What’s next for quantum computing

What’s next for quantum computing

This story is a part of MIT Technology Review’s What’s Next series, where we look across industries, trends, and technologies to give you a first look at the future

In 2023, progress in quantum computing will be defined less by big hardware announcements than by researchers consolidating years of hard work, getting chips to talk to one another, and shifting away from trying to make do with noise as the field gets ever more international in scope.

For years, quantum computing’s news cycle was dominated by headlines about record-setting systems. Google and IBM researchers have had arguments over who did what, and whether it was worth the effort. The time for arguing about who has the fastest processor seems to be over: the firms are now focused on the real world and preparing for it. Everyone is acting like grown-ups suddenly.

As if to emphasize how much researchers want to get off the hype train, IBM is expected to announce a processor in 2023 that bucks the trend of putting ever more quantum bits, or “qubits,” into play. Qubits are the processing units for quantum computers and can be made from a variety technologies, such as superconducting circuitry or trapped ions.

IBM is a long-standing advocate of superconducting qubits and has made steady progress over the years in increasing the number that it can pack onto a chip. In 2021, for example, IBM unveiled one with a record-breaking 127 of them. In November, it debuted its 433-qubit Osprey processor, and the company aims to release a 1,121-qubit processor called Condor in 2023.

But this year IBM is also expected to debut its Heron processor, which will have just 133 qubits. Although it might seem like a backwards move, Heron’s qubits are of the highest quality. Each chip will be able connect directly to other Heron processors. This is a significant shift from single quantum computing chips to “modular” quantum computer built from multiple processors connected together. This move is expected to increase quantum computers’ scale.

Heron signals larger shifts within the quantum computing industry. Experts suggest that we may see general-purpose quantum computer sooner than we thought possible due to recent breakthroughs, aggressive planning, and high levels funding. Michele Mosca is the deputy director of the Institute for Quantum Computing, University of Waterloo. “Overall, things seem to be moving at a rapid pace.”

Here are some areas experts expect to see improvement.

Stringing quantum computers together

IBM’s Heron project is just a first step into the world of modular quantum computing. The chips will be connected to conventional electronics so that they can’t maintain the “quantumness” of information as it moves between processors. However, the hope is that these chips, when connected with quantum-friendly microwave or fiber-optic connections, will allow for distributed, large-scale quantum computing with up to a million connected qubits. This may be the number of qubits needed to run error-corrected, useful quantum algorithms. “We need technologies that scale both cost and size, so modularity is important,” Jerry Chow, director of IBM Quantum Hardware System Development, says.

Other companies are beginning similar experiments. “Connecting stuff together is suddenly a big theme,” says Peter Shadbolt, chief scientific officer of PsiQuantum, which uses photons as its qubits. PsiQuantum is finishing up a silicon-based modular chips. Shadbolt says the last piece it requires–an extremely fast, low-loss optical switch–will be fully demonstrated by the end of 2023. He says, “That gives us an feature-complete chip.” Then warehouse-scale construction can begin: “We’ll take all of the silicon chips that we’re making and assemble them together in what is going to be a building-scale, high-performance computer-like system.”

The desire to shuttle qubits among processors means that a somewhat neglected quantum technology will come to the fore now, according to Jack Hidary, CEO of SandboxAQ, a quantum technology company that was spun out of Alphabet last year. Quantum communications, where coherent qubits are transferred over distances as large as hundreds of kilometers, will be an essential part of the quantum computing story in 2023, he says.

“The only way to scale quantum computing is by creating modules with a few thousand qubits, and then linking them to achieve coherent linkage,” Hidary explained to MIT Technology Review. It could be in the same place, but it could also be spread across campus or across cities. In recent years, many of these communication components have been proven to be effective. In 2017, for example, China’s Micius satellite showed that coherent quantum communications could be accomplished between nodes separated by 1,200 kilometers. And in March 2022, an international group of academic and industrial researchers demonstrated a quantum repeater that effectively relayed quantum information over 600 kilometers of fiber optics.

Taking on the noise

At the same time that the industry is linking up qubits, it is also moving away from an idea that came into vogue in the last five years–that chips with just a few hundred qubits might be able to do useful computing, even though noise easily disrupts their operations.

This notion, known as “noisy intermediate quantum” (NISQ), was a way to get some short-term benefits out of quantum computing. It could have been years before we reach the ideal large-scale quantum computer with hundreds of thousands of qubits dedicated to correcting errors. However, NISQ optimism seems to be fading. Joe Fitzsimons (CEO of Horizon Quantum Computing, Singapore) says that the hope was that computers could be used before error correction. But, that is changing.

