Large Baseline Quantum-Enhanced Imaging Networks

成像和参数估计是大多数现代科学的基础，改进成像技术的发展将在科学和文化方面产生极其广泛的影响。目前的成像技术受到孔径大小、损耗和系统噪声的限制，但最近的研究结果表明，采用量子计量技术可以克服衍射极限。量子增强计量的实现需要可靠的大尺度纠缠态源。然而，这种状态非常脆弱，很容易被环境噪声破坏。因此，量子增强传感的演示目前仅限于实验室环境。与此同时，物理学家正在构建更大的量子网络，有望实现安全通信和分布式量子计算。量子网络提供了允许量子态从一个位置转移到另一个位置的资源，在那里相位和振幅信息都被忠实地再现。结合量子互联网空间分离的共享量子资源和大规模成像的需求，我们可以设计出原则上实现成像分辨率提高许多数量级的协议。在本理论提案中，我们开发了用于在量子网络上执行2D和3D成像和传感的最佳架构，并能够通过专用量子纠错协议减轻损失和噪声。同时，我们将设计非相干成像处理方法，使人们能够在光学频率下获得极大的基线（例如，地球的直径或更大）。我们首先构建了高精度时间测量的理论，这为进行时钟同步和执行目标测距/检测开辟了可能性。然后，我们在遥远的地点之间建立共享相位参考，允许在成像孔径的远端收集信号的相干处理。然后，我们将使用大型网络进行成像，并通过量子纠错集成损耗和噪声保护。最后，我们探索了训练量子干涉仪的方法，用于热态和纠缠态的物体识别。因此，该项目通过测量优化以及状态优化（包括量子误差校正）消除了当前成像和参数估计的限制。本项目具有连接量子成像、量子计量和量子通信的宏伟目标，将对整个量子技术领域产生深远影响。它提出了一种新的、统一的大基线二维和三维量子成像和计量理论，将与昆士兰大学（澳大利亚）、埃尔兰根大学（德国）和布里斯托尔大学（英国）的实验专业知识紧密结合。结果将带来低噪声探测器，高度精确的测量，以及通过创新的实验设计实现的超分辨率图像。该系统将特别适合在高噪声环境中工作，应用于恒星干涉测量和测距；它们将直接影响英国在加密应用、导航系统、现场传感器和通信技术方面对量子信息的使用。

Imaging and parameter estimation underpin most of modern science, and the development of improved imaging techniques will have an extremely broad impact, scientifically and culturally. Current imaging techniques are limited by aperture size, losses, and system noise, but recent results show that the diffraction limit can be overcome by employing techniques from quantum metrology. The realisation of quantum-enhanced metrology requires reliable sources of large-scale entangled states. However, such states are extremely fragile and are easily destroyed by environmental noise. As such, demonstrations of quantum-enhanced sensing are presently limited to a laboratory setting.Meanwhile, physicists are building ever-larger quantum networks, with the promise of secure communication and distributing quantum computing. Quantum networks provide resources that allow the transfer of quantum states from one location to another, where both phase and amplitude information is faithfully reproduced. Combining the spatially separated shared quantum resources of the Quantum Internet with the requirements of large-scale imaging, we can devise protocols that in principle achieve imaging resolution that is many orders of magnitude better. In this theoretical proposal we develop the optimal architecture for performing 2D and 3D imaging and sensing on a quantum network, with the ability to mitigate loss and noise via dedicated quantum error correction protocols. In parallel, we will devise incoherent imaging processing methods, allowing one to achieve extremely large baselines, (e.g., the diameter of the Earth or larger) at optical frequencies. We first construct the theory for high-accuracy time measurements, which opens up the possibility to perform clock synchronization and perform target ranging/detection. Then we establish shared phase references between distant sites, allowing coherent processing of signals collected at far ends of our imaging aperture. Then, we will use large networks to perform imaging, integrated with loss and noise protection via quantum error correction. Lastly, we explore methods to train a quantum interferometer for object recognition for both thermal and entangled states. Thus, the project removes the current limitations of imaging and parameter estimation by measurement optimisation, as well as state optimisation (including quantum error correction).This project has the ambitious goal of linking quantum imaging, quantum metrology and quantum communication, with a profound impact on the whole field of quantum technologies. It presents a novel, unified theory on large-baseline 2D and 3D quantum imaging and metrology that will be tightly combined with the experimental expertise of the Universities of Queensland (Australia), Erlangen (Germany), and Bristol (UK). The result will bring about low-noise detectors, highly accurate measurements, and super-resolved images, enabled by innovative experimental designs. The systems will be particularly suited to operate in a high-noise environment, with applications to stellar interferometry, and ranging; they will directly impact the UK's use of quantum information for cryptographic applications, navigation systems, field sensors, and communication technologies.