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Computers Computer Science

Algorithmic Number Theory

Efficient Algorithms

by (author) Eric Bach & Jeffrey Shallit

Publisher
The MIT Press
Initial publish date
Aug 1996
Category
Computer Science
Recommended Age
18
Recommended Grade
12
  • Paperback / softback

    ISBN
    9780262526296
    Publish Date
    Aug 1996
    List Price
    $94.00 USD

Classroom Resources

Where to buy it

Description

Algorithmic Number Theory provides a thorough introduction to the design and analysis of algorithms for problems from the theory of numbers. Although not an elementary textbook, it includes over 300 exercises with suggested solutions. Every theorem not proved in the text or left as an exercise has a reference in the notes section that appears at the end of each chapter.

Algorithmic Number Theory provides a thorough introduction to the design and analysis of algorithms for problems from the theory of numbers. Although not an elementary textbook, it includes over 300 exercises with suggested solutions. Every theorem not proved in the text or left as an exercise has a reference in the notes section that appears at the end of each chapter. The bibliography contains over 1,750 citations to the literature. Finally, it successfully blends computational theory with practice by covering some of the practical aspects of algorithm implementations. The subject of algorithmic number theory represents the marriage of number theory with the theory of computational complexity. It may be briefly defined as finding integer solutions to equations, or proving their non-existence, making efficient use of resources such as time and space. Implicit in this definition is the question of how to efficiently represent the objects in question on a computer. The problems of algorithmic number theory are important both for their intrinsic mathematical interest and their application to random number generation, codes for reliable and secure information transmission, computer algebra, and other areas. Publisher's Note: Volume 2 was not written. Volume 1 is, therefore, a stand-alone publication.

About the authors

Eric Bach received his doctorate from the University of California at Berkeley. He is currently an Assistant Professor of Computer Science at the University of Wisconsin at Madison.

Eric Bach's profile page

Jeffrey Shallit's profile page