Real-time corrections

Researchers at Honeywell Quantum Solutions, the company’s quantum computing division, demonstrated that it could correct in real time the errors that tend to creep into the calculations of today’s quantum computers, finding and correcting the mistakes as they occur. This is an advance on previous methods, in which such errors could only be spotted and corrected once a calculation had finished running, which made for potentially much slower processing times.

Errors are one of the things that is currently holding back many real-world applications of quantum computing. Honeywell managed to achieve its real-time error correction by yoking together seven of the 10 physical qubits—the parts of a quantum computer that perform calculations—to form a single calculating unit, known as a “logical qubit.”

“Big enterprise-level problems require precision and error-corrected logical qubits to scale successfully,” Tony Uttley, president of Honeywell Quantum Solutions, said in a statement.

Honeywell also said it had achieved a quantum volume of 1,024, doubling its previous record announced just in March. Quantum volume is a measure of performance that takes into account several different variables. Startup IonQ unveiled a quantum computer using an underlying trapped-ion technology similar to Honeywell’s in October that it said had an “expected quantum volume” of 4 million. IonQ also said it thought the benchmark metric, which was first promulgated by IBM in 2016, might not be useful for much longer because of differences between underlying hardware types.

More with less

Finally, Cambridge Quantum Computing announced that it had made an algorithmic advance that makes it possible to solve complex optimization problems using few qubits, which are the logical processing parts of a quantum computer. Today’s quantum computers often have just a few dozen of these qubits, compared to the billions of switches in today’s standard computer chips, so being able to do more with a fewer number of qubits is important for real-world applications. Optimization problems are also the sort of mathematical problem that pop up frequently in business, whether it is trying to find the most efficient route for a delivery courier, the best way to balance risk and reward in a financial portfolio, or the best way to run factory equipment quickly and reduce maintenance stoppages.

The startup said its methods could speed up the time it would take to solve some complex optimization problems by up to a factor of 100. “Faster quantum algorithms can have a profound impact on a variety of industries that face complicated optimization problems,” Ilyas Khan, the founder and chief executive officer of Cambridge Quantum Computing, said in a press release. He mentioned steel manufacturing as an area where quantum algorithms could help make manufacturing processes more efficient and cost-effective.

Quantum computing is making steady inroads into commercial applications. Dozens of companies, from Goldman Sachs to Bosch, have set up pilot projects that rely on access to quantum computers accessed through cloud-computing platforms. More still are using algorithms inspired by quantum computing techniques, but which run on standard hardware.

Quantum computers use phenomenon from quantum physics to make their calculations. For instance, while in a standard computer, information is represented by a binary unit called a bit, that can be either a 0 or 1. In a quantum computer, information is represented by a qubit, which can be both 0 and 1 at the same time. In a standard computer, each bit is also independent from every other bit. In a quantum computer, however, the state of every qubit can potentially influence the state of every other qubit. These two properties, which are called superposition and entanglement, theoretically give quantum computers exponentially more processing power than existing digital computers, which computer scientists often call “classical computers.”

There are other differences as well: Today’s digital computers pretty much all run on similar logic circuits constructed from semiconductors. The qubits in quantum computers can be made in a wide variety of different ways: IBM’s and Google’s quantum machines work by creating circuits using superconducting materials at extremely low temperatures. Microsoft has been trying to create a quantum computer using qubits that marry superconducting and semiconducting materials. Honeywell’s machine uses an entirely different method that relies on firing lasers into a material to trap ions.

The problem is that it is difficult to keep the qubits in a quantum state for long—one minute at most for a trapped ion qubit, just fractions of a second for most other superconducting circuits. And when these qubits fall out of a quantum state, errors pile up in their calculations. The presence of these errors and the fact that researchers have not yet figured out how to create chips with anywhere near the number of qubits as there are logical gates in a standard digital computer, mean that in most cases today’s quantum computers are still less powerful and less useful than even most laptops. This is true except for a small subset of very difficult problems—many related to quantum physics itself—where a quantum computer is the only provable way to arrive at a valid answer.

Correction, July 23: An earlier version of this story misstated the percentage of the new, standalone quantum computing company that Honeywell own after the merger and spin-off. It also in one instance mischaracterized the nature of Honeywell’s business combination with Cambridge Quantum Computing.