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Number theory with computations

Shiu, Peter.

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Number theory with computations

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Number theory with computations/ by Peter Shiu.
作者:	Shiu, Peter.
出版者:	Cham :Springer Nature Switzerland : : 2024.,
面頁冊數:	xvi, 442 p. :ill. (chiefly col.), digital ;24 cm.
內容註:	Part I Elementary Number Theory -- 1 Basics -- 2 Arithmetic functions I -- 3 Prime numbers: Euclid and Eratosthenes -- 4 Quadratic residues and congruences -- 5 Primitive roots -- 6 Sums of squares -- 7 Continued fractions -- Part II Analytic Number Theory -- 8 Diophantine approximations -- 9 Distribution of prime numbers -- 10 Arithmetic functions II -- 11 Prime number theorem -- 12 Primes in arithmetic progressions -- 13 Smooth numbers -- 14 Circle method.
Contained By:	Springer Nature eBook
標題:	Number theory. -
電子資源:	https://doi.org/10.1007/978-3-031-63814-5
ISBN:	9783031638145

Number theory with computations
Shiu, Peter.

Number theory with computations[electronic resource] /by Peter Shiu. - Cham :Springer Nature Switzerland :2024. - xvi, 442 p. :ill. (chiefly col.), digital ;24 cm. - Springer undergraduate mathematics series,2197-4144. - Springer undergraduate mathematics series..

Part I Elementary Number Theory -- 1 Basics -- 2 Arithmetic functions I -- 3 Prime numbers: Euclid and Eratosthenes -- 4 Quadratic residues and congruences -- 5 Primitive roots -- 6 Sums of squares -- 7 Continued fractions -- Part II Analytic Number Theory -- 8 Diophantine approximations -- 9 Distribution of prime numbers -- 10 Arithmetic functions II -- 11 Prime number theorem -- 12 Primes in arithmetic progressions -- 13 Smooth numbers -- 14 Circle method.

This introductory text is designed for undergraduate courses in number theory, covering both elementary number theory and analytic number theory. The book emphasises computational aspects, including algorithms and their implementation in Python. The book is divided into two parts. The first part, on elementary number theory, deals with concepts such as induction, divisibility, congruences, primitive roots, cryptography, and continued fractions. The second part is devoted to analytic number theory and includes chapters on Dirichlet's theorem on primes in arithmetic progressions, the prime number theorem, smooth numbers, and the famous circle method of Hardy and Littlewood. The book contains many topics not often found in introductory textbooks, such as Aubry's theorem, the Tonelli-Shanks algorithm, factorisation methods, continued fraction representations of e, and the irrationality of (3) Each chapter concludes with a summary and notes, as well as numerous exercises. Assuming only basic calculus for the first part of the book, the second part assumes some knowledge of complex analysis. Familiarity with basic coding syntax will be helpful for the computational exercises.

ISBN: 9783031638145

Standard No.: 10.1007/978-3-031-63814-5doiSubjects--Topical Terms:

515832
Number theory.

LC Class. No.: QA241

Dewey Class. No.: 512.7

Number theory with computations
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520 $a This introductory text is designed for undergraduate courses in number theory, covering both elementary number theory and analytic number theory. The book emphasises computational aspects, including algorithms and their implementation in Python. The book is divided into two parts. The first part, on elementary number theory, deals with concepts such as induction, divisibility, congruences, primitive roots, cryptography, and continued fractions. The second part is devoted to analytic number theory and includes chapters on Dirichlet's theorem on primes in arithmetic progressions, the prime number theorem, smooth numbers, and the famous circle method of Hardy and Littlewood. The book contains many topics not often found in introductory textbooks, such as Aubry's theorem, the Tonelli-Shanks algorithm, factorisation methods, continued fraction representations of e, and the irrationality of (3) Each chapter concludes with a summary and notes, as well as numerous exercises. Assuming only basic calculus for the first part of the book, the second part assumes some knowledge of complex analysis. Familiarity with basic coding syntax will be helpful for the computational exercises.
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