produce lower error rates, so fewer qubits—and therefore less supporting hardware—will be needed to create powerful quantum machines.
Find out more about this topic over at Technology Review.
(Image Credit: Quantum Circuits)