Quantum computing, once considered a theoretical concept, is quickly becoming one of the most groundbreaking fields in science and technology. With the ability to solve problems far beyond the capabilities of classical computers, quantum computers have the potential to revolutionize industries, including cryptography, drug discovery, financial modeling, and artificial intelligence.
Enlarge / Quantinuum's H2 "racetrack" quantum processor. (credit: Quantinuum)
On Tuesday, Microsoft made a series of announcements related to its Azure Quantum Cloud service. Among them was a demonstration of logical operations using the largest number of error-corrected qubits yet.
"Since April, we've tripled the number of logical qubits here," said Microsoft Technical Fellow Krysta Svore. "So we are accelerating toward that hundred-logical-qubit capability." The company has also lined up a new partner in the form of Atom Computing, which uses neutral atoms to hold qubits and has already demonstrated hardware with over 1,000 hardware qubits.
Collectively, the announcements are the latest sign that quantum computing has emerged from its infancy and is rapidly progressing toward the development of systems that can reliably perform calculations that would be impractical or impossible to run on classical hardware. We talked with people at Microsoft and some of its hardware partners to get a sense of what's coming next to bring us closer to useful quantum computing.
Enlarge / A single logical qubit is built from a large collection of hardware qubits. (credit: at digit)
One of the more striking things about quantum computing is that the field, despite not having proven itself especially useful, has already spawned a collection of startups that are focused on building something other than qubits. It might be easy to dismiss this as opportunism—trying to cash in on the hype surrounding quantum computing. But it can be useful to look at the things these startups are targeting, because they can be an indication of hard problems in quantum computing that haven't yet been solved by any one of the big companies involved in that space—companies like Amazon, Google, IBM, or Intel.
In the case of a UK-based company called Riverlane, the unsolved piece that is being addressed is the huge amount of classical computations that are going to be necessary to make the quantum hardware work. Specifically, it's targeting the huge amount of data processing that will be needed for a key part of quantum error correction: recognizing when an error has occurred.
All qubits are fragile, tending to lose their state during operations, or simply over time. No matter what the technology—cold atoms, superconducting transmons, whatever—these error rates put a hard limit on the amount of computation that can be done before an error is inevitable. That rules out doing almost every useful computation operating directly on existing hardware qubits.
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