Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC)

Distributed Scheduling for Modular Quantum Computing in Cloud

Vinooth Rao Kulkarni, Vipin Chaudhary

Published Jul 11, 2026• 0 citations
Publisher
DOI
10.1145/3806645.3820071

Related papers

Deadline-Aware Scheduling of Distributed Quantum Circuits in Near-Term Quantum Cloud

Nour Dehaini, Christia Chahoud, Mahdi M. Chehimi

International Conference on Quantum Communications, Networking, and Computing (QCNC)•Apr 6, 2026•0 citations

QuCloudSim: A Customizable Discrete Event Simulator for Quantum Cloud Computing Enviroment

Ruilin Zhou, Yuhang Gan, Lucinda Shen +3 more

Current quantum computing service providers operate in a cloud-based model, hosting expensive quantum computers in data centers for remote access. However, in the Noisy Intermediate-Scale Quantum (NISQ) era, quantum hardware is limited in terms of qubit count and connectivity. To address scalability challenges, future quantum cloud infrastructures will likely adopt a modular architecture where Quantum Processing Units (QPUs) are interconnected via quantum networks using various hardware technologies. In such systems, challenges like resource management, scheduling, and placement become critical, yet there is currently a gap in simulation tools capable of modeling quantum computers connected via quantum networks. To address this, we propose QuCloudSim, a quantum cloud simulator that adopts a modular design to model various hardware components within a quantum cloud environment. It employs discrete event simulation to replicate real-world scenarios with concurrent user requests, and our evaluation of different scheduling and placement methods demonstrates that QuCloudSim effectively models modular quantum cloud systems while providing valuable insights for developing scalable quantum cloud infrastructures.

International Conference on Quantum Communications, Networking, and Computing (QCNC)•Mar 31, 2025•0 citations

InterQ: Communication-Aware Scheduling Across Modular QPUs with Classical and Quantum Links

Vinooth Kulkarni, Jaehyun Lee, Lauren Li +5 more

As quantum computing scales toward practical workloads, future systems are expected to move beyond single monolithic processors toward modular architectures that connect multiple QPUs. Different platforms realize this modularity through different communication models: superconducting systems rely on real-time classical links and dynamic-circuit coordination, trapped-ion systems use photonic interconnects for remote entanglement, and neutral-atom systems provide strong intra-core connectivity with proposed optical links for inter-core communication. This heterogeneity makes communication-aware scheduling essential for shared modular quantum cloud environments. We present InterQ, a communication-aware scheduler for modular QPU architectures with heterogeneous communication models. InterQ jointly considers qubit capacity, placement, parallel execution, and communication-driven dependencies across distributed subcircuits, while enabling adaptive circuit cutting to reduce makespan while balancing fidelity and communication overhead. The framework distinguishes classical-link execution, where measurement and feedforward impose synchronization constraints, from quantum-link execution, where entanglement distribution and state transfer determine coordination cost. Using a unified simulation framework to compare superconducting, trapped-ion, and neutral-atom modular systems, InterQ shows how communication models and scheduler-driven cutting decisions affect throughput, latency, and fidelity. Across evaluated workloads, InterQ exposes an architecture-dependent tradeoff: neutral-atom modular QPUs achieve the highest fidelity, superconducting systems minimize runtime, and trapped-ion systems provide a balanced intermediate profile across fidelity and makespan.

quant-pharXiv:2605.17769•May 19, 2026•0 citations

Distributed Quantum Computing for Scalable Systems

Daniel Casado-Faulí, Parfait Atchade-Adelomou, David Pérez de Lara +1 more

Lecture notes in networks and systems•Jan 1, 2026•0 citations

Application of Quantum Computing Gates for Enhanced Task Scheduling in Cloud Environments

Prathamesh Vijay Lahande, Shree Nigade, Tejas Mandhare

Cloud task scheduling is a complex optimization problem that has a decisive influence on the use of resources, execution latency, and scalability of distributed infrastructures. In the modern cloud computing environments, most cloud applications utilize classical computing gates for all computations. However, with the progress of Quantum Computing (QC) in the domain of task scheduling, it is important to apply and compare the performance of QC gates to ensure ideal QC-circuits are designed to enhance the scheduling of tasks. This paper investigates implementing C-NOT, Hadamard (H), and Phase-T gates of QC as part of a quantum-optimization platform for enhancing the task scheduling in the cloud. This includes analyzing their functional role in a real-time experimental setup using Virtual Machine (VM) configurations ranging from six to sixty across ten scenarios. Real-time tasks were scheduled using these QC-gates, their performance was recorded and compared using the time performance parameter. The experimental results show that the scheduling performed using the C-NOT QC-gate achieved the computational latency of 26.40ms, the least among the other considered QC-gates. On the other hand, the Hadamard and Phase-T QC-gates recorded 27.78ms and 29.25ms of latency, respectively. This conveyed that the C-NOT QC-gate demonstrated an enhanced task scheduling with an improvement of 4.97% and 9.74% compared to the Hadamard and Phase-T gate. This research supports utilizing entanglement-based scheduling achieved using the C-NOT gate for improved and optimized latency, thus making it the most effective gate set up to schedule cloud tasks.