Some companies are taking aim at the classic form of error correction, using some qubits to correct errors in others. Last year, both Google Quantum AI and Quantinuum, a new company formed by Honeywell and Cambridge Quantum Computing, issued papers demonstrating that qubits can be assembled into error-correcting ensembles that outperform the underlying physical qubits.

Other teams are looking to see if there is a way to make quantum computers fault-tolerant without as much overhead. IBM has explored the possibility of identifying the noise that causes error in its machines and then programming to subtract it (similarly to noise-canceling headphones). It’s not perfect, however. The algorithm is based on a prediction of what noise will occur, not what actually happens. But it does a decent job, Chow says: “We can build an error-correcting code, with a much lower resource cost, that makes error correction approachable in the near term.”

Maryland-based IonQ, which is building trapped-ion quantum computers, is doing something similar. Chris Monroe, chief scientist at IonQ, says that the majority of errors in our programs are caused by us. “That noise is known, and we have used different mitigation methods to increase our numbers. “

Getting serious about software

For all the hardware progress, many researchers feel that more attention needs to be given to programming. “Our toolbox is definitely limited, compared to what we need to have 10 years down the road,” says Michal Stechly of Zapata Computing, a quantum software company based in Boston.

The way code runs on a cloud-accessible quantum computer is generally “circuit-based,” which means the data is put through a specific, predefined series of quantum operations before a final quantum measurement is made, giving the output. Fitzsimons states that this is a problem for algorithm designers. Conventional programming routines involve looping steps until the desired output is reached and then moving on to another subroutine. Circuit-based quantum computing does not allow for looping. The output ends the computation. There is no way to go around again.

Horizon Quantum Computing is one company that has been developing programming tools to allow for these flexible computation routines. Fitzsimons states, “That gives you access to a different system in terms of what you can run, and we’ll begin rolling out early access in this coming year.”

Helsinki-based Algorithmiq is also innovating in the programming space. CEO Sabrina Maniscalco says, “We need non-standard frameworks for programming current quantum devices.” Algorithmiq’s new drug discovery platform Aurora, which combines quantum computation results with classical algorithms, is now available. This hybrid quantum computing is a rapidly growing area and is widely recognized as the way the field will function in the long-term. The company says it expects to achieve a useful quantum advantage–a demonstration that a quantum system can outperform a classical computer on real-world, relevant calculations–in 2023.

Competition around the world

Change is likely coming on the policy front as well. Government representatives including Alan Estevez, US undersecretary of commerce for industry and security, have hinted that trade restrictions surrounding quantum technologies are coming.

Tony Uttley is the COO of Quantinuum. He says he is actively in dialogue with the US government to ensure that this does not adversely affect an industry still young. “About 80% of our system is components or subsystems that we buy from outside the US,” he says. “Putting a limit on them doesn’t help, and it doesn’t make us any more competitive with other companies in other countries around this world
There are many competitors. Last year, the Chinese search company Baidu opened access to a 10-superconducting-qubit processor that it hopes will help researchers make forays into applying quantum computing to fields such as materials design and pharmaceutical development. The company says it has recently completed the design of a 36-qubit superconducting quantum chip. A spokesperson for Baidu told MIT Technology Review that the company will continue to make breakthroughs in integrating both quantum software and hardware, and help with the industrialization and commercialization of quantum computing. Alibaba is also home to researchers who are working on quantum computing using superconducting qubits.

In Japan, Fujitsu is working with the Riken research institute to offer companies access to the country’s first home-grown quantum computer in the fiscal year starting April 2023. It will have 64 superconducting qubits. Shintaro Sato (head of Fujitsu Research’s quantum laboratory) says that the initial focus will be on materials development, drug discovery and finance.

Not everyone is following the well-trodden superconducting path, however. In 2020, the Indian government pledged to spend 80 billion rupees ($1. 12 billion when the announcement was made) on quantum technologies. Photonics technologies will receive a large chunk of the funds, including for satellite-based quantum communications and innovative “qudit” photonics computing.

Qudits broaden the data encoding capabilities of qubits. They offer three, four or more dimensions as opposed to the binary 0 and 1. This increases the possibility for errors to occur, but it does not increase the error margin. Urbasi Sinha, who is responsible for the quantum information and computing laboratory at Bangalore’s Raman Research Institute, says, “This type of work will allow us to create an area rather than competing against what has been going on for many decades elsewhere.” Although quantum technology is becoming more competitive internationally, it remains largely collaborative for now. Monroe states that while competition is fierce in this field, it is also something Monroe likes. “We don’t have a zero sum game mentality. There are many technologies out there at different maturity levels and we all play together right here. 06431.

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