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Functional Analytic Methods in Matrix Theory, Majorization and Quantum Information

Functional Analytic Methods in Matrix Theory, Majorization and Quantum Information
矩阵理论、大化和量子信息中的泛函分析方法
批准号:
RGPIN-2022-04149
负责人:
Pereira, Rajesh
金额:
$1.53万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2022
资助国家:
加拿大
项目状态:
已结题
起止时间:
2022-01-01 至 2023-12-31

项目摘要

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中文摘要
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英文摘要
This research project aims to use techniques from functional analysis to study and solve some interconnected problems in quantum computing, matrix theory and the majorization order.  Success in this research project will deepen our understanding of the interconnections between these fields and will contribute to developing some interesting mathematical techniques that are useful in quantum computation.  Rudimentary quantum computers are already being built and advances in our understanding of quantum computation can yield significant technological advancement.
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Classes of Positive Semidefinite Matrices with applications to Quantum Information
  • 批准号:
    RGPIN-2016-04387
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.6万
  • 财政年份:
    2021
  • 负责人:
    Pereira, Rajesh
  • 依托单位:
Classes of Positive Semidefinite Matrices with applications to Quantum Information
  • 批准号:
    RGPIN-2016-04387
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.6万
  • 财政年份:
    2020
  • 负责人:
    Pereira, Rajesh
  • 依托单位:
Classes of Positive Semidefinite Matrices with applications to Quantum Information
  • 批准号:
    RGPIN-2016-04387
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.6万
  • 财政年份:
    2019
  • 负责人:
    Pereira, Rajesh
  • 依托单位:
Classes of Positive Semidefinite Matrices with applications to Quantum Information
  • 批准号:
    RGPIN-2016-04387
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.6万
  • 财政年份:
    2018
  • 负责人:
    Pereira, Rajesh
  • 依托单位:
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