株式会社極東書店トップ商品一覧Stochastic Processes and Random Matrices: Lecture Notes of the Les Houches Summer School: Volume 104, July 2015.

商品詳細

Stochastic Processes and Random Matrices: Lecture Notes of the Les Houches Summer School: Volume 104, July 2015.

Stochastic Processes and Random Matrices: Lecture Notes of the Les Houches Summer School: Volume 104, July 2015.

・ISBN 978-0-19-879731-9 hard GB£ 73.00

¥23,126.- (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
電子版あり 大学・学術機関向け電子ブック(eBook)ISBN 9780191838774
著者・編者Schehr, Gregory / Altland, Alexander / Fyodorov, Yan V. / O'Connell, Neil / Cugliandolo, Leticia F. (eds.),
シリーズ (Lecture Notes of the Les Houches Summer School 104)
出版社 (Oxford University Press, UK)
出版年月2017
ページ数640 pp.
言語ENG
ニュース番号<A00-62587>

解説

The field of stochastic processes and Random Matrix Theory (RMT) has been a rapidly evolving subject during the last fifteen years. The continuous development and discovery of new tools, connections and ideas have led to an avalanche of new results. These breakthroughs have been made possible thanks, to a large extent, to the recent development of various new techniques in RMT. Matrix models have been playing an important role in theoretical physics for a long time and they are currently also a very active domain of research in mathematics. An emblematic example of these recent advances concerns the theory of growth phenomena in the Kardar-Parisi-Zhang (KPZ) universality class where the joint efforts of physicists and mathematicians during the last twenty years have unveiled the beautiful connections between this fundamental problem of statistical mechanics and the theory of random matrices, namely the fluctuations of the largest eigenvalue of certain ensembles of random matrices. This text not only covers this topic in detail but also presents more recent developments that have emerged from these discoveries, for instance in the context of low dimensional heat transport (on the physics side) or integrable probability (on the mathematical side).