Efficient Time-Aware Partitioning of Quantum Circuits for Distributed Quantum Computing

2026-03-04

AI Summary

This work addresses the high communication overhead in distributed quantum computing arising from inter-node operations such as teleportation of quantum states and gates. To mitigate this, the authors propose a time-aware beam search heuristic that incrementally constructs low-communication qubit allocation sequences across discrete time steps, enabling efficient circuit partitioning. By integrating dynamic timing information with network topology, the method overcomes the limitations of conventional static graph partitioning and computationally expensive metaheuristic approaches. Experimental results demonstrate that the proposed algorithm consistently achieves substantial reductions in communication cost across diverse circuit sizes, depths, and network topologies, while maintaining time and space complexities of only quadratic in the number of qubits and linear in circuit depth, respectively.

Technology Category

• Search and Optimization: Distributed Search
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Machine Learning: Quantum Machine Learning

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

To overcome the physical limitations of scaling monolithic quantum computers, distributed quantum computing (DQC) interconnects multiple smaller-scale quantum processing units (QPUs) to form a quantum network. However, this approach introduces a critical challenge, namely the high cost of quantum communication between remote QPUs incurred by quantum state teleportation and quantum gate teleportation. To minimize this communication overhead, DQC compilers must strategically partition quantum circuits by mapping logical qubits to distributed physical QPUs. Static graph partitioning methods are fundamentally ill-equipped for this task as they ignore execution dynamics and underlying network topology, while metaheuristics require substantial computational runtime. In this work, we propose a heuristic based on beam search to solve the circuit partitioning problem. Our time-aware algorithm incrementally constructs a low-cost sequence of qubit assignments across successive time steps to minimize overall communication overhead. The time and space complexities of the proposed algorithm scale quadratically with the number of qubits and linearly with circuit depth, offering a significant computational speedup over common metaheuristics. We demonstrate that our proposed algorithm consistently achieves significantly lower communication costs than static baselines across varying circuit sizes, depths, and network topologies, providing an efficient compilation tool for near-term distributed quantum hardware.

Problem

• distributed quantum computing
• quantum circuit partitioning
• quantum communication overhead
• qubit assignment
• time-aware partitioning

Innovation

• beam search
• time-aware partitioning
• distributed quantum computing
• quantum circuit compilation
• communication overhead minimization