STATISTICAL INTERFERENCE FOR QUANTUM SYSTEMS

量子系统的统计干扰

• 批准号: 3774955
• 负责人: J D MALLEY
• 金额: --
• 依托单位: CENTER FOR INFORMATION TECHNOLOGY
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/3774955
• 关键词: computer data analysis; noise; optics; statistics /biometry

This highly interdisciplinary project is dedicated to the theoretical study and practical feasibility of biomedical applications of recently developed statistical decision procedures that operate on data known to be dominated by quantum-mechanical noise. The methodology has been successfully used over the last decade by electrical communications engineers, particularly those involved with quantum optics systems, and allows the statistician, for the first time, the opportunity to undertake nearly-classical statistical decision theory on data that, for example, are known to have, in principle no joint distribution. This latter, highly non-intuitive fact, and others that are equally well experimentally established, all have fundamental consequences for how statisticians must re-think the planning of experiments and data anlayses for processes occurring at the molecular level. This is especially important, for example, when the crucial experiments require, low power levels so as to not distort the true underlying biological processes (in which case not much data can be collected) or when important, but rare, events or markers must be sorted out from other sources of noise, including quantum noise. Of special biomedical interest are novel pairings of this quantum-consistent statistical theory and technologies in the rapidly developing field of light-based imaging devices and detection methods, and analysis techniques using other forms of radiation. Possible biomedical applications thus could include: reduced-dose PET scans; real-time, laser-based, reduced-illumination confocal microscopy of living cells and tissue. Also of interest are applications that involve bioluminescent molecular tagging and enhanced chemiluminescence, which would allow the non-invasive, non-destructive study of biological processes at the level of individual molecules and atoms. Moreover any of the relatively new fields of molecular electronics and electronics using super-lattices and quantum wells, and the manipulation of isolated trapped electons, ions, atoms, molecules or biological organisms, may provide the initial experimental contexts for optimal statistical estimatio and decision making, in the presence of quantum noise.

这个高度跨学科的项目致力于理论 研究和实际可行性的生物医学应用，最近 制定了统计决策程序，对已知的数据进行操作， 由量子力学噪音主导。 在过去十年中， 电气通信工程师，特别是那些参与 量子光学系统，并允许统计学家，第一次， 学习经典统计决策理论的机会 例如，已知原则上没有关节的数据 分布 后者，高度非直觉的事实，以及其他同样好的事实， 实验上建立的，都有基本的后果， 统计学家必须重新思考实验和数据的规划 分析分子水平上发生的过程。 这是 特别重要的是，例如，当关键实验需要时， 低功率水平，以便不扭曲真实的潜在生物 过程（在这种情况下，不能收集太多数据）或 重要但罕见的事件或标记必须从其他事件或标记中挑选出来。 噪声源，包括量子噪声。 具有特殊生物医学意义的是这种新型配对 量子一致性统计理论和技术在快速 开发基于光的成像设备和检测方法的领域， 以及使用其他形式辐射的分析技术。 可能 因此，生物医学应用可以包括：减少剂量的PET扫描; 实时、基于激光的、低照度共聚焦活体显微镜 细胞和组织。 同样令人感兴趣的是涉及以下内容的应用： 生物发光分子标记和增强化学发光， 将允许非侵入性，非破坏性的生物研究， 在单个分子和原子水平上的过程。 此外，任何 相对较新的分子电子学和电子学领域 使用超晶格和量子威尔斯，和操纵孤立的 被俘获的电子、离子、原子、分子或生物有机体可以 为最佳统计估计提供初始实验背景 和决策，在量子噪声的存在。