Published: 27 April 2017
Hardcover
2694 pages
This is a five-volume collection of 60 papers which have appeared in the Journal of Differential Geometry over the past fifty years ? a showcase of works that have played leading roles in the field of geometry.
The papers have been organized into five volumes by subject matter. The first volume deals with topology, the second with algebraic geometry, the third with geometric ideas, the fourth with geometric analysis, and the fifth with geometric flows. These five volumes provide, in effect, a sort of condensed version of the JDG, helping readers to understand the development of the field of geometry over the past fifty years.
This is a set comprising the following volumes, which may be purchased independently:
Selected Papers from the Journal of Differential Geometry 1967?2017, Volume 1
Selected Papers from the Journal of Differential Geometry 1967?2017, Volume 2
Selected Papers from the Journal of Differential Geometry 1967?2017, Volume 3
Selected Papers from the Journal of Differential Geometry 1967?2017, Volume 4
Selected Papers from the Journal of Differential Geometry 1967?2017, Volume 5
Published: 16 May 2017
Paperback
170 pages
This volume presents lively and engaging articles from the lecturers and the participants of the 23rd Gokova Geometry-Topology Conference, held on the shores of Gokova Bay, Turkey, in May/June of 2016.
Topics include manifolds, special holonomy, symplectic topology, gauge theory, Lie groups, hyperkahler manifolds, and more.
The 23rd Gokova Geometry-Topology Conference was sponsored by the National Science Foundation, by the Turkish Mathematical Society, and by the European Research Council.
D. Salamon and T. Walpuski. gNotes on the octonionsh
G. Tian and G. Xu. gThe symplectic approach of gauged linear Ð-modelh
U. Varolgunes. gOn the equatorial Dehn twist of a Lagrangian nodal sphereh
G. Dimitroglou Rizell and R. Golovko. gThe number of Hamiltonian fixed points on symplectically aspherical manifoldsh
S. Akbulut. gOn infinite order corksh
This volume is part of the Gokova Geometry-Topology Conferences book series.
ISBN: 978-1-119-38755-8
240 pages
July 2017
A fascinating and instructive guide to Markov chains for experienced users and newcomers alike
This unique guide to Markov chains approaches the subject along the four convergent lines of mathematics, implementation, simulation, and experimentation. It introduces readers to the art of stochastic modeling, shows how to design computer implementations, and provides extensive worked examples with case studies.
Markov Chains: From Theory to Implementation and Experimentation begins with a general introduction to the history of probability theory in which the author uses quantifiable examples to illustrate how probability theory arrived at the concept of discrete-time and the Markov model from experiments involving independent variables. An introduction to simple stochastic matrices and transition probabilities is followed by a simulation of a two-state Markov chain. The notion of steady state is explored in connection with the long-run distribution behavior of the Markov chain. Predictions based on Markov chains with more than two states are examined, followed by a discussion of the notion of absorbing Markov chains. Also covered in detail are topics relating to the average time spent in a state, various chain configurations, and n-state Markov chain simulations used for verifying experiments involving various diagram configurations.
Fascinating historical notes shed light on the key ideas that led to the development of the Markov model and its variants
Various configurations of Markov Chains and their limitations are explored at length
Numerous examples?from basic to complex?are presented in a comparative manner using a variety of color graphics
All algorithms presented can be analyzed in either Visual Basic, Java Script, or PHP
Designed to be useful to professional statisticians as well as readers without extensive knowledge of probability theory
Covering both the theory underlying the Markov model and an array of Markov chain implementations, within a common conceptual framework, Markov Chains: From Theory to Implementation and Experimentation is a stimulating introduction to and a valuable reference for those wishing to deepen their understanding of this extremely valuable statistical tool.
Introduces useful data diagnostic tools to non-mathematicians
Includes hands-on computer experiments in R code to learn and run Nonlinear Time Series Analysis
Written for professionals and graduate students in engineering, physical, life and social sciences
Consistent with modern trends in university instruction
Nonlinear Time Series Analysis with R provides a practical guide to emerging empirical techniques allowing practitioners to diagnose whether highly fluctuating and random appearing data are most likely driven by random or deterministic dynamic forces. It joins the chorus of voices recommending 'getting to know your data' as an essential preliminary evidentiary step in modelling. Time series are often highly fluctuating with a random appearance. Observed volatility is commonly attributed to exogenous random shocks to stable real-world systems. However, breakthroughs in nonlinear dynamics raise another possibility: highly complex dynamics can emerge endogenously from astoundingly parsimonious deterministic nonlinear models. Nonlinear Time Series Analysis (NLTS) is a collection of empirical tools designed to aid practitioners detect whether stochastic or deterministic dynamics most likely drive observed complexity. Practitioners become 'data detectives' accumulating hard empirical evidence supporting their modelling approach.
This book is targeted to professionals and graduate students in engineering and the biophysical and social sciences. Its major objectives are to help non-mathematicians?with limited knowledge of nonlinear dynamics?to become operational in NLTS; and in this way to pave the way for NLTS to be adopted in the conventional empirical toolbox and core coursework of the targeted disciplines. Consistent with modern trends in university instruction, the book makes readers active learners with hands-on computer experiments in R code directing them through NLTS methods and helping them understand the underlying logic. The computer code is explained in detail so that readers can adjust it for use in their own work. The book also provides readers with an explicit framework?condensed from sound empirical practices recommended in the literature?that details a step-by-step procedure for applying NLTS in real-world data diagnostics.
Honorable Mention
for the 2015 PROSE Award in Popular Science & Popular Mathematics, Association of American Publishers
Paperback | 2017 | ISBN: 9780691175881
Hardcover | 2014 | ISBN: 9780691150994
208 pp. | 9 x 9 1/2 | 66 color illus. 64 line illus.
f you've ever thought that mathematics and art don't mix, this stunning visual history of geometry will change your mind. As much a work of art as a book about mathematics, Beautiful Geometry presents more than sixty exquisite color plates illustrating a wide range of geometric patterns and theorems, accompanied by brief accounts of the fascinating history and people behind each. With artwork by Swiss artist Eugen Jost and text by math historian Eli Maor, this unique celebration of geometry covers numerous subjects, from straightedge-and-compass constructions to intriguing configurations involving infinity. The result is a delightful and informative illustrated tour through the 2,500-year-old history of one of the most important branches of mathematics.
Prefaces ix
1.Thales of Miletus 1
2.Triangles of Equal Area 3
3.Quadrilaterals 6
4.Perfect Numbers and Triangular Numbers 9
5.The Pythagorean Theorem I