Algorithmic Number Theory Vol. 1 : Efficient Algorithms

Bach, Eric, Shallit, Jeffrey

ISBN 10: 0262024055 / ISBN 13: 9780262024051

Published by MIT Press, 1996

About this Item

Former library copy. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Seller Inventory # 12555167-20

Bibliographic Details

• Title: Algorithmic Number Theory Vol. 1 : Efficient Algorithms
• Publisher: MIT Press
• Publication Date: 1996
• Language: English
• ISBN 10: 0262024055
• ISBN 13: 9780262024051
• Binding: Hardcover
• Condition: Very Good
• Weight: 2.656 pounds

About this title

Synopsis

Algorithmic Number Theory provides a thorough introduction to the design and analysisof algorithms for problems from the theory of numbers. Although not an elementary textbook, itincludes over 300 exercises with suggested solutions. Every theorem not proved in the text or leftas an exercise has a reference in the notes section that appears at the end of each chapter. Thebibliography contains over 1,750 citations to the literature. Finally, it successfully blendscomputational theory with practice by covering some of the practical aspects of algorithmimplementations.The subject of algorithmic number theory represents the marriage of number theorywith the theory of computational complexity. It may be briefly defined as finding integer solutionsto equations, or proving their non-existence, making efficient use of resources such as time andspace. Implicit in this definition is the question of how to efficiently represent the objects inquestion on a computer. The problems of algorithmic number theory are important both for theirintrinsic mathematical interest and their application to random number generation, codes forreliable 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 Author

Eric Bach is Professor, Computer Sciences Department, University of Wisconsin. Jeffrey Shallit is Associate Professor, Department of Computer Science, University of Waterloo.