In context: quantum AI researchers from Google have demonstrated that it is possible to reduce the number of errors in quantum computing by increasing the number of qubits used. This may seem simple — and it would be the case with classical computing — but in quantum systems everything works differently.
As Google CEO Sundar Pichai emphasizes, qubits are so sensitive that even such a small thing as scattered light can lead to errors in calculations, and the problem only gets worse as the size of quantum computers grows. Given that the best quantum algorithms require a much lower error rate than what we have today, this is a problem that needs to be solved if quantum computers have a meaningful future. This is where quantum error correction comes into play.
Pichai notes that quantum error correction encodes information between several physical qubits to create a “logical qubit”, and that this method is considered the only way to create a large-scale quantum computer with a sufficiently low error rate to be really useful.
During testing, Google created a logical qubit consisting of 49 physical qubits, which was able to surpass the version with 17 qubits. This confirmed to the team that quantum error correction works not only in theory, but also in practice.
Google believes that someday quantum computers will be able to help solve problems beyond the capabilities of traditional computers. Opportunities include identifying molecules for new drugs, developing more efficient battery technologies, and creating fertilizers with less energy consumption. The real payoff can happen when quantum computers can work in tandem with classical computers to further improve our understanding of the world around us.
However, the quantum future is probably still a long way off. Pichai said several components of their quantum computers would need to be improved, such as their cryogenics, the design and materials of their qubits. Unsurprisingly, Google is also exploring the possibility of using machine learning to improve its processes. AI is really everywhere these days.
Google’s latest research was published in the journal Nature.
