株式会社極東書店トップ ＞ 商品一覧 ＞ 50 Years of First-Passage Percolation.
商品詳細
50 Years of First-Passage Percolation.
・ISBN 978-1-4704-4183-8 paper US$ 69.00
￥16,166.- (税込) ※（※）価格はご注文時の参考価格となります。
納品価格につきましては書籍の入荷時点で確定となります。
版元の原価改定、外国為替の変動等により異なる場合がございますので、予めご了承下さい。
お気に入り
★★★
| 著者・編者 | Auffinger, Antonio / Damron, Michael / Hanson, Jack, |
|---|---|
| シリーズ | University Lecture Series |
| 出版社 | (American Mathematical Society, US) |
| 出版年月 | 2018 |
| ページ数 | 161 pp. |
| 言語 | ENG |
| ニュース番号 | ＜M25-12596＞ |
解説
First-passage percolation (FPP) is a fundamental model in probability theory that has a wide range of applications to other scientific areas (growth and infection in biology, optimization in computer science, disordered media in physics), as well as other areas of mathematics, including analysis and geometry. FPP was introduced in the 1960s as a random metric space. Although it is simple to define, and despite years of work by leading researchers, many of its central problems remain unsolved.
In this book, the authors describe the main results of FPP, with two purposes in mind. First, they give self-contained proofs of seminal results obtained until the 1990s on limit shapes and geodesics. Second, they discuss recent perspectives and directions including (1) tools from metric geometry, (2) applications of concentration of measure, and (3) related growth and competition models. The authors also provide a collection of old and new open questions. This book is intended as a textbook for a graduate course or as a learning tool for researchers.
In this book, the authors describe the main results of FPP, with two purposes in mind. First, they give self-contained proofs of seminal results obtained until the 1990s on limit shapes and geodesics. Second, they discuss recent perspectives and directions including (1) tools from metric geometry, (2) applications of concentration of measure, and (3) related growth and competition models. The authors also provide a collection of old and new open questions. This book is intended as a textbook for a graduate course or as a learning tool for researchers.