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Google Cuts Quantum 'Magic State' Errors 40-Fold on Its Willow Chip in a Science Paper

Google Quantum AI reports T-states at 99.99 percent logical fidelity using a technique called magic state cultivation, a step toward cheaper error-corrected quantum computers.

Outspoken Digest Technology Desk

Friday, October 16, 2026/2 min read

A computer-rendered illustration of a wire-bonded superconducting quantum chip with six transmon qubits on a grey carrier, dated 8 September 2025, an illustration of a generic superconducting chip and not of Google's Willow processor
Photo: OJB Quantum via Wikimedia Commons (CC BY 4.0)

Some of the most expensive ingredients in a future quantum computer are not qubits but special quantum states called magic states. Google Quantum AI says it has found a cheaper way to make them. In a paper published in Science, the team reports a roughly 40-fold reduction in errors and logical T-states at 99.99 percent fidelity on its Willow processor, according to the company's blog post on 15 October.

Magic states are what let an error-corrected quantum machine perform the operations that take it beyond classical computing. Each one can be used only once, so they are scarce, and producing them to a high standard is resource-intensive.

What is magic state cultivation?

The older approach, distillation, was projected by some estimates to eat up as much as 95 percent of a quantum computer's capacity. Cultivation works more like a filter. It prepares a rough state in a small patch of qubits, runs checks, discards any attempt that shows a flaw, and grows the survivors, as The Quantum Insider described it. The team also showed it could move states from color codes into surface codes, a first step it called a technical challenge.

What did Google actually measure?

The headline numbers apply to state preparation, not to the processor as a whole. The main experiment reached an error rate of roughly one in 10,000 after about four hours of reinforcement-learning calibration. Willow has 105 superconducting qubits; the distance-5 experiment that grafted states into a larger code used 54 of them.

Measuring the result was a puzzle of its own. The team's original tomography approach could overstate fidelity, so they built a method they call kickback tomography that gives a lower bound. Calibration made a large difference: Insider said it improved both the logical error probability and the share of retained attempts by about an order of magnitude. The researchers named in the paper include Rosenfeld, Gidney, Shutty and Jones. The quality figures also apply only to accepted attempts, which means the retention rate affects the real cost of a computation.

What are the limits of the result?

Google is open about them. After grafting, a storage test showed logical errors about seven times higher than simulations predicted, which the researchers attribute mainly to leakage that the simulations left out. The authors write that cultivation still needs to be demonstrated at a larger scale, and the Insider noted the work does not by itself solve the resource problem at practical scale. The article quoted only the Google researchers, with no outside expert comment.

The team expects gains from better calibration, leakage removal, a simpler circuit layout and larger codes. For now this is a lab milestone rather than a product, but it targets one of the line items that could decide how big, and how costly, a useful quantum computer has to be.

Published in The Outspoken Digest

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