Google demonstrated a method that reduces errors in quantum computing by approximately 40 times

Google's Quantum AI team has demonstrated significant progress toward overcoming one of the major technical obstacles in quantum computing. According to a study published Thursday in the journal Science, the company tested a new method on its Willow quantum processor that reduced the error rate by approximately 40 times.

The technology is called Magic State Cultivation, and its goal is to create more reliable quantum states needed for quantum computing while using fewer resources. According to researchers' estimates, producing these states could consume up to 95% of a quantum computer's computational capacity, leaving fewer resources for the actual computations.

So-called "magic states" are essential for performing the operations required for universal quantum computing. However, achieving them with a sufficiently low error rate has remained one of the key challenges in building quantum systems capable of reliably performing complex tasks.

Google's approach involves the use of coordinated measurements, which allow researchers to detect errors and discard unreliable results. As a result, higher-quality quantum states can be obtained using fewer resources.

In the experiment conducted on the Willow processor, researchers achieved a logical fidelity of 99.99% for T-type magic states. This figure reflects how closely the obtained quantum state matches the desired state.

As part of the study, the team also demonstrated that states produced using the new method can be transferred between two different quantum error correction methods. This result is significant for integrating the technology into Google's existing quantum architecture.

The study provides experimental confirmation of an approach that was theoretically developed back in 2024. Despite the results achieved, Google notes that the technology still requires scaling and further development before it can be put to practical use.

If the method proves effective on larger quantum systems as well, it could reduce the hardware resources needed to build error-resistant quantum computers. This could mark an important step in moving quantum computing from laboratory experiments toward practical application.