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Dilations, Linear Matrix Inequalities, the Matrix Cube Problem and Beta Distributions
 
J. William Helton University of California, San Diego, California
Igor Klep The University of Auckland, Auckland, New Zealand
Scott McCullough University of Florida, Gainesville, Florida
Markus Schweighofer Universität Konstanz, Konstanz, Germany
Dilations, Linear Matrix Inequalities, the Matrix Cube Problem and Beta Distributions
Softcover ISBN:  978-1-4704-3455-7
Product Code:  MEMO/257/1232
List Price: $81.00
MAA Member Price: $72.90
AMS Member Price: $48.60
eBook ISBN:  978-1-4704-4947-6
Product Code:  MEMO/257/1232.E
List Price: $81.00
MAA Member Price: $72.90
AMS Member Price: $48.60
Softcover ISBN:  978-1-4704-3455-7
eBook: ISBN:  978-1-4704-4947-6
Product Code:  MEMO/257/1232.B
List Price: $162.00 $121.50
MAA Member Price: $145.80 $109.35
AMS Member Price: $97.20 $72.90
Dilations, Linear Matrix Inequalities, the Matrix Cube Problem and Beta Distributions
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Dilations, Linear Matrix Inequalities, the Matrix Cube Problem and Beta Distributions
J. William Helton University of California, San Diego, California
Igor Klep The University of Auckland, Auckland, New Zealand
Scott McCullough University of Florida, Gainesville, Florida
Markus Schweighofer Universität Konstanz, Konstanz, Germany
Softcover ISBN:  978-1-4704-3455-7
Product Code:  MEMO/257/1232
List Price: $81.00
MAA Member Price: $72.90
AMS Member Price: $48.60
eBook ISBN:  978-1-4704-4947-6
Product Code:  MEMO/257/1232.E
List Price: $81.00
MAA Member Price: $72.90
AMS Member Price: $48.60
Softcover ISBN:  978-1-4704-3455-7
eBook ISBN:  978-1-4704-4947-6
Product Code:  MEMO/257/1232.B
List Price: $162.00 $121.50
MAA Member Price: $145.80 $109.35
AMS Member Price: $97.20 $72.90
  • Book Details
     
     
    Memoirs of the American Mathematical Society
    Volume: 2572019; 104 pp
    MSC: Primary 47; 46; 13; Secondary 60; 33; 90

    An operator \(C\) on a Hilbert space \(\mathcal H\) dilates to an operator \(T\) on a Hilbert space \(\mathcal K\) if there is an isometry \(V:\mathcal H\to \mathcal K\) such that \(C= V^* TV\). A main result of this paper is, for a positive integer \(d\), the simultaneous dilation, up to a sharp factor \(\vartheta (d)\), expressed as a ratio of \(\Gamma \) functions for \(d\) even, of all \(d\times d\) symmetric matrices of operator norm at most one to a collection of commuting self-adjoint contraction operators on a Hilbert space.

  • Table of Contents
     
     
    • Chapters
    • 1. Introduction
    • 2. Dilations and Free Spectrahedral Inclusions
    • 3. Lifting and Averaging
    • 4. A Simplified Form for $\vartheta $
    • 5. $\vartheta $ is the Optimal Bound
    • 6. The Optimality Condition $\alpha =\beta $ inTerms of Beta Functions
    • 7. Rank versus Size for the Matrix Cube
    • 8. Free Spectrahedral Inclusion Generalities
    • 9. Reformulation of the Optimization Problem
    • 10. Simmons’ Theorem for Half Integers
    • 11. Bounds on the Median and the Equipoint of the Beta Distribution
    • 12. Proof of Theorem
    • 13. Estimating $\vartheta (d)$ for Odd $d$
    • 14. Dilations and Inclusions of Balls
    • 15. Probabilistic Theorems and Interpretations Continued
  • Additional Material
     
     
  • Requests
     
     
    Review Copy – for publishers of book reviews
    Permission – for use of book, eBook, or Journal content
    Accessibility – to request an alternate format of an AMS title
Volume: 2572019; 104 pp
MSC: Primary 47; 46; 13; Secondary 60; 33; 90

An operator \(C\) on a Hilbert space \(\mathcal H\) dilates to an operator \(T\) on a Hilbert space \(\mathcal K\) if there is an isometry \(V:\mathcal H\to \mathcal K\) such that \(C= V^* TV\). A main result of this paper is, for a positive integer \(d\), the simultaneous dilation, up to a sharp factor \(\vartheta (d)\), expressed as a ratio of \(\Gamma \) functions for \(d\) even, of all \(d\times d\) symmetric matrices of operator norm at most one to a collection of commuting self-adjoint contraction operators on a Hilbert space.

  • Chapters
  • 1. Introduction
  • 2. Dilations and Free Spectrahedral Inclusions
  • 3. Lifting and Averaging
  • 4. A Simplified Form for $\vartheta $
  • 5. $\vartheta $ is the Optimal Bound
  • 6. The Optimality Condition $\alpha =\beta $ inTerms of Beta Functions
  • 7. Rank versus Size for the Matrix Cube
  • 8. Free Spectrahedral Inclusion Generalities
  • 9. Reformulation of the Optimization Problem
  • 10. Simmons’ Theorem for Half Integers
  • 11. Bounds on the Median and the Equipoint of the Beta Distribution
  • 12. Proof of Theorem
  • 13. Estimating $\vartheta (d)$ for Odd $d$
  • 14. Dilations and Inclusions of Balls
  • 15. Probabilistic Theorems and Interpretations Continued
Review Copy – for publishers of book reviews
Permission – for use of book, eBook, or Journal content
Accessibility – to request an alternate format of an AMS title
Please select which format for which you are requesting permissions.