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Quantum Computation and Quantum Information: A Mathematical Perspective
 
J. M. Landsberg Texas A&M University, College Station, TX
Hardcover ISBN:  978-1-4704-7557-4
Product Code:  GSM/243
List Price: $135.00
MAA Member Price: $121.50
AMS Member Price: $108.00
Softcover ISBN:  978-1-4704-7777-6
Product Code:  GSM/243.S
List Price: $89.00
MAA Member Price: $80.10
AMS Member Price: $71.20
eBook ISBN:  978-1-4704-7776-9
Product Code:  GSM/243.E
List Price: $85.00
MAA Member Price: $76.50
AMS Member Price: $68.00
Softcover ISBN:  978-1-4704-7777-6
eBook: ISBN:  978-1-4704-7776-9
Product Code:  GSM/243.S.B
List Price: $174.00 $131.50
MAA Member Price: $156.60 $118.35
AMS Member Price: $139.20 $105.20
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Quantum Computation and Quantum Information: A Mathematical Perspective
J. M. Landsberg Texas A&M University, College Station, TX
Hardcover ISBN:  978-1-4704-7557-4
Product Code:  GSM/243
List Price: $135.00
MAA Member Price: $121.50
AMS Member Price: $108.00
Softcover ISBN:  978-1-4704-7777-6
Product Code:  GSM/243.S
List Price: $89.00
MAA Member Price: $80.10
AMS Member Price: $71.20
eBook ISBN:  978-1-4704-7776-9
Product Code:  GSM/243.E
List Price: $85.00
MAA Member Price: $76.50
AMS Member Price: $68.00
Softcover ISBN:  978-1-4704-7777-6
eBook ISBN:  978-1-4704-7776-9
Product Code:  GSM/243.S.B
List Price: $174.00 $131.50
MAA Member Price: $156.60 $118.35
AMS Member Price: $139.20 $105.20
  • Book Details
     
     
    Graduate Studies in Mathematics
    Volume: 2432024; 204 pp
    MSC: Primary 81; 68; 94; 20

    This book presents the basics of quantum computing and quantum information theory. It emphasizes the mathematical aspects and the historical continuity of both algorithms and information theory when passing from classical to quantum settings.

    The book begins with several classical algorithms relevant for quantum computing and of interest in their own right. The postulates of quantum mechanics are then presented as a generalization of classical probability. Complete, rigorous, and self-contained treatments of the algorithms of Shor, Simon, and Grover are given. Passing to quantum information theory, the author presents it as a straightforward adaptation of Shannon's foundations to information theory. Both Shannon's theory and its adaptation to the quantum setting are explained in detail. The book concludes with a chapter on the use of representation theory in quantum information theory. It shows how all known entropy inequalities, including the celebrated strong subadditivity of von Neumann entropy, may be obtained from a representation theory perspective.

    With many exercises in each chapter, the book is designed to be used as a textbook for a course in quantum computing and quantum information theory. Prerequisites are elementary undergraduate probability and undergraduate algebra, both linear and abstract. No prior knowledge of quantum mechanics or information theory is required.

    Readership

    Graduate students and research mathematicians interested in the mathematical aspects of quantum computing.

  • Table of Contents
     
     
    • Chapters
    • Classical and probabilistic computation
    • Quantum mechanics for quantum computation
    • Algorithms
    • Classical information theory
    • Language and background material for quantum information theory
    • Quantum information
    • Representation theory and quantum information
    • Algebra and linear algebra
    • Probability
    • Hints and answers to selected exercises
  • Additional Material
     
     
  • Requests
     
     
    Review Copy – for publishers of book reviews
    Desk Copy – for instructors who have adopted an AMS textbook for a course
    Examination Copy – for faculty considering an AMS textbook for a course
    Accessibility – to request an alternate format of an AMS title
Volume: 2432024; 204 pp
MSC: Primary 81; 68; 94; 20

This book presents the basics of quantum computing and quantum information theory. It emphasizes the mathematical aspects and the historical continuity of both algorithms and information theory when passing from classical to quantum settings.

The book begins with several classical algorithms relevant for quantum computing and of interest in their own right. The postulates of quantum mechanics are then presented as a generalization of classical probability. Complete, rigorous, and self-contained treatments of the algorithms of Shor, Simon, and Grover are given. Passing to quantum information theory, the author presents it as a straightforward adaptation of Shannon's foundations to information theory. Both Shannon's theory and its adaptation to the quantum setting are explained in detail. The book concludes with a chapter on the use of representation theory in quantum information theory. It shows how all known entropy inequalities, including the celebrated strong subadditivity of von Neumann entropy, may be obtained from a representation theory perspective.

With many exercises in each chapter, the book is designed to be used as a textbook for a course in quantum computing and quantum information theory. Prerequisites are elementary undergraduate probability and undergraduate algebra, both linear and abstract. No prior knowledge of quantum mechanics or information theory is required.

Readership

Graduate students and research mathematicians interested in the mathematical aspects of quantum computing.

  • Chapters
  • Classical and probabilistic computation
  • Quantum mechanics for quantum computation
  • Algorithms
  • Classical information theory
  • Language and background material for quantum information theory
  • Quantum information
  • Representation theory and quantum information
  • Algebra and linear algebra
  • Probability
  • Hints and answers to selected exercises
Review Copy – for publishers of book reviews
Desk Copy – for instructors who have adopted an AMS textbook for a course
Examination Copy – for faculty considering an AMS textbook for a course
Accessibility – to request an alternate format of an AMS title
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