Hybrid Quantum and Classical Workload Management with Graph-based Scheduling

Quantum Physics arXiv:2607.09151 (quant-ph) [Submitted on 10 Jul 2026] Title:Hybrid Quantum and Classical Workload Management with Graph-based Scheduling Authors:Vanessa Sochat, Daniel Milroy View a PDF of the paper titled Hybrid Quantum and Classical Workload Management with Graph-based Scheduling, by Vanessa Sochat and Daniel Milroy View PDF HTML (experimental) Abstract:High Performance Computing (HPC) centers are expanding to encompass resources that extend beyond traditional computing. By extending resources to quantum computing, hybrid quantum-classical workflows tackle complex optimization problems that have never before been possible. However, integrating quantum processing units (QPUs) into cloud-native and scientific workload managers presents a unique orchestration challenge: remote quantum devices introduce a second, external queue -- a two-queue problem -- alongside the queue owned by the traditional scheduler. In this work we present Fluence, a Kubernetes scheduler plugin backed by the Fluxion graph-based scheduler, that enables informed, gang-scheduled placement for quantum-classical workloads and custom resources. We evaluate Fluence across three scenarios using AWS Braket simulators and real QPUs. First, under node contention, Fluence's atomic gang placement all but eliminates the wasted node-time that a default scheduler accrues by partially placing gangs. Second, we introduce a synchronization primitive for the two-queue problem in which a single producer submits a shared quantum task while consumers remain scheduling-gated, reducing worker idle time by roughly 5x under short device queues and by orders of magnitude when a real device queue stretched to hours. Third, cost- and queue-aware backend selection pins the cheapest or shortest-queue device satisfying a workload, cutting mean per-run cost by roughly 70x and time-to-result from hours to under a minute. Together, these results show that quantum-awareness can be added to a cloud-native scheduler without modifying user containers. Comments: Subjects: Quantum Physics (quant-ph); Distributed, Parallel, and Cluster Computing (cs.DC) Cite as: arXiv:2607.09151 [quant-ph] (or arXiv:2607.09151v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2607.09151 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Vanessa Sochat [view email] [v1] Fri, 10 Jul 2026 07:09:32 UTC (1,069 KB) Full-text links: Access Paper: View a PDF of the paper titled Hybrid Quantum and Classical Workload Management with Graph-based Scheduling, by Vanessa Sochat and Daniel MilroyView PDFHTML (experimental)TeX Source view license Current browse context: quant-ph new | recent | 2026-07 Change to browse by: cs cs.DC 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?)