一句话：提出 COMPAS，用预共享 Bell 对在分布式 QPU 上实现多方 SWAP 测试与多元迹估计，兼得常数深度与线性 Bell 对消耗。
量子比特数量有限使分布式多 QPU 架构成为扩展量子计算的重要方向，但跨设备执行算法需协同设计电路深度与纠缠开销。本文将多元迹估计识别为适合分布式的关键子程序，并用于 Rényi 熵估计、虚拟冷却与蒸馏等任务。作者提出 COMPAS：利用预共享纠缠 Bell 对，在互连的模块化/分布式 QPU 网络上实现多方 SWAP 测试与多元迹估计。该架构仅引入常数深度开销，Bell 对消耗随电路宽度线性增长，适合近期硬件；不同于只能在电路深度或 GHZ 宽度渐近最优性间取舍的方案，COMPAS 同时实现二者。文中还分析网络层错误并模拟电路级噪声影响。
The limited number of qubits per chip remains a critical bottleneck in quantum computing, motivating the use of distributed architectures that interconnect multiple quantum processing units (QPUs). However, executing quantum algorithms across distributed systems requires careful co-design of algorithmic primitives and hardware architectures to manage circuit depth and entanglement overhead. We identify multivariate trace estimation as a key subroutine that is naturally suited for distribution, and broadly useful in tasks such as estimating Rényi entropies, virtual cooling and distillation, and certain applications of quantum signal processing. In this work, we introduce COMPAS, an architecture that realizes multivariate trace estimation across a multi-party network of interconnected modular and distributed QPUs by leveraging pre-shared entangled Bell pairs as resources. COMPAS adds only a constant depth overhead and consumes Bell pairs at a rate linear in circuit width, making it suitable for near-term hardware. Unlike other schemes, which must choose between asymptotic optimality in circuit depth or GHZ width, COMPAS achieves both at once. Additionally, we analyze network-level errors and simulate the effects of circuit-level noise on the architecture.
DOI 原文 · arXiv · PDF（开放获取） · DBLP
@inproceedings{Goldstein-GelbL26,
title = {COMPAS: A Distributed Multi-Party SWAP Test for Parallel Quantum Algorithms},
author = {Brayden Goldstein-Gelb and Kun Liu and John M. Martyn and Hengyun (Harry) Zhou and Yongshan Ding and Yuan Liu},
booktitle = {ASPLOS},
year = {2026},
doi = {10.1145/3779212.3790143}
}