Quantum computing has a publicity problem | MIT Technology Review

The qubit systems we have today are a tremendous scientific achievement, but they don’t bring us any closer to having a quantum computer that can solve a problem that anyone cares about. It’s akin to trying to make today’s best smartphones using vacuum tubes from the early 20th century. You can put 100 tubes together and establish the principle that if you could somehow get 10 billion of them to work together consistently and seamlessly, you could accomplish all kinds of miracles. What is missing, however, is the breakthrough of ICs and CPUs leading to smartphones: it took 60 years of very difficult engineering to go from the invention of transistors to the smartphone without new physics involved in the process. .

In fact, there are ideas, and I played some paper in developing the theories for these ideas, to circumvent quantum error correction by using much more stable qubits, in an approach called topological quantum computing. microsoft is working on this approach. But it turns out that developing topological quantum computing hardware is also a big challenge. It is not clear whether extensive quantum error correction or topological quantum computing (or something else, like a hybrid between the two) will be the ultimate winner.

Physicists are smart, as we all know (disclosure: I’m a physicist), and some physicists are also very good at coming up with noun-sounding acronyms that stick. The great difficulty in getting rid of decoherence has led to the impressive NISQ acronym for “noisy intermediate scale quantum” computer, for the idea that small collections of noisy physical qubits could do something useful and better than a classical computer. I’m not sure what this object is: How loud? How many qubits? Why is this a computer? What valuable problems can such a NISQ machine solve?

AN recent lab experiment at Google has looked at some predicted aspects of quantum dynamics (called “time crystals”) using 20 noisy superconducting qubits. The experiment was an impressive display of electronic control techniques, but it showed no computational advantage over conventional computers, which can easily simulate time crystals with a similar number of virtual qubits. He also did not reveal anything about the fundamental physics of time crystals. Other NISQ triumphs are recent experiments that simulate random quantum circuitsagain a highly specialized task with no commercial value.

The use of NISQ is certainly an excellent new fundamental research idea: it could help physical research in fundamental areas such as quantum dynamics. But despite constant hype for NISQ coming from various quantum computing startups, the commercialization potential is far from clear. I’ve seen vague claims about how NISQ could be used for rapid optimization or even AI training. I’m not an optimization or AI expert, but I’ve asked the experts and they’re equally baffled. I’ve asked researchers involved in several startups how NISQ would optimize any difficult task involving real-world applications, and I interpret their convoluted answers as essentially saying that since we don’t quite understand how classical machine learning and AI actually work, it’s possible that NISQ could do this even faster. Maybe, but this is hoping for the best, not technology.

There are proposals to use small-scale quantum computers for drug design, as a way to quickly calculate molecular structure, which is a puzzling application given that quantum chemistry is a tiny part of the whole process. Equally puzzling are claims that quantum computers will help finances in the short term. No whitepaper convincingly demonstrates that small quantum computers, let alone NISQ machines, can lead to significant optimization in algorithmic trading or risk assessment or arbitrage or hedging or targeting and forecasting or trading. of assets or the preparation of risk profiles. However, this hasn’t stopped a number of investment banks from jumping on the quantum computing bandwagon.

A real quantum computer will have applications unimaginable today, just as when the first transistor was made in 1947, no one could have foreseen how it would eventually lead to smartphones and laptops. I have every hope and a strong belief in quantum computing as a potentially disruptive technology, but to claim that it would start producing millions of dollars in profits for real companies selling services or products in the near future is very puzzling to me. How?

Quantum computing is, in fact, one of the most important developments not only in physics, but in all of science. But “interlacing” and “overlaying” are not magic wands that we can wave and hope will transform technology in the near future. Quantum mechanics is admittedly weird and counterintuitive, but that alone doesn’t guarantee revenue or profit.

Over a decade ago, I was often asked when I thought a real quantum computer would be built. (It’s interesting that I’m no longer faced with this question, as the quantum computing hype has apparently convinced people that such systems already exist or are just around the corner.) My unequivocal answer was always that I don’t know. Predicting the future of technology is impossible: it happens when it happens. One could try to make an analogy with the past. It took more than 60 years for the aviation industry to go from the Wright brothers to jumbo jets carrying hundreds of passengers thousands of miles. The immediate question is where the development of quantum computing, as it stands today, should be placed in that timeline. Is it with the Wright brothers in 1903? The first jet planes around 1940? Or maybe we’re still in the top 16the century, with Leonardo da Vinci’s flying machine? I don’t know. Neither does anyone else.

Sankar Das Sarma is the director of the Center for Condensed Matter Theory at the University of Maryland, College Park.

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