Quantum divergences and convex optimization

量子发散和凸优化

• 批准号: 2602157
• 金额: --
• 依托单位: University of Cambridge
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2602157
• 关键词: Quantum; divergences; convex; optimization

Quantum divergences have enabled important recent advances in the theory of quantum information. In parallel, ideas from convex optimization such as semidefinite programming play an important role in the study of problems such as entanglement detection, and nonlocal games. The goal of the project is to combine tools from quantum divergences and convex optimization to tackle new fundamental problems in the theory of quantum information and more particularly in quantum many-body systems.

量子发散使量子信息理论的最新进展成为可能。同时，半定规划等凸优化的思想在纠缠检测和非局部博弈等问题的研究中发挥了重要作用。该项目的目标是将量子发散和凸优化的联合收割机工具结合起来，以解决量子信息理论中的新的基本问题，特别是量子多体系统。