In context: Google's quantum AI researchers have demonstrated that it is possible to reduce errors in quantum calculations by increasing the number of qubits used. That may sound straightforward – and it would be with classical computing – but things work differently when dealing with quantum systems.
As Google CEO Sundar Pichai highlights, qubits are so sensitive that even something as minuscule as stray light can result in calculation errors, and the problem only gets worse as quantum computers grow in size. Considering the best quantum algorithms require much lower error rates than what we have today, it is a problem that must be overcome if quantum computers are to have a meaningful future. This is where quantum error correction comes into play.
Pichai notes that quantum error correction encodes information across multiple physical qubits to create a "logical qubit," and that this technique is believed to be the only way to create a large-scale quantum computer with error rates low enough to actually be useful.
In testing, Google created a logical qubit comprised of 49 physical qubits that was able to outperform a version made with 17 qubits. This confirmed to the team that quantum error correction does not just work in theory, but also in practice.
Google believes that someday, quantum computers will be able to help tackle problems that are beyond the scope of traditional computers. Possibilities include identifying molecules for new medicines, coming up with more efficient battery technology and creating fertilizer using less energy. The real payoff could happen when quantum computers are able to work in tandem with classical computers to further advance our understanding of the world around us.
A quantum future is likely still far away, however. Pichai said several components of their quantum computers will need to be improved such as their cryogenics and the design and materials of their qubits. Unsurprisingly, Google is also exploring the use of machine learning to improve their processes. AI really is everywhere these days.
Google's latest research has been published in the journal Nature.
