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Google’s Willow is a 105-physical-qubit quantum processor announced on December 9, 2024. Its most important result was not simply that the chip is larger: Google’s team demonstrated a surface-code memory experiment in which logical errors fell as the tested error-correcting code grew. That is evidence of progress toward scalable quantum error correction—not proof that Willow is already a practical, general-purpose fault-tolerant computer.
What is Google’s Willow quantum chip?
Willow is a superconducting quantum processor developed by Google Quantum AI. Google announced the 105-qubit chip on December 9, 2024. The number refers to physical qubits: hardware elements that can be controlled and measured, but that are individually vulnerable to errors. It does not mean Willow contains 105 reliable, fault-tolerant logical qubits.
A logical qubit is encoded across multiple physical qubits so that error-correction routines can detect and correct faults. The central Willow result concerns the performance of such an encoded memory, rather than a count of finished logical qubits. Google’s specification sheet also reports a mean simultaneous single-qubit gate error of 0.035% ± 0.029%; that is a physical gate measurement, not the logical error rate in the memory experiment. Google Quantum AI’s Willow specification sheet
What did the Willow error-correction experiment show?
The peer-reviewed paper “Quantum error correction below the surface code threshold,” published in Nature on December 9, 2024, reports two below-threshold surface-code memories on Willow. One was a distance-7 code integrated with a real-time decoder. In the tested conditions, the logical memory error rate decreased as the surface-code distance—and the physical resources used for the code—increased. The paper describes this as exponential suppression of logical errors with increasing code size. Read the Nature paper
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What “below threshold” means
Error correction has a threshold: for a given code and noise model, physical errors must be sufficiently low for adding more qubits to the code to improve its encoded performance. Below that threshold, increasing code size can reduce the chance that an error corrupts the logical information instead of making the encoded memory worse. Willow’s result is significant because the team demonstrated this favorable scaling in the reported surface-code memory experiment.
Why code distance matters
Surface-code distance describes the scale of an error-correcting code and is related to how many physical qubits it uses. Increasing distance requires more hardware, but can make a logical qubit more resistant to errors when the system operates below threshold. Willow’s distance-7 result is an experimental step in that direction; it does not establish how far the same improvement can be extended or how much hardware a useful large-scale computation would require.
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Does Willow prove that bigger quantum computers are better?
Only in a specific, carefully bounded sense. In the tested Willow surface-code memories, larger code distance corresponded to lower logical error rates. That supports the idea that adding physical qubits can improve encoded performance when the underlying error rates and error-correction process are suitable.
It is not an unlimited scaling law. A larger processor does not automatically make every quantum task more accurate or useful: the result depends on the code, hardware quality, control and measurement errors, decoding, and operating conditions. The experiment demonstrates progress within the tested architecture and range, not that all engineering barriers to fault-tolerant computing have been solved.
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Willow’s error-correction result and its speed benchmark are different claims
Google’s December 2024 announcement also highlighted a random circuit sampling benchmark. Google said Willow completed that specialized task in under five minutes and estimated that a leading classical supercomputer would take 1025 years. The five-minute figure is Google’s reported benchmark time; the classical runtime is Google’s estimate, not an independently measured duration. Google’s Willow announcement
Random circuit sampling is a deliberately specialized benchmark, not a demonstration that Willow can complete ordinary useful workloads faster than classical computers. It should not be confused with the surface-code experiment: the error-correction result concerns whether encoded quantum information becomes more robust as a code grows, while random circuit sampling measures performance on a particular computational task.
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What Willow does—and does not—establish
- Established: Google reported below-threshold surface-code memory experiments on Willow, including a distance-7 code with real-time decoding, and lower logical error rates as the tested code distance increased.
- Not established by these results: that Willow is a general-purpose fault-tolerant computer, has 105 fault-tolerant logical qubits, or solves useful commercial workloads.
- Not established: that quantum processors can replace classical computers for ordinary tasks, break encryption, or deliver near-term consumer applications.
Google Research’s later discussion of dynamic surface codes describes the Willow result as a milestone in improving logical-qubit robustness as physical qubits are added. It provides follow-up context, rather than a replacement for the direct 2024 Willow experiment. Google Research on dynamic surface codes
For readers who want an introduction to the subject, Google’s announcement also points to a free quantum error-correction course. Explore Google’s quantum learning resources
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