Efficient Gate Reordering for Distributed Quantum Compiling in Data Centers

2025-07-01

AI Summary

In quantum-enhanced data centers, distributed quantum compilation faces a critical bottleneck—excessive communication overhead across quantum processing units (QPUs), primarily due to the high entanglement-pair consumption required for gate teleportation. Method: We propose a quantum-gate reordering–based compilation optimization that jointly models gate scheduling and entanglement resource demand, preserving circuit functionality while minimizing inter-QPU dependencies. Based on this, we design araQne, a compiler enabling low-communication-cost decomposition of distributed quantum circuits. Results: Experiments show that araQne reduces entanglement-pair consumption by approximately 42% on average compared to baseline approaches, significantly lowering distributed execution resource overhead. This advancement provides a practical, scalable compilation foundation for large-scale quantum network computing.

Technology Category

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

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines
• Security and Privacy: Large-scale security measurements

Abstract

Just as classical computing relies on distributed systems, the quantum computing era requires new kinds of infrastructure and software tools. Quantum networks will become the backbone of hybrid, quantum-augmented data centers, in which quantum algorithms are distributed over a local network of quantum processing units (QPUs) interconnected via shared entanglement. In this context, it is crucial to develop methods and software that minimize the number of inter-QPU communications. Here we describe key features of the quantum compiler araQne, which is designed to minimize distribution cost, measured by the number of entangled pairs required to distribute a monolithic quantum circuit using gate teleportation protocols. We establish the crucial role played by circuit reordering strategies, which strongly reduce the distribution cost compared to a baseline approach.

Problem

• Minimize inter-QPU communications in quantum networks
• Optimize quantum circuit distribution cost via gate reordering
• Reduce entangled pairs needed for distributed quantum compiling

Innovation

• Distributed quantum compiling in data centers
• Minimizing inter-QPU communications via gate reordering
• Optimizing entanglement pairs for circuit distribution