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An introduction to probabilistic number theory / Emmanuel Kowalski, Swiss Federal Institute of Technology, Zurich.

By: Material type: TextTextSeries: Cambridge studies in advanced mathematics ; 192Description: pages cmISBN:
  • 9781108840965
Subject(s): Additional physical formats: Online version:: An introduction to probabilistic number theoryDDC classification:
  • 512.7 KOW 23
LOC classification:
  • QA241.7 .K69 2021
Summary: "Despite its seemingly deterministic nature, the study of whole numbers, especially prime numbers, has many interactions with probability theory, the theory of random processes and events. This surprising connection was first discovered around 1920, but in recent years, the links have become much deeper and better understood. Aimed at beginning graduate students, this textbook is the first to explain some of the most modern parts of the story. Such topics include the Chebychev bias, universality of the Riemann zeta function, exponential sums, and the bewitching shapes known as Kloosterman paths. Emphasis is given throughout to probabilistic ideas in the arguments, not just the final statements, and the focus is on key examples over technicalities. The book develops probabilistic number theory from scratch, with short appendices summarizing the most important background results from number theory, analysis, and probability, making it a readable and incisive introduction to this beautiful area of mathematics"--
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Item type Current library Collection Call number Status Date due Barcode
Books Books School of Theoretical Physics New Books Books 512.7 KOW (Browse shelf(Opens below)) Available (New Book) 11647

Includes bibliographical references and index.

"Despite its seemingly deterministic nature, the study of whole numbers, especially prime numbers, has many interactions with probability theory, the theory of random processes and events. This surprising connection was first discovered around 1920, but in recent years, the links have become much deeper and better understood. Aimed at beginning graduate students, this textbook is the first to explain some of the most modern parts of the story. Such topics include the Chebychev bias, universality of the Riemann zeta function, exponential sums, and the bewitching shapes known as Kloosterman paths. Emphasis is given throughout to probabilistic ideas in the arguments, not just the final statements, and the focus is on key examples over technicalities. The book develops probabilistic number theory from scratch, with short appendices summarizing the most important background results from number theory, analysis, and probability, making it a readable and incisive introduction to this beautiful area of mathematics"--

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