Error-structure-tailored early fault-tolerant quantum computing
Abstract
Fault tolerance is widely regarded as indispensable for achieving scalable and reliable quantum computing. However, the spacetime overhead required for fault-tolerant quantum computating remains prohibitively large. A critical challenge arises in many quantum algorithms with Clifford + compiling, where logical rotation gates serve as essential components. The Eastin-Knill theorem prevents their transversal implementation in quantum error correction codes and necessitating resource-intensive workarounds through T-gate compilation combined with magic state distillation and injection. In this work, we consider error-structure-tailored fault tolerance, where fault-tolerance conditions are analyzed by combining perturbative analysis of realistic dissipative noise processes with the structural properties of stabilizer codes. Based on this framework, we design 1-fault-tolerant continuous-angle rotation gates in stabilizer codes, implemented via dispersive-coupling Hamiltonians. Our approach could circumvent the need for T-gate compilation and distillation, offering a hardware-efficient solution that maintains simplicity, minimizes physical footprint, and requires only nearest-neighbor interactions. Integrating with recent small-angle-state preparation techniques, we can suppress the gate error to for small rotation angle (where p denotes the physical error rate). For current achievable hardware parameters (), this enables reliable execution of over small-angle rotations when , meeting the requirements of many near-term quantum applications. Compared to the 15-to-1 magic state distillation and magic state cultivation approaches, our method reduces spacetime resource costs by factors of 1337.5 and 43.6, respectively, for a Heisenberg Hamiltonian simulation task under realistic hardware assumptions.
Cite
@article{arxiv.2511.19983,
title = {Error-structure-tailored early fault-tolerant quantum computing},
author = {Pei Zeng and Guo Zheng and Qian Xu and Liang Jiang},
journal= {arXiv preprint arXiv:2511.19983},
year = {2025}
}
Comments
35 pages, 22 figures. Comments are welcome