Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

arXiv:2105.06062 · Quantum Information Processing

Performance of superconducting quantum computing chips under different architecture designs

Wei Hu, Yang Yang, Weiye Xia, Jiawei Pi, Enyi Huang, Xin-Ding Zhang, Hua Xu

Published Jul 2, 2022• 14 citations
arXivHTMLPDF
DOI
10.1007/s11128-022-03571-0

Related papers

Performance Study of Superconducting Quantum Computing Chips under Different Architecture Design

Wei Hu, Jiawei Pi, Weiye Xia +2 more

Bulletin of the American Physical Society•Mar 17, 2021•0 citations

Towards Efficient Superconducting Quantum Processor Architecture Design

Gushu Li, Yufei Ding, Yuan Xie

More computational resources (i.e., more physical qubits and qubit connections) on a superconducting quantum processor not only improve the performance but also result in more complex chip architecture with lower yield rate. Optimizing both of them simultaneously is a difficult problem due to their intrinsic trade-off. Inspired by the application-specific design principle, this paper proposes an automatic design flow to generate simplified superconducting quantum processor architecture with negligible performance loss for different quantum programs. Our architecture-design-oriented profiling method identifies program components and patterns critical to both the performance and the yield rate. A follow-up hardware design flow decomposes the complicated design procedure into three subroutines, each of which focuses on different hardware components and cooperates with corresponding profiling results and physical constraints. Experimental results show that our design methodology could outperform IBM's general-purpose design schemes with better Pareto-optimal results.,0

International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS)•Mar 9, 2020•49 citations

Towards Efficient Superconducting Quantum Processor Architecture Design

Gushu Li, Yufei Ding, Yuan Xie

Springer eBooks•Aug 13, 2022•3 citations

Quantum Computing with Superconductors I: Architectures

Michael R. Geller, Emily Pritchett, Andrew T. Sornborger +1 more

arXiv:quant-ph/0603224•NATO science series. Series II, Mathematics, physics and chemistry•May 30, 2007•18 citations

Taming Spacetime Overhead and Design Complexity in Distributed Fault-Tolerant Superconducting Quantum Computation

Qinjing Yu, Ke Liu

Scaling fault-tolerant superconducting quantum computers will likely require distributed architectures built from multiple manufacturable quantum processing units. A central question is whether noisy and slow inter-chip operations impose substantial spacetime overhead or orchestration burdens compared with monolithic architectures. To answer this question, we present a hardware-grounded architectural co-design together with a comprehensive resource-estimation protocol for surface-code-based modular processors. The design confines inter-chip latency and noise to module boundaries, preventing slow, noisy links from inducing prohibitive spacetime overhead or becoming a global orchestration bottleneck. The resource-estimation protocol integrates hardware constraints and circuit-level error-correction performance into utility-scale algorithmic cost estimates, enabling a controlled assessment of different architectures. Using RSA-2048 factorization as a demanding benchmark, we estimate resources under experimentally anchored parameters and realistic superconducting hardware constraints. Compared with a large, ideal monolithic baseline, the resulting distributed architecture requires only modest additional resource overhead in both qubit count and execution time. More importantly, the overhead is nearly scale-invariant across a broad module-capacity window, decoupling chip size from global performance. This decoupling turns module capacity from a finely tuned architectural parameter into a flexible engineering degree of freedom, allowing chip sizes to be set by manufacturability and control-packaging constraints rather than architectural fine-tuning. These results establish a viable route to distributed fault-tolerant superconducting quantum computation that scales without prohibitive resource growth or heavy orchestration burden.

quant-pharXiv:2608.23159•Aug 25, 2026•0 citations

Towards Efficient Superconducting Quantum Processor Architecture Design

Gushu Li, Yufei Ding, Yuan Xie

More computational resources (i.e., more physical qubits and qubit connections) on a superconducting quantum processor not only improve the performance but also result in more complex chip architecture with lower yield rate. Optimizing both of them simultaneously is a difficult problem due to their intrinsic trade-off. Inspired by the application-specific design principle, this paper proposes an automatic design flow to generate simplified superconducting quantum processor architecture with negligible performance loss for different quantum programs. Our architecture-design-oriented profiling method identifies program components and patterns critical to both the performance and the yield rate. A follow-up hardware design flow decomposes the complicated design procedure into three subroutines, each of which focuses on different hardware components and cooperates with corresponding profiling results and physical constraints. Experimental results show that our design methodology could outperform IBM's general-purpose design schemes with better Pareto-optimal results.

arXiv:1911.12879•Nov 28, 2019•3 citations
More computational resources (i.e., more physical qubits and qubit connections) on a superconducting quantum processor not only improve the performance but also result in more complex chip architecture with lower yield rate. Optimizing both of them simultaneously is a difficult problem due to their intrinsic trade-off. Inspired by the application-specific design principle, this paper proposes an automatic design flow to generate simplified superconducting quantum processor architecture with negligible performance loss for different quantum programs. Our architecture-design-oriented profiling method identifies program components and patterns critical to both the performance and the yield rate. A follow-up hardware design flow decomposes the complicated design procedure into three subroutines, each of which focuses on different hardware components and cooperates with corresponding profiling results and physical constraints. Experimental results show that our design methodology could outperform IBM's general-purpose design schemes with better Pareto-optimal results.,0
Scaling fault-tolerant superconducting quantum computers will likely require distributed architectures built from multiple manufacturable quantum processing units. A central question is whether noisy and slow inter-chip operations impose substantial spacetime overhead or orchestration burdens compared with monolithic architectures. To answer this question, we present a hardware-grounded architectural co-design together with a comprehensive resource-estimation protocol for surface-code-based modular processors. The design confines inter-chip latency and noise to module boundaries, preventing slow, noisy links from inducing prohibitive spacetime overhead or becoming a global orchestration bottleneck. The resource-estimation protocol integrates hardware constraints and circuit-level error-correction performance into utility-scale algorithmic cost estimates, enabling a controlled assessment of different architectures. Using RSA-2048 factorization as a demanding benchmark, we estimate resources under experimentally anchored parameters and realistic superconducting hardware constraints. Compared with a large, ideal monolithic baseline, the resulting distributed architecture requires only modest additional resource overhead in both qubit count and execution time. More importantly, the overhead is nearly scale-invariant across a broad module-capacity window, decoupling chip size from global performance. This decoupling turns module capacity from a finely tuned architectural parameter into a flexible engineering degree of freedom, allowing chip sizes to be set by manufacturability and control-packaging constraints rather than architectural fine-tuning. These results establish a viable route to distributed fault-tolerant superconducting quantum computation that scales without prohibitive resource growth or heavy orchestration burden.
More computational resources (i.e., more physical qubits and qubit connections) on a superconducting quantum processor not only improve the performance but also result in more complex chip architecture with lower yield rate. Optimizing both of them simultaneously is a difficult problem due to their intrinsic trade-off. Inspired by the application-specific design principle, this paper proposes an automatic design flow to generate simplified superconducting quantum processor architecture with negligible performance loss for different quantum programs. Our architecture-design-oriented profiling method identifies program components and patterns critical to both the performance and the yield rate. A follow-up hardware design flow decomposes the complicated design procedure into three subroutines, each of which focuses on different hardware components and cooperates with corresponding profiling results and physical constraints. Experimental results show that our design methodology could outperform IBM's general-purpose design schemes with better Pareto-optimal results.