Google claims its Willow quantum processor generates complex calculation states with roughly 40 times fewer errors. This breakthrough tackles a major hurdle in building machines powerful enough to breach bitcoin wallets—a feat that could be accomplished by quantum systems in the future.
Published in Science this week, the finding highlights an overlooked angle in the bitcoin quantum debate—a discussion that typically focuses on attacker machine size while ignoring how much horsepower is consumed by pre-calculation setup.
Why Bitcoin’s Oldest Coins Give Attackers More Time
Bitcoin wallets use secret keys to authorize transactions and matching public keys that let the network verify those approvals. While making a payment typically exposes the public key, certain transaction types are designed to reveal it right away.
Deriving a private key from its public counterpart requires an impractical volume of computing power, ensuring that crypto wallets cannot be reverse-engineered through conventional methods in practice.
In theory, a sufficiently powerful quantum computer executing Shor’s algorithm could solve that equation. Any attacker extracting the private key can easily approve transactions as the genuine owner, though this method was originally introduced by mathematician Peter Shor in 1994 and remains unproven in practice.
Locking a recovery seed inside a physical drawer provides zero protection against this threat, since attackers extract their target data directly from information already published on the blockchain—a vulnerability that is created by public ledger exposure.
Modern payment formats obscure the public key behind a digital fingerprint until the owner initiates a transaction. An attacker eyeing a hidden key must wait for that reveal and solve the private key fast enough to be inserted before the network finalizes the transfer.
Abandoned coins present a tricky dilemma for the network. While Bitcoin can deploy enhanced spending safeguards, owners still require their original keys to migrate old funds over. Without those keys, moving the assets becomes impossible, leaving exposed public keys vulnerable to any attacker who is equipped with quantum capabilities in the future.
Miners left public keys exposed on several of Bitcoin’s earliest coin hoards from the moment they were first generated.
Dormant coins have also begun shifting as quantum concerns intensify across the industry. On Oct. 7, an investor transferred 100.02 BTC untouched since July 2010 after 16 years, representing around $8.5 million. Meanwhile, six wallets inactive since 2011–2014 moved another 553.59 BTC in August, an stash that was valued at roughly $40 million at the time.
These coin movements do not definitively prove that owners are reacting to quantum risks, since shifting funds often stems from changing wallets, reorganizing portfolios, or preparing for a sale—actions that are routinely driven by ordinary market activity.
The Cost of Preparing for What Comes Next
Quantum systems process data using fragile units known as qubits. Environmental factors like heat, vibration, and stray signals easily disrupt these delicate components and introduce errors, while scaling up the qubit count inherently opens up more opportunities to be disrupted by external noise.
Engineers tackle this challenge by clustering numerous physical qubits into fault-tolerant groups that detect and fix operational glitches. These specialized clusters function like a far more dependable unit, a concept that is commonly known as a logical qubit.
These logical units require a digital form of fuel to perform specific calculations—specially prepared quantum conditions known as “magic states.” Because every operation consumes a state, the system must continuously manufacture fresh ones throughout the run—a resource that is steadily depleted during complex processing.
Picture a busy restaurant kitchen where every main course demands a freshly made, single-use sauce. While some chefs cook the main dishes, others must constantly whip up fresh batches. In quantum computing, processors dedicated to generating magic states represent hardware capacity that cannot be assigned to perform other computational tasks.
Google’s new technique, dubbed cultivation, begins with a crude initial state, screens it for defects, and discards any corrupted runs. This approach aims to yield pristine quantum states using far less hardware than earlier methods required—a efficiency that was previously considered unachievable by many researchers.
The company recorded approximately 99.99% fidelity—a metric tracking how precisely the final output matched the team’s target parameters—a benchmark that was achieved through refined state cultivation.
That success rate reflects only the states that successfully passed screening. Willow retained roughly 8% of its initial runs following standard preparation and measurement checks. Out of every 100 attempts, about eight candidates were selected to advance to execution.
Upcoming milestones involve expanding this process across far larger systems while preserving state stability during extended computational runs. Engineering teams emphasize that additional refinement remains necessary for real-time execution and integrating states into more robust fault-tolerant architectures—a challenge that is now being prioritized by lead researchers.
How It Connects With Previous Research
In March, Google projected that a future superconducting quantum processor featuring under 500,000 physical qubits could crack the core cryptography safeguarding Bitcoin and Ethereum wallets, assuming specific hardware conditions are successfully met by developers.
In September, highlighted scientific progress reducing the computational burden of a key algorithm step behind that exploit. That research focused on a single component while omitting the full attack strategy and the physical hardware overhead that would be required to execute it.
These studies substantially lower the computational load facing potential attackers. Meanwhile, cultivation slashes the overhead expenses of powering quantum hardware during execution—an operational bottleneck that is effectively alleviated by Google’s new approach.
These efficiency gains cannot simply be multiplied together. Google’s March projection had already factored in streamlined magic-state generation. The latest trial merely validates a portion of that hardware framework, rather than delivering another 40-fold drop in the estimated cost that would be required to compromise Bitcoin.
The March paper also illustrates how much energy such an exploit would consume. For a modeled breach lasting roughly nine minutes after exposing a public key, Google calculated that the system would require about 500,000 highly reliable magic states per second—a resource threshold that must be consistently supplied throughout the process.
