Quantum computing and the burden of proof

Quantum pioneers disagree on when advantage will arrive, but agree it's time to prove it – and for enterprises to prepare

Quantum computing is moving from ambitious promises towards the harder task of proving commercial value. Vendors ORCA and QuEra disagree over how soon genuine quantum advantage will arrive, but there is growing agreement that businesses should start identifying suitable applications now, benchmarking them against classical alternatives and preparing for a future in which quantum becomes another tool in the computing toolbox.

Clem O’Rourke is a consultant at Origami Labs, a company that specialises in “difficult defence and security problems where you can't just take an off-the-shelf approach”.

As part of this approach, he has been experimenting with quantum computers, to see whether they offer an advantage over classical computing. So far, the answer has been no. Indeed, it got to the stage where O'Rourke had to erase the “Q word” from any planning discussions, such was the cynicism it provoked.

“So far they've been too noisy or too small to be able to actually do anything at scale,” he told Computing. “Everything has a caveat.”

Not that he’s cynical himself. The industry is moving rapidly in the right direction, he said, and machine learning and data-efficiency experiments provide “really good indications of where you want to push,” once devices reach sufficient scale and capability.

Daniel Goldsmith, senior quantum computing technologist at accelerator Digital Catapult and head of QTAP, the Quantum Technology Access Programme, says the most successful organisations he’s seen are those that put the business case first, rather than obsessing over the number of qubits.

“It was organisations that brought to the programme people who already had a really detailed knowledge of what the business problems were in their organisation, what the classical solutions were, what the classical solutions were good at, and whether gaps could be filled by quantum.”

It’s a message that many quantum startups have taken on board. Provided they scale successfully over the next few years, quantum computers are expected to offer advantages over classical systems only for particular workloads - albeit potentially highly relevant and economically important ones - including optimisation, chemistry and materials science. Cryptanalysis is another much-discussed prospective application, but one requiring substantially more capable machines.

Moreover, rather than displacing classical computing, the latest messaging from the industry has quantum computers working in tandem with HPC systems, with AI increasingly employed in areas including algorithm design and hardware control. Quantum becomes one more tool in the toolbox.

Advantage before fault tolerance?

“Today, quantum computers are toys,” Yuval Boger, CCO at Boston-based quantum computing company QuEra told Computing.

“I mean, they're beautiful toys and complex and sophisticated and expensive toys, but they're toys in the sense that there's really nothing you can do in a quantum computer that you cannot do classically.”

His firm is focused on identifying exactly where quantum can “be better” than the existing alternatives.

“What problems do you have that need solving, and what is the baseline? I mean, you have classical solutions for them. How good are the classical solutions? What would constitute a meaningful improvement?”

QuEra even tells customers to come back later if their problem isn't suitable, he went on.
“If we don't think that the problem fits, then let's reengage in a year or two.”

Indeed, a year or two, 2028 to be precise, is when Boger predicts that QuEra will be able to offer customers a fault-tolerant quantum computer capable of solving “a small subset of problems” around chemistry or materials science. Advances in AI are accelerating algorithmic design and helping with the calibration of the sophisticated lasers used in QuEra’s devices, he explained.

“AI is compressing the requirements, and therefore we feel very, very confident that there will be a meeting point in 2028.”

Richard Murray, CEO of UK-based ORCA Computing, is on the same page, although he is rather more bullish about the timelines and potential applications.

“We've made our mission to find what we think are the very first applications of quantum advantage systems - quantum systems beating classical alternatives,” he said during a press briefing in London recently, identifying molecular modelling and optimisation as areas where he believes near-term quantum computing systems can improve on classical approaches.

ORCA is also working on AI model training, using quantum computers to generate complex probability distributions in the prior stages of a neural net, potentially reducing the amount of learning the classical network has to do for some use cases, such as molecular modelling.

ORCA has just released its latest photonic device, PT-3, which is installed in a Digital Realty co-location data centre in London. Meanwhile, QuEra’s Aquila device has been available via the Amazon Braket cloud service since 2022. QuEra says its planned fault-tolerant Libra system is due to come to Amazon Braket in 2028.

Start now, benefit later

Both vendors insist that enterprises cannot wait until the hardware is fully ready before beginning work on applications. Boger estimates that selecting, developing, encoding and simulating an application could take 12 to 18 months, which is why he says prospective users interested in QuEra’s planned 2028 system should start now.

Meanwhile ORCA is pursuing advantage before general-purpose fault tolerance. Murray argued that current photonic machines can improve certain genAI and optimisation workloads as part of a hybrid quantum-GPU approach, pointing to ORCA’s ongoing work with Nvidia’s Proteina molecular simulation model. He claimed that adding a prior layer generated by is latest PT-3 device showed signs of improving molecular “designability” and diversity, although he acknowledged that the work is at an early stage.

Origami Labs’ O'Rourke said he is watching these developments closely, checking for signals of genuinely useful progress.

“People aren't going to want to spend large chunks of money until they can see is really going to help solve our problem because that's what they care about,” he said, adding his voice to those suggesting that the time to start is now.

“Five years ago, they had the time to go, ‘we need to think about what's going to happen in 10 years’. Now they're in the space of 'we need to deal with the now'.”