The qubit systems we have today are a huge scientific achievement, but they don’t get us any closer to having a quantum computer that can solve a problem that everyone cares about. It’s akin to trying to make today’s best smartphones using early 20th century vacuum tubes. You can put 100 tubes together and establish the principle that if you could somehow get 10 billion of them to work together in a coherent, seamless way, you could achieve all kinds of miracles. What’s missing, though, is the breakthrough integrated circuits and CPUs that led to smartphones — it took 60 years of very difficult engineering to go from the invention of transistors to the smartphone without new physics involved.
There are, in fact, ideas, and I’ve been instrumental in developing the theories for these ideas, to get around 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 hardware for quantum computers is also a huge challenge. It’s unclear whether extended 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 really good at coming up with substantive-sounding acronyms that stick. The great difficulty in getting rid of decoherence has led to the impressive acronym NISQ for “noisy intermediate scale quantum” computer – for the idea that small collections of noisy physical qubits could do something more useful and better than a classical computer. Not sure what this object is: How noisy? How many qubits? Why is this a computer? What worthy problems can such a NISQ machine solve?
A recent lab experiment at Google observed some predicted aspects of quantum dynamics (called “time crystals”) using 20 noisy superconducting qubits. The experiment was an impressive demonstration of electronic control techniques, but it showed no computational advantage over conventional computers, which can easily simulate time crystals with a comparable number of virtual qubits. It also revealed nothing about the fundamental physics of time crystals. NISQ’s other triumphs include recent experiments simulating arbitrary quantum circuits, again a highly specialized task without any commercial value.
Using NISQ is certainly an excellent new basic research idea – it could help physics research in fundamental areas such as quantum dynamics. But despite a constant thump of NISQ hype coming from various quantum computing startups, the commercialization potential is far from clear. I’ve seen vague claims about how NISQ can 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 every difficult task with real-world applications, and I basically interpret their complicated answers as saying that since we don’t fully understand how classic machine learning and AI really work, it 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 to design drugs, as a way to quickly calculate molecular structure, which is a mind-boggling application, given that quantum chemistry is a minuscule part of the whole process. Equally mind-boggling are claims that quantum computers will help finance in the near term. There are no technical documents convincingly showing that small quantum computers, let alone NISQ machines, can lead to significant optimization in algorithmic trading or risk evaluation or arbitrage or hedging or targeting and forecasting or asset trading or risk profiling. However, this has not stopped several investment banks from jumping on the quantum computer.
A true quantum computer will have unimaginable uses today, just as when the first transistor was created in 1947, no one could have foreseen how it would eventually lead to smartphones and laptops. I’m all for hope and a big proponent of quantum computing as a potentially disruptive technology, but to claim that it could start generating millions of dollars in profits for real companies selling services or products in the near future is utterly mind-boggling to me. How?
Quantum computing is indeed one of the most important developments not only in physics, but in all of science. But ‘entanglement’ and ‘superposition’ are not magic wands that we can shake and expect to transform technology in the near future. Quantum mechanics is indeed weird and counterintuitive, but that in itself is no guarantee of revenue and profit.
Ten years and more ago, I was often asked when I thought a real quantum computer would be built. (It’s interesting that I no longer face this question, as the hype of quantum computers has apparently convinced people that these systems already exist or are just around the corner). My unequivocal answer has always been that I don’t know. Predicting the future of technology is impossible – it happens when it happens. One might try to draw an analogy with the past. It took the airline industry more than 60 years to move from the Wright brothers to jumbo jets that carried hundreds of passengers from thousands of miles. The immediate question is where to place the development of quantum computing, as it stands now, on that timeline. Is it with the Wright brothers in 1903? The first jet aircraft around 1940? Or maybe we are still way back in the early 16th century, with Leonardo da Vinci’s flying machine? I do not know. Nor does anyone else.
Sankar Das Sarma is the director of the Condensed Matter Theory Center at the University of Maryland, College Park.