CUDA-Q Logical: Retargetable Compilation for Fault-Tolerant Quantum Computing

Quantum Physics arXiv:2609.13388 (quant-ph) [Submitted on 11 Sep 2026] Title:CUDA-Q Logical: Retargetable Compilation for Fault-Tolerant Quantum Computing Authors:Alexander McCaskey, Justin Lietz, Adam Holmes, Kohei Nakaji, Vadym Kliuchnikov, Yifan Hong, Amalee Wilson, Andres Paz, Bettina Heim, Bruno Schmitt, Krysta M. Svore View a PDF of the paper titled CUDA-Q Logical: Retargetable Compilation for Fault-Tolerant Quantum Computing, by Alexander McCaskey and 10 other authors View PDF HTML (experimental) Abstract:Realizing fault-tolerant quantum computing requires mapping logical programs to heterogeneous quantum error correction (QEC) codes and diverse fault-tolerant execution models, scheduling physical resources, and coupling to real-time classical control and feedback. Specialized tools exist for each step but rely on manual composition and translation that discard assumptions and provenance, separating resource estimates from the compiler artifacts they describe, and making it difficult to validate correctness, compare architectures, or attribute costs to specific design choices. We present CUDA-Q Logical, an extensible compiler infrastructure for retargetable fault-tolerant compilation, analysis, and execution. Interoperable with CUDA-Q and other mainstream front-ends, CUDA-Q Logical progressively lowers target-independent logical programs through a constrained logical virtual machine, QEC microcode, physical gate schedules, and real-time control plans, with each layer preserving semantics and provenance, while verifying composition and resource constraints. By deriving every resource estimate directly from compiler artifacts, the framework unifies compilation and resource analysis, enabling successively refined estimates and principled cross-architecture comparison while permitting QEC codes, execution models, decoders, and hardware architectures to be introduced as modular extensions. Across workloads ranging from application-architecture studies to qLDPC surgery and detector-error-model composition, we show that schedule-derived estimates reconcile with established independent models. Crucially, this compiler-visible structure exposes cost drivers hidden by aggregate analytical formulas, carries QEC artifacts intact into simulation, and demonstrates a complete compilation pipeline for fault-tolerant quantum computing. Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2609.13388 [quant-ph] (or arXiv:2609.13388v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2609.13388 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Alexander McCaskey [view email] [v1] Fri, 11 Sep 2026 18:00:16 UTC (1,510 KB) Full-text links: Access Paper: View a PDF of the paper titled CUDA-Q Logical: Retargetable Compilation for Fault-Tolerant Quantum Computing, by Alexander McCaskey and 10 other authorsView PDFHTML (experimental)TeX Source view license Current browse context: quant-ph new | recent | 2026-09 References & Citations INSPIRE HEP NASA ADSGoogle Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv (What is alphaXiv?) Links to Code Toggle CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub Toggle DagsHub (What is DagsHub?) GotitPub Toggle Gotit.pub (What is GotitPub?) Huggingface Toggle Hugging Face (What is Huggingface?) ScienceCast Toggle ScienceCast (What is ScienceCast?) Demos Demos Replicate Toggle Replicate (What is Replicate?) Spaces Toggle Hugging Face Spaces (What is Spaces?) Spaces Toggle TXYZ.AI (What is TXYZ.AI?) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower (What are Influence Flowers?) Core recommender toggle CORE Recommender (What is CORE?) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)