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How to factor 2048 bit RSA integers with less than a million noisy qubits

Canonical reference. 82% of citing Pith papers cite this work as background.

66 Pith papers citing it
3 external citations · Pith
Background 82% of classified citations
abstract

Planning the transition to quantum-safe cryptosystems requires understanding the cost of quantum attacks on vulnerable cryptosystems. In Gidney+Eker{\aa} 2019, I co-published an estimate stating that 2048 bit RSA integers could be factored in eight hours by a quantum computer with 20 million noisy qubits. In this paper, I substantially reduce the number of qubits required. I estimate that a 2048 bit RSA integer could be factored in less than a week by a quantum computer with less than a million noisy qubits. I make the same assumptions as in 2019: a square grid of qubits with nearest neighbor connections, a uniform gate error rate of $0.1\%$, a surface code cycle time of 1 microsecond, and a control system reaction time of $10$ microseconds. The qubit count reduction comes mainly from using approximate residue arithmetic (Chevignard+Fouque+Schrottenloher 2024), from storing idle logical qubits with yoked surface codes (Gidney+Newman+Brooks+Jones 2023), and from allocating less space to magic state distillation by using magic state cultivation (Gidney+Shutty+Jones 2024). The longer runtime is mainly due to performing more Toffoli gates and using fewer magic state factories compared to Gidney+Eker{\aa} 2019. That said, I reduce the Toffoli count by over 100x compared to Chevignard+Fouque+Schrottenloher 2024.

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representative citing papers

Energy efficiency of quantum computers

quant-ph · 2026-05-14 · unverdicted · novelty 7.0

A new definition of quantum computer energy efficiency is introduced and applied to five major qubit platforms, yielding concrete consumption estimates for current systems and a benchmarking framework for future architectures.

Quantum Circuit Synthesis Using an Exact T Library

quant-ph · 2026-05-14 · unverdicted · novelty 6.0

Exact T-count minimization via precomputed optimal libraries up to 7 variables and Clifford canonicalization yields up to 14.3% T reduction on EPFL benchmarks and 40% on cryptographic modules.

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