GoKawiilTo this day, we have yet to see a quantum computer conclusively perform a single useful task. Existing machines are simply too small and error-ridden to solve commercially relevant problems. That hasn’t stopped Donald Trump’s science adviser from promising a “quantum computer powerful enough for scientific discovery by 2028” and Trump from issuing a new executive order to speed up the US quantum computing industry in its competition with China, both on June 22nd.
Companies drive the hype, too. In June, Microsoft announced a new quantum computing chip named Majorana 2. It claimed the chip was a hardware advancement that accelerates its timeline to a “scalable, practical quantum computer” by 2029. But independent experts swiftly criticized the announcement. “This is complete codswallop,” Henry Legg, a physicist from the University of St. Andrews and a longtime Microsoft critic, tells The Verge.
Legg just published a paper in Nature on June 24th criticizing Microsoft’s quantum claims from a year ago — peer review takes a long time — and pointing to what he sees as major discrepancies between Microsoft’s papers and press releases. Nature included Microsoft’s rebuttal. As the arguments continue to roil, the arc of quantum computing’s progress can seem like a mess, alternating between hyped-up announcements from companies, subsequent smackdowns from academic researchers, more fights, and, now, overconfident goals set by heads of state.
Researchers have made genuine progress in quantum computing — it’s just been largely incremental and too esoteric to immediately capture the public’s imagination. Oh, and it’s all very expensive.
Over the last decade, Google, IBM, Amazon, Microsoft, and a slew of national governments and smaller startups have poured billions into quantum computing development. Proponents predict that the technology will lead to discoveries in medicine, as well as advances in materials science and machine learning. Meanwhile, many national security experts frame its development as a new Cold War competition between the US and China.
The promise of quantum computing is that it excels at a fundamentally different type of math than classical computers. Instead of using bits like a classical computer, a quantum computer’s fundamental unit of information is the qubit. Qubits represent information as probabilities rather than ones and zeros. You can think of a qubit as a coin flipping through the air. Before the coin lands definitively as heads or tails, it is a probability of both states. Objects like molecules or processes like photosynthesis inherently involve probabilities, and thus are more “natural” for quantum computers to simulate than classical computers. However, quantum computers are unlikely to be good at classical computing tasks like email or word processing.
Companies make qubits from different materials. Several physicists The Verge spoke to said that the leading qubit types are neutral atoms, ions, and superconducting circuit qubits. Google and IBM both make qubits based on superconducting circuits. Honeywell-affiliated Quantinuum makes qubits out of individual barium ions, whereas Boston-area startup QuEra makes qubits out of individual rubidium atoms. Microsoft’s Majorana particle qubit, which experts dispute exists, is built using a thin wire attached to a superconductor. In pursuing these different approaches, the companies are throwing everything at the wall to develop quantum computing hardware that is both precise and easy to scale.
“This whole Majorana technology, it’s not a technology yet.”
Proponents of the technology say that it could solve problems that today’s supercomputers struggle with. Theoretical research indicates quantum computers should be able to simulate molecules far more easily than supercomputers. These simulations could help to develop new battery materials or medicines.
Proponents of the technology say that it could solve problems that today’s supercomputers struggle with. Theoretical research indicates quantum computers should be able to simulate molecules far more easily than supercomputers. These simulations could help to develop new battery materials or medicines.
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