EAGER: Smart single-pixel quantum statistical imaging beyond the Abbe-Rayleigh criterion

EAGER：超越阿贝-瑞利准则的智能单像素量子统计成像

• 批准号: 2225986
• 负责人: Omar Magana-Loaiza
• 金额: $ 7.55万
• 依托单位: Louisiana State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-15 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2225986&HistoricalAwards=false
• 关键词: EAGER; Smart; single; pixel; quantum

The identification of the photon as a promising information resource has triggered a variety of quantum photonic technologies for multiple purposes that range from information processing to imaging. Recently, the possibility of using the quantum properties of the light field to overcome diffraction has become one of the main goals of quantum imaging. The interest in quantum optical superresolution resides in its potential for improving the performance of existing schemes for remote imaging and microscopy. Interestingly, seminal work that established the foundations of classical superresolution imaging was awarded with the Nobel Prize of Chemistry in 2014. These fundamental contributions demonstrated the possibility of performing imaging beyond the Abbe-Rayleigh resolution criterion. Recently, researchers from the quantum optics community have conducted experiments that aim to boost spatial resolution of classical schemes for imaging by projecting target objects onto spatial modes. These conventional protocols rely on a series of spatial projective measurements to pick up phase information that is then used to boost the spatial resolution of optical systems. Unfortunately, these schemes require a priori information regarding the coherence properties of the light beams, a well as stringent alignment conditions. The purpose of this research program is to demonstrate that the limited spatial resolution of optical instruments can be overcome through measurements of the quantum statistical properties of photons, which are insensitive to diffraction. The identification of the quantum properties of light will be performed using artificial neural networks. The successful completion of the program will enable transformative technology for remote imaging and superresolving microscopy. The educational objectives of this project are to contribute to the inclusive and fair diffusion of science by engaging students to perform research on superresolving imaging, and by developing a series of lectures and demonstrations for general audiences in the Ascension Parish Library from Louisiana.This program includes a series of theoretical and experimental milestones. The theoretical component of this research program aims to develop new formalisms to model the evolution of the properties of quantum coherence of multiparticle systems. These physical systems lead to computationally hard problems scaling on the order of O(2nn!), where n represents the number of photons in the imaging system. The experimental part of the program will be carried out in table-top optical setups. The investigators will prepare multiple light sources with tunable coherence properties and degrees of indistinguishability, these beams will be characterized through photon-number-resolving detection. These capabilities will enable the team to 1) develop a general theory of quantum coherence to describe the photon statistics produced by the combination of an arbitrary number of light sources, 2) design artificial neural networks to demonstrate single-pixel cameras with photon-number resolution, and 3) experimentally demonstrate single-pixel superresolution imaging of an arbitrary number of photon emitters and scatterers. The completion of these milestones will lead to the first family of superresolving single-pixel cameras that exploit the self-learning features of artificial intelligence to identify the statistical fluctuations of truly unknown mixtures of light sources. The potential of these novel photonic devices will be explored in the context of remote imaging and microscopy.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.

将光子识别为有前途的信息资源，已经触发了各种量子光子技术，用于从信息处理到成像的多种用途。最近，使用光场的量子特性克服衍射的可能性已成为量子成像的主要目标之一。对量子光学上分辨率的兴趣在于其在改善现有方案进行远程成像和显微镜检查的潜力。有趣的是，建立经典超分辨率成像基础的开创性工作是在2014年获得诺贝尔化学奖授予的。这些基本贡献表明，有可能执行超出Abbe-Rayleigh分辨率标准的成像。最近，量子光学界的研究人员进行了实验，旨在通过将目标对象投影到空间模式上来提高经典方案的空间分辨率来进行成像。这些常规协议依靠一系列的空间投影测量来获取相位信息，然后用来提高光学系统的空间分辨率。不幸的是，这些方案需要有关光束的相干性能的先验信息，以及严格的比对条件。该研究计划的目的是证明光学仪器的空间分辨率有限，可以通过测量光子的量子统计特性来克服，这对衍射不敏感。光的量子特性将使用人工神经网络进行。该程序的成功完成将实现用于远程成像和整体显微镜的变革技术。该项目的教育目标是通过吸引学生对超分分析成像进行研究，并为路易斯安那州升天教区图书馆中的一系列听众开发一系列的讲座和示威来为科学的包容性和公平传播做出贡献。该计划包括一系列的理论和实验里程碑。 该研究计划的理论组成部分旨在开发新的形式主义，以模拟多粒系统量子相干性的性能的演变。这些物理系统导致计算上的硬性问题在O（2nn！）的顺序上扩展，其中n代表成像系统中的光子数量。该程序的实验部分将在台式光学设置中进行。研究人员将准备多个光源具有可调的连贯性能和不可区分性的程度，这些梁将通过光子数分辨率检测来表征。这些功能将使团队能够达到1）开发量子相干性的一般理论，以描述由任意数量的光源组合产生的光子统计数据，2）设计人工神经网络，以证明单像素数量分辨率和3）实验表现出单像素超级分辨率的光子分辨率超级分辨率图像散布的光子和散射量。这些里程碑的完成将导致第一家像素摄像机的第一个家族，从而利用人工智能的自学特征，以确定光源的真正未知混合物的统计波动。这些新型光子设备的潜力将在远程成像和显微镜的背景下进行探索。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响评估标准通过评估来支持的。

项目成果

Smart quantum statistical imaging beyond the Abbe-Rayleigh criterion

超越阿贝-瑞利准则的智能量子统计成像

• DOI: 10.1038/s41534-022-00593-5
• 发表时间: 2022
• 期刊: npj Quantum Information
• 影响因子: 7.6
• 作者: Bhusal, Narayan;Hong, Mingyuan;Miller, Ashe;Quiroz-Juárez, Mario A.;León-Montiel, Roberto de;You, Chenglong;Magaña-Loaiza, Omar S.
• 通讯作者: Magaña-Loaiza, Omar S.