As innovation continues to accelerate, quantum computing has become an increasingly important technology to monitor as part of the broader wave of digital transformation. Quantum computing aims to solve complex problems that are impossible to address with today’s supercomputers and has strong potential across multiple industry sectors, including pharma, energy, finance, logistics, manufacturing, and materials.

However, there are significant obstacles in developing the technology that are currently limiting, and these obstacles will continue to challenge developers over the coming years. Over the next ten years, it is uncertain if quantum computing will consistently outperform today’s supercomputers for useful business-related problems, if at all.

In the new report ‘Preparing for Quantum Computing’, Lux Research addresses what businesses need to know about quantum computing, including why it is better, when it will become available, and how a company should engage with it. “Today’s supercomputers tackle difficult problems including weather modelling, genomic analysis, and computational fluid dynamics, but even the best supercomputers will always be limited in specific areas,” Lewie Roberts, senior research associate and lead report author at Lux, said. “They’re still unable to handle some important problems in areas like chemical product design, protein folding, or supply chain optimisation. It’s our belief that quantum computing will one day enable multiple industries to address some of these key problems, moving past today’s barriers and enabling further innovation.”

Problems Quantum Computing targets

Today, the main problems being targeted by quantum computing are the simulation of quantum systems, machine learning, and optimisation. Currently, quantum computing faces many barriers that limit its near-term development. There are major challenges in hardware development, which severely limit further software development. Quantum bits, or qubits, are inherently unstable, thus reducing the accuracy of any computation that relies on them; this is the first major obstacle to commercialisation.

For this reason, problems that lack clearly defined answers, such as machine learning, but still benefit from improved solutions are the best problems to target with quantum computing. Hardware developers hope to increase the stability of qubits but will ultimately have to build fault-tolerant quantum computers that can correct any errors that result from this instability. Lux Research does not expect a fault-tolerant quantum computer to become available for at least ten years.

“Quantum computing is not currently providing business value that could not be achieved with today’s existing computers, and it’s not clear when it will,” Roberts added. “For this reason, we advise companies not to make it a priority right now, unless your work is already bottlenecked by today’s supercomputing.”

For companies that must pursue quantum computing now, research projects that estimate when quantum advantage can be achieved will be key. Lux Research advises forming partnerships for these projects based on the level of internal expertise, as this greatly affects which players will be most helpful for your unique projects.

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