Even though I’ve spent my whole career in emerging technologies, this statement surprises and thrills me. Not so long ago, everyone thought quantum computing was sci-fi – a physical impossibility. The mere existence of the field’s current race for scale is a fantastic achievement.
Not everyone agrees with me that it’s a winnable contest though, either in a reasonable timeframe or at all. Given the scale of the challenge to get from where we are today to large-scale useful quantum computers, am I right to believe we will get there?
Why quantum computing matters
Before I dive into the scale of the challenge, I want to explain why I think quantum computing is important.
Right from the start, quantum computers weren’t entirely about replacing their classical cousins. Instead, they were (and are) intended to tackle specific kinds of problems that classical computers either can’t solve in a useful timeframe or will never be able to solve at all. These are typically complex problems involving many factors and possible combinations.
When you start to think about all the data we can access to make the modern world work better, these sorts of problems crop up all over the place. For instance, solving them could help us simulate new molecules to speed up drug discovery, plan sustainable urban environments and optimize global shipping routes to be green as well as profitable. Many other proposed use cases are just as significant, and I’m sure there will be plenty more to come.
Quantum computing’s scale challenge
Realizing such aspirational benefits is no mean feat. So far, scientists, technologists and engineers have spent 40 years working out how to build a quantum computer in the real world. After decades of graft, the past few years have seen incredible progress.
Google, IBM and others believe 1,000 qubit systems are only a few years away. Both tech giants have also released public roadmaps that include reaching one million qubits – by 2029 for Google,1 and 2030 for IBM.2
The three obstacles everyone is trying to overcome are noise, errors and scaling up the physical connection required between qubits. Noise refers to anything that interferes with qubits’ ability to maintain their delicate quantum state, from stray atoms to vibration or temperature changes. Such interference causes qubits to “decohere” or lose the quantum properties that give them their computing superpower.
To make a hard challenge harder still, for qubits to be in the quantum state that gives quantum computers their superpower, all of them need to be physically connected to each other within a quantum computer. Achieving this is an enormous challenge that only gets more difficult as you add more qubits. As a result, it is limiting scalability of current devices and the types of problems we can ask them to solve.
Pushing quantum technology forward
Recent breakthroughs addressing these challenges have electrified the quantum community and galvanized the race to commercial scale. Most notably, in January 2022, three research teams published separate papers showing that large-scale, fault-tolerant quantum computers could be “made and used in the real world”.3The teams from Australia, Japan and the Netherlands not only show it is possible to make 99.9% error-free quantum computers, far above the 99% threshold, but to do so in a way that is compatible with existing technology for manufacturing silicon-based processors at scale.
The news is a particular boost for developers focused on silicon-based quantum technologies. The most prominent are the superconducting systems being developed by giants such as IBM and Google, as well as by quantum startups such as Rigetti Computing. IBM’s release of a 127-qubit processor in late 2021 was another piece of good news for this branch of the sector, along with the company’s expected launch of a 1,000-qubit successor in 2023.4 Rigetti Computing’s roadmap is also promising, with near-term milestones of 1,000 qubits by 2025, and 4,000 qubits by 2027.5
Developers of competing “gate-based” technologies, including photonics, trapped ions, cold atoms and quantum dots, are also working hard to find answers to the noise and errors at the core of the scale challenge. At the same time, some companies are taking a different tack and looking at what quantum computing can do now.
Quantum annealing, for example, might not be as broadly useful as gate-based technologies, but research by GlaxoSmithKline in 2021 found that D-Wave’s quantum annealing processor can already compete with classical computers in terms of solving realistic optimization problems – problems about finding the best possible solution.6
Another research area I’m watching closely is hybrid classical and quantum computing. By pairing a classical computer processor with a quantum co-processor, you can, in theory at least, access quantum’s capabilities in a more reliable way. In fact, some believe that such combinations will deliver the first practical uses of current “noisy” quantum computers (NISQ - Noisy Intermediate-Scale Quantum), while we wait for large-scale fault-tolerant quantum computers to be available.
One of my own fields of expertise, machine learning and artificial intelligence, is an ideal candidate for hybrid combinations, as it uses large datasets to tackle complex problems. I’m confident that quantum-charged AI systems could speed up solution-finding for problems as diverse as fraud detection and advanced weather modeling.
Others share my confidence (but not everyone)
My optimism that the recent technology advances, publicized roadmaps and viable use cases will lead to commercial-scale quantum computing is shared by others. But it’s not universal.
Sharing my bullish corner are my EY colleagues who are trialling quantum secured communication services developed by Toshiba and partners to secure data transmitted between two of our offices in London.7 Quantum software company Zapata is also close by. They believe that tech progress, levels of business investment and tentative steps out of research and development will lead to hybrid classical-quantum systems in “real customer use” within two years.8
Google is more circumspect, however. They believe it could take up to a decade to achieve a useful, error-corrected quantum computer.9 And although 170 organizations are already using IBM’s 27 quantum systems, it is still for research rather than operational purposes.10
A fair number of other experts, including within the field, believe overcoming the noise problem at scale is such a big challenge that general applications, or “broad quantum advantage” could still be decades away if we get there at all.
