Microsoft’s new approach to quantum computing is “very close,” an executive says.
Google just announced quantum supremacy, a milestone in which the radically different nature of a quantum computer lets it vastly outpace a traditional machine. But Microsoft expects progress of its own by redesigning the core element of quantum computing, the qubit.
Microsoft has been working on a qubit technology called a topological qubit that it expects will deliver benefits from quantum computing technology that today are mostly just a promise. After spending five years figuring out the complicated hardware of topological qubits, the company is almost ready to put them to use, said Krysta Svore, general manager of Microsoft’s quantum computing software work.
“We’ve really spent the recent few years developing that technology,” Svore said Thursday after a talk at the IEEE International Conference on Rebooting Computing. “We believe we’re very close to having that.”
Quantum computers are hard to understand, hard to build, hard to operate and hard to program. Since they only work when chilled to a tiny fraction of a degree above absolute zero – colder than outer space – you’re not likely to have a quantum laptop anytime soon.
But running them in data centers where customers can tap into them could deliver profound benefits by tackling computing challenges that classical computers can’t handle. Among examples Svore offered are solving chemistry problems like making fertilizer more efficiently, or routing trucks to speed deliveries and cut traffic.
Classical computers store data as a bit that represents either a 0 or a 1. Qubits, though, can store a combination of 0 and 1 simultaneously through a peculiar quantum physics principle called superposition. And qubits can be ganged together through another phenomenon called entanglement. Together, the phenomena should enable quantum computers to explore an enormous number of possible solutions to a problem at the same time.
One of the basic quantum computing problems is that qubits are easily perturbed. That’s why the heart of a quantum computer is housed in a refrigerated container the size of a 55-gallon drum.
Even with that isolation, though, individual qubits today only can perform useful work for a fraction of a second. To compensate, quantum computer designers plan technology called error correction that yokes many qubits together into a single effective qubit, called a logical qubit. The idea is that logical qubits can perform useful processing work when many of their underlying physical qubits have gone astray.
The key advantage of Microsoft’s topological qubit is that fewer physical qubits are needed to make one logical qubit, Svore said.
Specifically, she thinks one logical qubit will require 10 to 100 physical qubits with Microsoft’s topological qubits. That compares to something like 1,000 to 20,000 physical qubits for other approaches.
“We believe that overhead will be far less,” she said. That’ll mean quantum computers will become practical with far fewer qubits.
By comparison, Google’s Sycamore quantum computing chip used 53 physical qubits. For serious quantum computing work, researchers are hoping to reach qubit levels of at least a million.
One drawback of Microsoft’s topological qubit, though, is that they’re not available yet. Alternative designs might not work as well, but they’re in real-world testing today.
Fertilizer and delivery trucks
MIcrobes efficiently “fix” nitrogen into molecules useful for fertilizer, but our industrial processes require vast amounts of energy. Quantum computers, by simulating the actual physics underlying molecular interactions, could potentially come up with a catalyst that would power a better manufacturing process
“If we want better performance for nitrogen fixation, we can mimic the behavior of these microbes,” Svore said. “These microbes are doing this all the time in the soil, not asking for a high temperature and pressure, not consuming up to 5% of the world’s natural gas.“
That computational chemistry work is a common example among quantum computing fans. Besides Microsoft and Google, they include IBM, Intel, Honeywell, IonQ and Rigetti Computing.
But the idea goes back much further – indeed, back to some of the earliest thinking about quantum computing, from Nobel Prize winning physicist Richard Feynman in 1981.
“Nature isn’t classical, dammit, and if you want to make a simulation of nature, you’d better make it quantum mechanical,” he said in a speech at MIT at the time. You can approximate nature with a simulation on a classical computer, but Feynman wanted a quantum computer that offers the real thing, a computer that “will do exactly the same as nature,” Feynman said.
Another example of quantum computing usefulness is optimization – a broad idea that encompasses everything from balancing an investment portfolio to routing planes. Microsoft has already shown quantum computers can speed up package delivery calculations performed on classical machines, Svore said.
In one test, the quantum-boosted work yielded routes with 37% less driving mileage, she said, and needed fewer trucks, too.
“We really did get a better answer,” Svore said.
Better quantum computing algorithms
Microsoft is also trying to improve other aspects of quantum computing. One is the control system, which in today’s quantum computers is a snarl of hundreds of wires, each an expensive coaxial cable used to communicate with qubits.
On Monday at Microsoft’s Ignite conference, the company also showed off a new quantum computer control system developed with the University of Sydney that uses many fewer wires – down from 216 to just three, Svore said. “We think this will scale to tens of thousands of qubits and beyond.”
And Svore pushed for progress on quantum computing software, too, urging professors to introduce their students to learning and improving quantum computing algorithms.
In one example of those benefits, Microsoft tackled an aspect of that nitrogen-fixing fertilizer problem that simply couldn’t be solved on a classical machine – but found that a quantum computer would still take 30,000 years.
That’s faster than a classical computer that would require “the lifetime of the universe,” but still not practical, she said. But with algorithm improvements, Microsoft found a way to shorten that to just a day and a half.
“New algorithms can be a breakthrough in how to solve something,” Svore said. “We need to make them better, we need to optimize them, we need to be pushing.”
Source: CNetRelated posts: