发表机构
Frontier Science Center for Quantum Information, Department of Physics, Tsinghua University; Department of Astronomy, Tsinghua University（清华大学量子信息前沿科学中心物理系; 清华大学天文系）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究针对多台站干涉仪成像的阵列级不相容问题，提出存储器辅助干涉架构，通过集体测量实现O(√N)级信噪比提升，可改进图像重建与分辨能力，为量子辅助恒星成像阵列提供新方案。
AI 中文摘要
利用多台站干涉仪对天体物理源进行成像本质上是一个多参数量子估计问题。我们借助多参数量子度量学工具表明，在N台站阵列中，时间分辨的重复或自适应测量会在可见度估计器之间产生基础的阵列级不相容性。集体测量通过在单次联合读出中相干处理多个时间区间内接收到的星光，可消除阵列大小带来的惩罚（误差因子为量级1），使可见度测量的方向平均信噪比获得渐近O(√N)的提升。我们随后提出一种基于存储器的干涉测量架构，旨在通过相干存储和联合量子处理实现集体读出。成像模拟与费舍尔信息分析表明，集体测量可改进近期阵列的图像重建效果，并提升未来长基线架构的分辨能力，对NGC~4151和3C~273等代表性活动星系核（AGN）目标具有显著益处。这些结果凸显集体测量是未来用于恒星成像的量子辅助干涉阵列的有潜力的构建模块。
英文摘要
Imaging astrophysical sources with a multi-station interferometer is intrinsically a multiparameter quantum-estimation problem. {Using tools from multiparameter quantum metrology,} we show that time-resolved repetitive or adaptive measurements in an \(N\)-station array suffer a fundamental array-level incompatibility among visibility estimators. Collective measurements, {which coherently process the received starlight across multiple time bins in a single joint readout}, remove the array-size penalty up to an order-unity factor, yielding an asymptotic \(O(\sqrt{N})\) enhancement for the {directional-averaged} SNR of visibility measurement. We then propose a memory-assisted interferometric architecture designed to implement collective readout through coherent storage and joint quantum processing. Imaging simulations and Fisher-information analyses demonstrate that collective measurements improve image reconstruction in near-term arrays and enhance the resolving power of future long-baseline architectures, with pronounced benefits for representative AGN targets such as NGC~4151 and 3C~273. These results highlight collective measurement as a promising building block for future quantum-assisted interferometric arrays for stellar imaging.
Comments23 pages (10 pages of main text+13 pages of appendix); 7 figures
