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C-Phase-Aware Compilation for Efficient Fault-Tolerant Quantum Execution

arXiv Quantum Physics
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Researchers introduced a microarchitecture-aware quantum compilation method that reduces fault-tolerant execution overhead by leveraging C-Phase gate commutativity, achieving up to 59.7× faster runtime than conventional approaches. The technique transforms sequential gate operations into parallel multi-target interactions, eliminating artificial dependencies and exposing instruction-level parallelism in lattice surgery-based quantum computers. A dynamic, event-driven scheduler models spatial layout and routing constraints in real time, enabling overlapping operations while minimizing resource contention and idle periods. Unlike coarse-grained slice-based compilers, this approach directly integrates algorithmic structure with hardware execution, improving alignment between quantum algorithms and physical qubit layouts. The work addresses a critical bottleneck in fault-tolerant quantum computing by optimizing both temporal and spatial resource utilization, potentially accelerating practical quantum advantage.
C-Phase-Aware Compilation for Efficient Fault-Tolerant Quantum Execution

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Quantum Physics arXiv:2605.14042 (quant-ph) [Submitted on 13 May 2026] Title:C-Phase-Aware Compilation for Efficient Fault-Tolerant Quantum Execution Authors:Dhanvi Bharadwaj, Siddharth Dangwal, Yuewen Hou, Gokul Subramanian Ravi View a PDF of the paper titled C-Phase-Aware Compilation for Efficient Fault-Tolerant Quantum Execution, by Dhanvi Bharadwaj and 3 other authors View PDF HTML (experimental) Abstract:Achieving practical quantum advantage on fault-tolerant quantum computers (FTQC) is fundamentally constrained by the substantial spatial and temporal overheads required to map logical operations onto physical hardware. Existing compilation approaches typically adopt coarse-grained, slice-based abstractions that overlook fine-grained microarchitectural effects, such as routing contention, leading to inefficient resource utilization and limited alignment between algorithm structure and hardware capabilities. This work presents a microarchitecture-aware compilation approach that integrates algorithmic structure directly with lattice surgery (LS) execution. By leveraging the commutativity of C-Phase operations, the method transforms inherently sequential gate sequences into concurrent multi-target interactions, effectively removing artificial dependencies and exposing significant instruction-level parallelism. To enable this, we design a dynamic, event-driven scheduling strategy that accurately models spatial layout and routing constraints, allowing operations to overlap in time while minimizing contention. Through improved coordination of computation and communication, this approach substantially reduces idle resources and achieves up to a 59.7$\times$ reduction in execution time compared to standard baselines. Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2605.14042 [quant-ph] (or arXiv:2605.14042v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2605.14042 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Dhanvi Bharadwaj [view email] [v1] Wed, 13 May 2026 19:03:18 UTC (2,124 KB) Full-text links: Access Paper: View a PDF of the paper titled C-Phase-Aware Compilation for Efficient Fault-Tolerant Quantum Execution, by Dhanvi Bharadwaj and 3 other authorsView PDFHTML (experimental)TeX Source view license Current browse context: quant-ph new | recent | 2026-05 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?)

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quantum-optimization
government-funding
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Source: arXiv Quantum Physics