Can Quantum Computers Break Crypto in Minutes? Inside Google’s New Findings

If someone told you a computer could recover a Bitcoin private key in ten minutes, you might laugh—Google does not. The search giant recently moved its internal post‑quantum cryptography migration deadline forward to 2029, reflecting a reassessment of quantum‑enabled threats.

Shor’s Algorithm and the Quantum Threat

Shor’s algorithm, introduced in 1994, can factor large integers and solve elliptic‑curve discrete logarithms in polynomial time, endangering RSA, ECC, HTTPS, digital signatures and blockchain security.

Two Recent Papers Reduce Resource Estimates

The first paper, a Google Quantum AI whitepaper, optimizes the logical‑layer implementation of Shor’s algorithm for Bitcoin and Ethereum signatures. It reports that attacking the 256‑bit secp256k1 curve requires only about 1,000 logical qubits , and a fast superconducting device could recover a private key in minutes.

The second paper, from the startup Oratomic, builds on Google’s logical improvements and applies special techniques for neutral‑atom quantum computers. It estimates that 26,000 atomic qubits suffice to break a 256‑bit elliptic‑curve signature—a ~40× improvement over previous top‑line estimates.

Bitcoin researcher Justin Drake summed up the findings: the two works optimize different layers of the quantum stack, and the results are “shocking.” Both papers conclude that the quantum resources needed to break current cryptography are far lower than previously thought.

Google’s Detailed Resource Numbers

Core resource data : For secp256k1, breaking the 256‑bit ECDLP now needs <1200 logical qubits and 90 million Toffoli gates , or an alternative configuration of <1450 logical qubits and 70 million Toffoli gates .

Physical layer threshold : On a superconducting architecture with planar connectivity and a 0.1 % physical error rate (surface‑code error correction), the circuit would require fewer than 500 k physical qubits and could finish in minutes.

Fast‑clock vs. slow‑clock : Fast‑clock platforms (superconducting, silicon‑spin, photonic) have very short error‑correction cycles and can break keys in minutes, whereas slow‑clock platforms (neutral‑atom, ion‑trap) are two to three orders of magnitude slower.

Implications for Bitcoin and Ethereum

Both networks use secp256k1, but Ethereum’s account model, high‑privilege admin keys, BLS12‑381 consensus signatures and data‑availability commitments expose a broader attack surface. Specific vulnerabilities include account key exposure, admin key compromise, consensus manipulation, and data‑availability attacks.

Bitcoin’s risk is more localized: quantum mining (Grover‑based PoW) remains impractical for decades, but early coins locked with P2PK scripts and address reuse could be vulnerable.

Oratomic’s Physical‑Qubit Estimates

~10,000 physical qubits to run a cryptographic‑scale Shor algorithm.

~12,000 qubits to break ECC‑256 in roughly 10 days .

~102,000 qubits to break RSA‑2048 in about 97 days .

These numbers contrast with earlier estimates of a million physical qubits, showing a two‑order‑of‑magnitude reduction.

Code‑Rate Improvements

The papers employ quantum LDPC codes, specifically quasi‑cyclic lifted‑product (QCLP) codes, achieving a code rate of about 28 % compared with ~1 % for surface codes and ~4 % for small LDPC codes. This yields roughly 30× more logical information per physical qubit, or a ten‑fold reduction in required physical qubits for the same logical capacity.

With a physical error rate of p = 0.1 %, an uncorrectable error is expected only after ~10¹¹ cycles (≈3 years at 1 ms per cycle), which is acceptable for day‑scale Shor executions.

Hardware Platform Choices

Superconducting qubits offer speed but short coherence times; ion traps provide high fidelity but scale poorly. Oratomic’s reconfigurable neutral‑atom arrays allow dynamic 3‑D positioning of atoms, enabling on‑the‑fly qubit rearrangement, high‑fidelity entangling gates between any pair, and natural support for the non‑local connectivity required by high‑rate LDPC codes.

Compilation Strategy

The proposed compilation flow combines Pauli‑based computation with code surgery:

Circuit decomposition: split the full Shor circuit into sub‑circuits {Cᵢ} containing Toffoli, Clifford gates and intermediate Pauli measurements, fitting into the processor zone.

Teleportation to processor zone: use 2m Pauli‑product measurements (PPM) to invisibly transfer m logical qubits from memory to processor.

Pauli‑based computation: execute the computation, absorbing Clifford gates into PPM and injecting Toffoli gates via CCZ magic‑state teleportation.

Return results: another 2m PPM moves the outcome back to memory.

Authors and Motivation

The Oratomic paper lists first authors Madelyn Cain and Qian Xu (Oratomic), with collaborators including Caltech quantum‑computing pioneer John Preskill, neutral‑atom leader Manuel Endres, and quantum‑ML expert Hsin‑Yuan (Robert) Huang. Corresponding author Dolev Bluvstein, an Oratomic co‑founder, previously contributed to neutral‑atom breakthroughs at Harvard’s Mikhail Lukin lab. Their stated goal is to build the world’s first fault‑tolerant quantum computer.

Why Google Is Urgent

In security circles, “Q‑Day” denotes the moment a quantum computer can break today’s encryption. Industry actions include NIST’s 2024 release of the first post‑quantum standards (FIPS 203/204/205), multi‑year migration timelines, and “harvest‑then‑decrypt” attacks where adversaries store ciphertext now for future decryption.

Google’s internal deadline of 2029 signals that its threat model now places the Q‑Day window within this decade. The company has been a proactive post‑quantum advocate, integrating hybrid X25519‑Kyber768 key exchange in Chrome (2023), offering post‑quantum TLS in Google Cloud, and publishing migration guides.

Historical Trend of Shor Resource Estimates

Over the past two decades, estimates for the qubits needed to run Shor’s algorithm have steadily declined, driven by breakthroughs in quantum error‑correction theory (from surface codes to high‑rate LDPC codes), maturation of new hardware platforms (neutral atoms, ion traps, superconductors), and algorithmic/compilation advances that reduce circuit depth and gate counts.

The key question remains whether this downward trend will continue, further shrinking the barrier to practical quantum attacks.

Conclusion

When Peter Shor published his algorithm in 1994, quantum computers were a theoretical curiosity. Thirty‑two years later, researchers discuss breaking the world’s most widely used cryptographic systems with a few thousand qubits in minutes, underscoring the accelerating pace of quantum breakthroughs.