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CAREER: Quantifying Noisy Quantum Resources

职业：量化噪声量子资源

基本信息

批准号：
1652560
负责人：
Graeme Smith
金额：
$ 55万
依托单位：
University of Colorado at Boulder
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-06-15 至 2024-05-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1652560&HistoricalAwards=false
关键词：
CAREER Quantifying Noisy Quantum Resources

项目摘要

While quantum mechanics was originally developed to describe the realm of the very small, it has become increasingly clear over the past decades that quantum theory is at bottom a theory of information. This realization opens the door for a more complete understanding of both quantum theory and information theory. Asking how to best store, transmit, and process information allows the identification of key features of quantum theory and enables the identification of the fundamental limits applying to all information technologies.This project aims to identify, quantify, and ultimately understand the fundamental resources in quantum information theory. It studies optimal interconversion rates of noisy resources, such as quantum communication links and noisy quantum states. Understanding how such noisy resources can be combined to generate quantum synergies is a key challenge to be tackled, as is identifying potential application of such synergies. Just as crucially, determining when such synergies (aka non-additivities) are ruled out is a key challenge to be tackled: This project seeks to determine which resources are additive, and how they can be quantified. Finally, the project seeks to use techniques developed to address additivity and non-additivity to build bridges between quantum information theory and computational complexity theory.The research will be carried out by the PI together with a graduate student, who will learn methods and ideas from physics, information theory, theoretical computer science, and mathematics.

虽然量子力学最初是为了描述非常小的领域而发展起来的，但在过去的几十年里，量子理论本质上是一种信息理论，这一点越来越清楚。这一认识为更全面地理解量子理论和信息理论打开了大门。通过研究如何最好地存储、传输和处理信息，可以识别量子理论的关键特征，并识别适用于所有信息技术的基本限制。本项目旨在识别、量化并最终理解量子信息理论中的基本资源。它研究了噪声资源的最佳相互转换率，如量子通信链路和噪声量子态。了解如何将这些嘈杂的资源结合起来产生量子协同效应是一个需要解决的关键挑战，确定这种协同效应的潜在应用也是如此。同样重要的是，确定何时排除这种协同效应（即非加和性）是一个需要解决的关键挑战：该项目旨在确定哪些资源是加和性的，以及如何量化它们。最后，该项目旨在利用已开发的解决加性和非加性的技术，在量子信息理论和计算复杂性理论之间建立桥梁。该研究将由PI与一名研究生一起进行，该研究生将学习物理学，信息论，理论计算机科学和数学的方法和思想。