QuMod: Parallel Quantum Job Scheduling on Modular QPUs using Circuit Cutting

2026-04-13

AI Summary

This work addresses the scheduling challenges of multi-user parallel workloads in modular quantum processing unit (QPU) architectures, where efficient resource allocation, cross-module execution, and measurement synchronization are critical. The paper presents the first multitasking scheduler that integrates quantum circuit cutting, dynamic circuit control, and quantum task scheduling into a unified framework. This approach jointly optimizes qubit mapping, parallel subcircuit execution, Bell pair generation, quantum teleportation, and cross-QPU measurement synchronization. By enabling large-scale quantum circuits to execute efficiently across classically interconnected modular QPUs, the proposed method significantly enhances system throughput and resource-sharing efficiency while maintaining fairness among concurrent users.

Technology Category

• Machine Learning: Quantum Machine Learning
• Planning, Routing, and Scheduling: Scheduling
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Economics, Online Markets and Human Computation: LLM based quality controls for crowd work
• Security and Privacy: Large-scale security measurements
• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking

Abstract

The quantum computing community is increasingly positioning quantum processors as accelerators within classical HPC workflows, analogous to GPUs and TPUs. However, many real-world applications require scaling to hundreds or thousands of physical qubits to realize logical qubits via error correction. To reach these scales, hardware vendors employing diverse technologies -- such as trapped ions, photonics, neutral atoms, and superconducting circuits -- are moving beyond single, monolithic QPUs toward modular architectures connected via interconnects. For example, IonQ has proposed photonic links for scaling, while IBM has demonstrated a modular QPU architecture by classically linking two 127-qubit devices. Using dynamic circuits, Bell-pair-based teleportation, and circuit cutting, they have shown how to execute a large quantum circuit that cannot fit on a single QPU. As interest in quantum computing grows, cloud providers must ensure fair and efficient resource allocation for multiple users sharing such modular systems. Classical interconnection of QPUs introduces new scheduling challenges, particularly when multiple jobs execute in parallel. In this work, we develop a multi-programmable scheduler for modular quantum systems that jointly considers qubit mapping, parallel circuit execution, measurement synchronization across subcircuits, and teleportation operations between QPUs using dynamic circuits.

Problem

• quantum scheduling
• modular QPUs
• circuit cutting
• resource allocation
• parallel quantum jobs

Innovation

• quantum job scheduling
• modular QPUs
• circuit cutting
• dynamic circuits
• quantum teleportation