Low-cost algorithm-to-execution framework for surface-code quantum computing
Abstract
Fault-tolerant quantum computing is progressing from demonstrations of individual logical components toward the execution of useful quantum algorithms on large-scale error-corrected processors. Realizing this transition requires co-design across algorithms, fault-tolerant implementations, and hardware resources. Here we develop an algorithm-to-execution framework for low-cost surface-code quantum computing that carries the structure of a computation from hierarchical logical descriptions to circuit-specific spatial organization, non-Clifford resource planning, and physical resource evaluation. We apply the framework to twenty benchmark circuits spanning seven algorithm families and to a hierarchically reconstructed application-scale elliptic-curve discrete-logarithm workload. Under the stated error and resource-supply models, combining circuit-specific layouts with hybrid non-Clifford implementation reduces space--time volume by up to 12.70x relative to an all-synthesis Litinski fast-block baseline. Circuit-specific layouts reduce both modeled runtime and space--time volume in eighteen benchmarks, while the remaining two retain the fast layout. These results show that the physical cost of fault-tolerant computation emerges from the interaction between algorithm structure, error-corrected implementation, and hardware organization rather than from aggregate logical resource counts alone.
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BibTeX
@misc{tang2026lowcost,
title = {{Low-cost algorithm-to-execution framework for surface-code quantum computing}},
author = {Yunxin Tang and Zixuan Huo and Junxiang Huang and Zhou You and Zhirao Wang and Zhenai Ding and Yumeng Zeng and Yangyu Lu and Yiming Huang and Zongkang Zhang and Haipeng Xie and Ruipeng Xing and Qiming Ding and Ying Li and Jinzhao Sun and Xiao Yuan and Yuan Yao},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2609.10965},
eprint = {2609.10965},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.10965},
}
RIS
TY - UNPB
TI - Low-cost algorithm-to-execution framework for surface-code quantum computing
AU - Yunxin Tang
AU - Zixuan Huo
AU - Junxiang Huang
AU - Zhou You
AU - Zhirao Wang
AU - Zhenai Ding
AU - Yumeng Zeng
AU - Yangyu Lu
AU - Yiming Huang
AU - Zongkang Zhang
AU - Haipeng Xie
AU - Ruipeng Xing
AU - Qiming Ding
AU - Ying Li
AU - Jinzhao Sun
AU - Xiao Yuan
AU - Yuan Yao
PY - 2026
DA - 2026/10/13
PB - arXiv
DO - 10.48550/arxiv.2609.10965
UR - https://arxiv.org/abs/2609.10965
AB - Fault-tolerant quantum computing is progressing from demonstrations of individual logical components toward the execution of useful quantum algorithms on large-scale error-corrected processors. Realizing this transition requires co-design across algorithms, fault-tolerant implementations, and hardware resources. Here we develop an algorithm-to-execution framework for low-cost surface-code quantum computing that carries the structure of a computation from hierarchical logical descriptions to circuit-specific spatial organization, non-Clifford resource planning, and physical resource evaluation. We apply the framework to twenty benchmark circuits spanning seven algorithm families and to a hierarchically reconstructed application-scale elliptic-curve discrete-logarithm workload. Under the stated error and resource-supply models, combining circuit-specific layouts with hybrid non-Clifford implementation reduces space--time volume by up to 12.70x relative to an all-synthesis Litinski fast-block baseline. Circuit-specific layouts reduce both modeled runtime and space--time volume in eighteen benchmarks, while the remaining two retain the fast layout. These results show that the physical cost of fault-tolerant computation emerges from the interaction between algorithm structure, error-corrected implementation, and hardware organization rather than from aggregate logical resource counts alone.
ER -