Is Quantum Computing Headed for a Quantum Winter?
Well done report. Points out some of the realities to ‘hype’ and where the quantum computing business stands (or sits). Because Quantum is Coming. Qubit.
Beyond quantum supremacy: the hunt for useful quantum computers
Selected notes ~
+ Today’s quantum machines have at best a few dozen quantum bits, or qubits, and they are often beset by computation-destroying noise. Researchers are still decades — and many thousands of qubits — away from general-purpose quantum computers, ones that could do long-heralded calculations such as factoring large numbers. A team at Google has now reportedly demonstrated a quantum computer that can outperform conventional machines, but such ‘quantum supremacy’ is expected to be extremely limited. For general applications, 30 years is “not an unrealistic timescale”, says physicist John Preskill at the California Institute of Technology in Pasadena.
For now, however, researchers must contend with the fact that there is still no proof that today’s quantum machines will yield anything of use. NISQ could simply turn out to be the name for the broad, possibly featureless landscape researchers must traverse before they can build quantum computers capable of outclassing conventional ones in helpful ways. “Although there were a lot of ideas about what we could do with these near-term devices,” Preskill says, “nobody really knows what they are going to be good for.”
+ Some researchers have raised the possibility that, if quantum computers fail to deliver anything of use soon, a quantum winter will descend: enthusiasm will wane and funding will dry up before researchers get anywhere close to building full-scale machines. “Quantum winter is a real concern,” Preskill says. But he remains upbeat, because the slow progress has forced researchers to adjust their focus and see whether the devices they already have might be able to do something interesting in the near future.
+ Judging from a flurry of papers published over the past few years, it’s a definite possibility. This is the era of the small, error-prone, or “noisy intermediate-scale quantum” (NISQ), machine, as Preskill has put it1. And so far, it has turned out to be a much more interesting time than anyone had anticipated. Although the results are still quite preliminary, algorithm designers are finding work for NISQ machines that could have an immediate impact in chemistry, machine learning, materials science and cryptography — offering insights into the creation of chemical catalysts, for example. What’s more, these innovations are provoking unexpected progress in conventional computing. All this activity is running alongside efforts to build bigger, more robust quantum systems. Aspuru-Guzik advises people to expect the unexpected. “We’re here for the long run,” he says. “But there might be some surprises tomorrow.”
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