In a recent development that could reshape the conversation around the vulnerability of major blockchain networks to quantum computing, a group of cryptocurrency researchers has published a paper—shared with CoinDesk—that suggests the timeline for a practical quantum attack on Bitcoin and Ethereum may be considerably longer than previously estimated. The researchers report that both human participants and artificial intelligence agents have managed to surpass the performance of Google’s March 2024 benchmark on a pivotal calculation that underpins Shor’s algorithm, the quantum algorithm widely regarded as capable of breaking the cryptographic foundations of most modern digital currencies. Shor’s algorithm, introduced by mathematician Peter Shor in 1994, provides a method for efficiently factoring large integers and computing discrete logarithms—tasks that are computationally infeasible for classical computers but become tractable for sufficiently powerful quantum machines.
The security of Bitcoin, Ethereum, and countless other cryptocurrencies relies on the hardness of these mathematical problems. If a quantum computer were able to run Shor’s algorithm at scale, it could, in theory, derive private keys from publicly visible addresses, enabling the theft of funds and the collapse of trust in the blockchain ecosystem. The new paper focuses on a specific sub‑routine within Shor’s algorithm known as the modular exponentiation step.
This step is the most resource‑intensive portion of the algorithm and determines the overall quantum circuit depth and qubit count required for a successful attack. In March 2024, Google announced a breakthrough in executing this sub‑routine on its quantum processor, achieving a record‑setting fidelity that many observers interpreted as a marker on the quantum‑risk timeline. The announcement prompted a wave of speculation that the era of quantum‑enabled crypto theft could be only a few years away.
However, the research team—comprising cryptographers, quantum physicists, and AI specialists—re‑examined the assumptions behind Google’s result. They designed a series of experiments in which both human mathematicians and advanced AI models were tasked with optimizing the modular exponentiation circuit.
The goal was to minimize the number of quantum gates and the overall error rate, thereby reducing the hardware requirements for a functional attack. Remarkably, the participants succeeded in producing circuit designs that required roughly half the number of qubits and gate operations compared to Google’s original implementation. The implications of this achievement are twofold.
First, it demonstrates that the quantum community is not limited to hardware advancements; algorithmic and software‑level optimizations can dramatically alter the feasibility of attacks. Second, by cutting the resource estimate in half, the researchers effectively push the projected timeline for a viable quantum threat further into the future.
Their calculations suggest that, even with optimistic growth rates in quantum hardware, a system capable of executing the optimized version of Shor’s algorithm on Bitcoin‑scale keys would likely not appear until the late 2030s or beyond. While the study does not claim that quantum attacks are impossible, it emphasizes that the “quantum clock” ticking over the crypto industry is more complex than a simple linear progression of qubit counts. Human ingenuity and AI‑driven circuit design can introduce significant variability, meaning that security assessments must account for both hardware and software evolution.
The authors also outline several mitigation strategies that blockchain developers and users can adopt in the interim. One approach is the gradual transition to post‑quantum cryptographic primitives, such as lattice‑based signatures, which are believed to be resistant to both classical and quantum attacks. Another recommendation is to implement multi‑signature schemes and threshold wallets, which distribute signing authority across multiple keys, thereby raising the bar for any single quantum adversary. Critics of the paper caution that the experimental conditions differ from real‑world quantum hardware constraints.
The optimized circuits were tested in simulated environments, and translating those gains to physical qubits may encounter unforeseen challenges, such as decoherence and error correction overhead. Nonetheless, the consensus among experts is that the research adds a valuable layer of nuance to the ongoing discourse.
In summary, the newly released study provides evidence that the quantum threat to Bitcoin and Ethereum may be less imminent than earlier headlines suggested. By demonstrating that both humans and AI can halve the resource requirements for a critical component of Shor’s algorithm, the researchers have introduced a new variable into the risk equation—algorithmic efficiency. This development underscores the importance of proactive cryptographic upgrades and continued monitoring of quantum advancements. As the quantum computing field matures, the crypto community must remain vigilant, balancing optimism about emerging defenses with realistic assessments of the evolving capabilities of quantum attackers.