QuSeC-TAQS: Quantum Sensor Networks for Metrology, Chemistry and Astrophysics

新型量子传感器的出现使得对各种尺度的物理世界的灵敏度和探索达到了前所未有的水平。量子传感器利用了量子相干和纠缠的优势。通过利用分布在多个粒子之间的非局部相关性，量子传感器网络可以在微观和宏观尺度上提高灵敏度并揭示目标信号的空间结构。该项目旨在开发一种协议，以展示量子传感器网络的能力。它包括理解基本属性，进行原理验证实验，以及为不同的科学应用调整不同的平台和规模。该项目将专注于理论概念来描述和增强空间分布式量子传感，利用尖端的量子网络技术在多个平台上：基于金刚石缺陷的纳米级磁共振成像在分子尺度上进行传感；用于感知引力效应的原子钟纠缠网络；量子增强的太赫兹天线网络可以在天文尺度上感知。为了实现高分辨率的磁共振成像，与NV中心相关的顺磁自旋的小簇将用于纠缠增强磁强学和最优控制。这种方法可以实现材料和生物系统中磁场的纳米级分辨率成像。该项目涉及开发一个纠缠时钟网络，将基于纠缠的时间反转量子计量与原子输运相结合，同时保持纠缠。这些能力将用于感知重力梯度，寻找暗物质，以及探索超出标准模型的物理。此外，量子增强型太赫兹天线将利用里德伯原子阵列对宽频率范围（10GHz -几个太赫兹）电场的集体响应。通过光学连接太赫兹接收器并进行可行性研究，该团队的目标是建立全球规模的量子接收器阵列，有可能超越当前技术来探测微弱的恒星物体。实验工作将辅以新颖的理论方法，这些方法结合了量子信息和机器学习的最新进展，包括测量制备的量子多体态、最优控制和机器学习优化控制。这个跨学科项目结合了量子信息、原子-分子-光学物理和机器学习方面的最新技术，对天体物理学、粒子物理学、生物学和化学等学科产生了广泛的影响。该项目由量子传感器挑战赛（QuSeC-TAQS）计划、天文科学部的特殊项目计划、材料研究部的电子和光子材料计划以及国际科学与工程办公室共同资助。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The emergence of new quantum sensors allows for unprecedented levels of sensitivity and exploration of the physical world across various scales. Quantum sensors harness the advantages of quantum coherence and entanglement. By leveraging non-local correlations distributed among multiple particles, networks of quantum sensors can enhance sensitivity and reveal the spatial structure of target signals at both microscopic and macroscopic scales. This project aims to develop a protocol to showcase the capabilities of quantum sensor networks. It involves understanding fundamental properties, conducting proof-of-principle experiments, and adapting approaches to different platforms and scales for diverse scientific applications. The project will focus on theoretical concepts to describe and enhance spatially distributed quantum sensing, utilizing cutting-edge quantum networking technology on multiple platforms: diamond defect-based nanoscale magnetic-resonance imaging to sense on the molecular scale; entangled networks of atomic clocks to sense gravitational effects; and quantum enhanced THz antenna networks to sense on astronomical scales. To achieve high-resolution magnetic resonance imaging, small clusters of paramagnetic spins associated with NV centers will be utilized for entanglement-enhanced magnetometry and optimal control. This approach enables nano-scale resolution imaging of magnetic fields in materials and biological systems. This project involves developing an entangled network of clocks, combining entanglement-based time-reversal quantum metrology with atom transport while maintaining entanglement. These capabilities will be utilized for sensing gravity gradients, searching for dark matter, and exploring physics beyond the standard model. Additionally, a quantum enhanced THz antenna will utilize collective response of Rydberg atom arrays to electric fields across a broad frequency range (10GHz - few THz). By optically connecting THz receivers and conducting a feasibility study, this team aims to establish global-scale quantum receiver arrays, potentially enabling the detection of faint stellar objects beyond current technology. The experimental work will be complemented by novel theoretical methods that incorporate recent advancements in quantum information and machine learning, including measurement-prepared quantum many-body states, optimal control, and machine learning-optimized controls. This interdisciplinary project combines state-of-the-art technologies in quantum information, atomic-molecular-optical physics, and machine learning, with wide-ranging impact across disciplines such as astrophysics, particle physics, biology, and chemistry. This project was co-funded by the Quantum Sensors Challenge for Transformative Advances in Quantum Systems (QuSeC-TAQS) program, the Special Projects program in the Division of Astronomical Sciences, the Electronic and Photonic Materials program in the Division of Materials Research, and with co-funding from the Office of International Science and Engineering.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.