This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: Qubits, the quantum equivalent of digital bits, are fragile and prone to errors. That makes building reliable quantum computers extremely difficult.
One fix has been to use traditional magic state distillation, which filters out flaws, but it is extremely resource-intensive. Another potential solution is magic state cultivation, which cleans up a noisy magic state (a specially prepared quantum state that is needed for advanced calculations) directly inside a protected qubit. But this approach has never been tested successfully on real hardware.
However, in a first for quantum computing, Google Quantum AI researchers have demonstrated magic state cultivation on Willow, a superconducting processor, and it has cut errors dramatically. The team first needed some errors to fix. So, in their experiment, they encoded a noisy magic state across several physical qubits, spreading the quantum information over a small grid of qubits to protect it against errors.
Then, they tried to weed out the errors in the noisy state using helper qubits to scan the information for mistakes without destroying the delicate data itself. If the checks caught any flaws, the system threw that attempt away and started over. If an attempt passed every test, the refined magic state was kept for further processing.
The results, which are published in the journal Science, were striking. "Cultivation reduces the error by a factor of 40," the scientists wrote. And that yielded refined magic states with a fidelity of at least approximately 99.99% (a measure of how closely the prepared quantum state matches the intended state).
Checking such tiny levels of error required a new approach, so the scientists developed a checking method called kickback tomography. It is capable of detecting remaining errors using far fewer measurements than traditional techniques. And the filtering was strict.
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