International Conference on Trends in Electronics and Informatics (ICOEI)•Apr 21, 2026•0 citations

Distributed Quantum Computing

Harry Buhrman, Hein Röhrig

Lecture notes in computer science•Jan 1, 2003•95 citations
Current quantum computing service providers operate in a cloud-based model, hosting expensive quantum computers in data centers for remote access. However, in the Noisy Intermediate-Scale Quantum (NISQ) era, quantum hardware is limited in terms of qubit count and connectivity. To address scalability challenges, future quantum cloud infrastructures will likely adopt a modular architecture where Quantum Processing Units (QPUs) are interconnected via quantum networks using various hardware technologies. In such systems, challenges like resource management, scheduling, and placement become critical, yet there is currently a gap in simulation tools capable of modeling quantum computers connected via quantum networks. To address this, we propose QuCloudSim, a quantum cloud simulator that adopts a modular design to model various hardware components within a quantum cloud environment. It employs discrete event simulation to replicate real-world scenarios with concurrent user requests, and our evaluation of different scheduling and placement methods demonstrates that QuCloudSim effectively models modular quantum cloud systems while providing valuable insights for developing scalable quantum cloud infrastructures.
As quantum computing scales toward practical workloads, future systems are expected to move beyond single monolithic processors toward modular architectures that connect multiple QPUs. Different platforms realize this modularity through different communication models: superconducting systems rely on real-time classical links and dynamic-circuit coordination, trapped-ion systems use photonic interconnects for remote entanglement, and neutral-atom systems provide strong intra-core connectivity with proposed optical links for inter-core communication. This heterogeneity makes communication-aware scheduling essential for shared modular quantum cloud environments. We present InterQ, a communication-aware scheduler for modular QPU architectures with heterogeneous communication models. InterQ jointly considers qubit capacity, placement, parallel execution, and communication-driven dependencies across distributed subcircuits, while enabling adaptive circuit cutting to reduce makespan while balancing fidelity and communication overhead. The framework distinguishes classical-link execution, where measurement and feedforward impose synchronization constraints, from quantum-link execution, where entanglement distribution and state transfer determine coordination cost. Using a unified simulation framework to compare superconducting, trapped-ion, and neutral-atom modular systems, InterQ shows how communication models and scheduler-driven cutting decisions affect throughput, latency, and fidelity. Across evaluated workloads, InterQ exposes an architecture-dependent tradeoff: neutral-atom modular QPUs achieve the highest fidelity, superconducting systems minimize runtime, and trapped-ion systems provide a balanced intermediate profile across fidelity and makespan.
Cloud task scheduling is a complex optimization problem that has a decisive influence on the use of resources, execution latency, and scalability of distributed infrastructures. In the modern cloud computing environments, most cloud applications utilize classical computing gates for all computations. However, with the progress of Quantum Computing (QC) in the domain of task scheduling, it is important to apply and compare the performance of QC gates to ensure ideal QC-circuits are designed to enhance the scheduling of tasks. This paper investigates implementing C-NOT, Hadamard (H), and Phase-T gates of QC as part of a quantum-optimization platform for enhancing the task scheduling in the cloud. This includes analyzing their functional role in a real-time experimental setup using Virtual Machine (VM) configurations ranging from six to sixty across ten scenarios. Real-time tasks were scheduled using these QC-gates, their performance was recorded and compared using the time performance parameter. The experimental results show that the scheduling performed using the C-NOT QC-gate achieved the computational latency of 26.40ms, the least among the other considered QC-gates. On the other hand, the Hadamard and Phase-T QC-gates recorded 27.78ms and 29.25ms of latency, respectively. This conveyed that the C-NOT QC-gate demonstrated an enhanced task scheduling with an improvement of 4.97% and 9.74% compared to the Hadamard and Phase-T gate. This research supports utilizing entanglement-based scheduling achieved using the C-NOT gate for improved and optimized latency, thus making it the most effective gate set up to schedule cloud tasks.