"The Mathematics of Encryption: An Elementary Introduction,” by DIMACS faculty member Midge Cozzens and Steven Miller of Williams College, is part of the Mathematical World series published by AMS. The series features accessible expository works that illustrate the beauty and utility of mathematics. In keeping with the series philosophy, this new book introduces just enough mathematics to explore topics that include classical and modern methods of encryption, ciphers, secret-sharing, error detection and correction, steganography, and quantum cryptography. The book is an outgrowth of introductory cryptography courses for non-math majors taught at both Rutgers and Williams. It is suitable for a wide range of audiences, both inside and outside the classroom.
The second new book, “Graph Partitioning and Graph Clustering,” is part of the AMS series in Contemporary Mathematics. The book is a compilation of papers resulting from the 10th DIMACS Implementation Challenge on Graph Partitioning and Graph Clustering held in February 2012. It is edited by the Challenge organizers, David Bader, Henning Meyerhenke, Peter Sanders, and Dorothea Wagner. Implementation Challenges seek to benchmark realistic algorithm performance for important problem classes when worst-case analysis is overly pessimistic and probabilistic models are too unrealistic. They use experimentation to gain insight into practical algorithm performance when analysis fails. By evaluating different implementations on common instances, the Challenges create a reproducible picture of the state of the art in the area under consideration. They often lead to improved implementation methods and data structures and take a step toward technology transfer by providing leading-edge implementations of algorithms for others to use and adapt.
Some of the contributions of the 10th Challenge include: extension of a file format used by several graph partitioning and graph clustering libraries for graphs and their partitions; an online testbed of input instances and generators; definition of a new combination of measures to assess the quality of a clustering; definition of a measure to assess the work an implementation performs in a parallel setting to normalize sequential and parallel implementations to a common baseline; and a nondiscriminatory way to assign scores to solvers that takes both running time and solution quality into account.