Google has demonstrated a quantum computing technique that reduces errors in preparing crucial quantum states by about 40 times, advancing efforts to build machines capable of running complex algorithms reliably.
The experiment achieved 99.99% logical fidelity for specially prepared “magic states” on Google’s Willow processor.
The company said the findings, published in Science, bring a resource-intensive component of quantum computing closer to practical use.
For Bitcoin, the advance strengthens the case for preparing for future quantum threats. However, the experiment does not demonstrate a computer capable of stealing Bitcoin or establish a deadline for when such attacks might become possible.
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Magic states provide an essential ingredient for the operations required in universal, error-corrected quantum computing. Producing them reliably can consume substantial computing resources, limiting the capacity available for useful calculations.
Google’s technique, called “magic state cultivation,” starts with a noisy quantum state and uses coordinated measurements to identify errors. The process rejects flawed attempts while producing cleaner states that can support more demanding computations.
Researchers Craig Gidney, Noah Shutty, and Cody Jones developed the approach theoretically in 2024. The latest experiment demonstrated that it works on physical hardware.
The team also transferred states between two approaches to quantum error correction, known as the color code and the surface code. That matters because successful state preparation must eventually connect with the architecture running a larger computation.
Google acknowledged that cultivation still needs to work at a greater scale. Its reported fidelity describes the quality of prepared T-states, rather than the reliability of an entire quantum algorithm.
The result, therefore, addresses an important engineering obstacle while leaving the broader challenge of building a useful, fault-tolerant machine unresolved.
Bitcoin’s quantum vulnerability centers on the elliptic-curve cryptography used to authorize transactions.
A sufficiently powerful quantum computer running Shor’s algorithm could derive a private key from an exposed public key, potentially allowing an attacker to forge signatures and spend the associated coins.
The challenge extends beyond producing one exceptionally clean quantum state. An attack would require a large system capable of executing a lengthy sequence of operations with sufficiently low error rates.
A March 2026 whitepaper coauthored by Google researchers estimated that a 256-bit elliptic-curve attack could require fewer than 1,200 logical qubits and fewer than 90 million Toffoli gates under one proposed design.
Under specified superconducting hardware assumptions, the authors estimated execution times of minutes using fewer than 500,000 physical qubits. These are modeled resource requirements, rather than a demonstrated attack capability.
Magic-state improvements matter because they could reduce the overhead of executing such algorithms. However, Google’s latest experiment does not establish a 40-fold reduction in the resources or time needed to compromise Bitcoin.
Bitcoin developers are already examining ways to reduce exposure.
BIP 360 proposes Pay-to-Merkle-Root, an output structure intended to mitigate attacks against public keys exposed for extended periods.
Its scope is limited: protecting against that exposure does not automatically solve attacks targeting keys revealed when transactions are spent.
Any broader transition would require decisions about cryptographic designs, network rules, and how users move existing funds. Publication of a Bitcoin Improvement Proposal does not establish community agreement or guarantee adoption.
Google’s result makes that preparation more relevant by demonstrating progress on an enabling technology. It provides evidence that quantum engineering is advancing, but offers no direct evidence that Bitcoin’s signatures can currently be broken.
The practical question is how quickly Bitcoin can prepare as researchers continue lowering the barriers to reliable quantum computation.