analiza aiqbench
This paper treats distributed quantum computing as a streaming scheduling problem: jobs arrive over time, and the scheduler must allocate qubits and launch circuits without knowing future arrivals, under memory limits, probabilistic entanglement, and decoherence. For readers, the useful point is that it reframes cloud-style quantum workloads as an online resource-allocation problem rather than a static batch one, with latency and throughput as explicit trade-offs. Whether its proposed policies hold up on real hardware will depend on the evaluation details, which the abstract alone does not show.
Online Scheduling and Distribution of Quantum Circuits over Quantum Networks
arXiv:2610.25875v1 Announce Type: cross Abstract: Emerging quantum networks enable distributed quantum computing (DQC) by interconnecting modest, noisy quantum processors. However, practical deployments face tight memory budgets, probabilistic entanglement generation, and decoherence, all while serving multiple users. In realistic settings -- cloud execution, iterative/interactive workloads and concurrent jobs -- circuits do not arrive in a single batch but as a stream. This creates a fundamentally online problem: the system must react to stochastic arrivals, balance latency and throughput, and remain stable under varying loads without foresight of future jobs. We study Online Scheduling and Distribution of Quantum Circuits (OS-DQC) and formalize the online scheduling problem for quantum networks: circuits arrive over time and must be executed without knowledge of future arrivals. At each event time (arrival or completion), the system decides which waiting circuits to launch and how to place their qubits, while accounting for congestion from in-flight circuits and constraints due to finite memories and decoherence. The objective is to minimize the mean completion time and makespan under these physical and resource constraints.
Abstract:Emerging quantum networks enable distributed quantum computing (DQC) by interconnecting modest, noisy quantum processors. However, practical deployments face tight memory budgets, probabilistic entanglement generation, and decoherence, all while serving multiple users. In realistic settings -- cloud execution, iterative/interactive workloads and concurrent jobs -- circuits do not arrive in a single batch but as a stream. This creates a fundamentally online problem: the system must react to stochastic arrivals, balance latency and throughput, and remain stable under varying loads without foresight of future jobs. We study Online Scheduling and Distribution of Quantum Circuits (OS-DQC) and formalize the online scheduling problem for quantum networks: circuits arrive over time and must be executed without knowledge of future arrivals. At each event time (arrival or completion), the system decides which waiting circuits to launch and how to place their qubits, while accounting for congestion from in-flight circuits and constraints due to finite memories and decoherence. The objective is to minimize the mean completion time and makespan under these physical and resource constraints.
8 pages, 5 figures. Full author version revised after acceptance; the QCNC 2026 version was shortened to meet the conference page limit
Emerging Technologies (cs.ET); Quantum Physics (quant-ph)
arXiv:2610.25875 [cs.ET]
(or arXiv:2610.25875v1 [cs.ET] for this version)
https://doi.org/10.48550/arXiv.2610.25875 Focus to learn more arXiv-issued DOI via DataCite
Proceedings - 2026 International Conference on Quantum Communications, Networking, and Computing (QCNC), pp. 264-270 (2026)
https://doi.org/10.1109/QCNC69040.2026.00045 Focus to learn more DOI(s) linking to related resources
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.
Text integral sub licența deschisă a publicației · 310 cuvinte
Subiecte conexe

Researchers Cut Quantum Computing Costs with New Scheduler
Quantum Zeitgeist · 25 oct. 2026

memQ Releases memQ DQC: An Open-Source Framework for Distributed Quantum Computing
Quantum Computing Report · 25 sept. 2026
Factorized Scheduling Principle: Learning Interpretable and Transferable Policies via Structured Additive Functions
arXiv · 30 sept. 2026

MilleMiglia: A realistic instance generator for middle-mile logistics
Google Research · 18 sept. 2026