Circuit Folding: Scalable and Graph-Based Circuit Cutting via Modular Structure Exploitation

[2412.18705] Circuit Folding: Scalable and Graph-Based Circuit Cutting via Modular Structure Exploitation Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Quantum Physics arXiv:2412.18705 (quant-ph) [Submitted on 24 Dec 2024 ( v1 ), last revised 13 Apr 2026 (this version, v3)] Title: Circuit Folding: Scalable and Graph-Based Circuit Cutting via Modular Structure Exploitation Authors: Shuwen Kan , Yanni Li , Hao Wang , Sara Mouradian , Ying Mao View a PDF of the paper titled Circuit Folding: Scalable and Graph-Based Circuit Cutting via Modular Structure Exploitation, by Shuwen Kan and 4 other authors View PDF HTML (experimental) Abstract: Circuit cutting is a promising technique that leverages both quantum and classical computational resources, enabling the practical execution of large quantum circuits on noisy intermediate-scale quantum (NISQ) hardware. Recent approaches typically focus exclusively on either gate cuts or wire cuts, modeling quantum circuits as graphs. However, identifying optimal cutting locations using this representation often results in prohibitively high computational complexity, especially under realistic hardware constraints. In this paper, we introduce CIFOLD, a novel graph-based framework that exploits repetitive modular structures inherent in quantum algorithms, significantly enhancing the scalability and efficiency of circuit cutting. Our approach systematically folds quantum circuits into compact meta-graphs by identifying and merging common gate sequences across entangled qubits, dramatically simplifying subsequent partitioning tasks. We define folding factor and variance to quantify circuit compression and ensure balanced folding. Using these condensed representations, CIFOLD precisely identifies cut locations without exhaustive global graph searches. We perform extensive experiments, comparing CIFOLD with state-of-the-art circuit-cutting techniques. Results demonstrate that CIFOLD achieves superior partition quality and computational efficiency, reducing the number of required cuts by an average of 31.6% and lowering the sampling overhead substantially by 3.55*10^9. Our findings illustrate that CIFOLD represents a significant advancement toward scalable quantum circuit cutting. Subjects: Quantum Physics (quant-ph) ; Distributed, Parallel, and Cluster Computing (cs.DC) Cite as: arXiv:2412.18705 [quant-ph] (or arXiv:2412.18705v3 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2412.18705 Focus to learn more arXiv-issued DOI via DataCite Journal reference: ICCAD 2025 Related DOI : https://doi.org/10.1109/ICCAD66269.2025.11240933 Focus to learn more DOI(s) linking to related resources Submission history From: Ying Mao [ view email ] [v1] Tue, 24 Dec 2024 23:34:17 UTC (2,105 KB) [v2] Tue, 7 Apr 2026 14:22:48 UTC (1,905 KB) [v3] Mon, 13 Apr 2026 20:18:57 UTC (1,905 KB) Full-text links: Access Paper: View a PDF of the paper titled Circuit Folding: Scalable and Graph-Based Circuit Cutting via Modular Structure Exploitation, by Shuwen Kan and 4 other authors View PDF HTML (experimental) TeX Source view license Current browse context: quant-ph < prev | next > new | recent | 2024-12 Change to browse by: cs cs.DC References & Citations INSPIRE HEP NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... 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