Biology is a source of fascination for most scientists, whether their training is in the life sciences or not. In particular, there is a special satisfaction in discovering an understanding of biology in the context of another science like mathematics. For- nately there are plenty of interesting problems (and fun) in biology, and virtually all scienti?c disciplines have become the richer for it. For example, two major journals, MathematicalBiosciences andJournalofMathematicalBiology, have tripled in size since their inceptions 20-25 years ago. More recently, the advent of genomics has spawned...
Biology is a source of fascination for most scientists, whether their training is in the life sciences or not. In particular, there is a special satis...
In this text, students of applied mathematics, science and engineering are introduced to fundamental ways of thinking about the broad context of parallelism. The authors begin by giving the reader a deeper understanding of the issues through a general examination of timing, data dependencies, and communication. These ideas are implemented with respect to shared memory, parallel and vector processing, and distributed memory cluster computing. Threads, OpenMP, and MPI are covered, along with code examples in Fortran, C, and Java. The principles of parallel computation are applied throughout as...
In this text, students of applied mathematics, science and engineering are introduced to fundamental ways of thinking about the broad context of paral...
In this text, students of applied mathematics, science and engineering are introduced to fundamental ways of thinking about the broad context of parallelism. The authors begin by giving the reader a deeper understanding of the issues through a general examination of timing, data dependencies, and communication. These ideas are implemented with respect to shared memory, parallel and vector processing, and distributed memory cluster computing. Threads, OpenMP, and MPI are covered, along with code examples in Fortran, C, and Java. The principles of parallel computation are applied throughout as...
In this text, students of applied mathematics, science and engineering are introduced to fundamental ways of thinking about the broad context of paral...
Monte Carlo methods are among the most used and useful computational tools available today, providing efficient and practical algorithims to solve a wide range of scientific and engineering problems. Applications covered in this book include optimization, finance, statistical mechanics, birth and death processes, and gambling systems.
Explorations in Monte Carlo Methods provides a hands-on approach to learning this subject. Each new idea is carefully motivated by a realistic problem, thus leading from questions to theory via examples and numerical simulations. Programming...
Monte Carlo methods are among the most used and useful computational tools available today, providing efficient and practical algorithims to solve ...
This text introduces upper division undergraduate/beginning graduate students in mathematics, finance, or economics, to the core topics of a beginning course in finance/financial engineering. Particular emphasis is placed on exploiting the power of the Monte Carlo method to illustrate and explore financial principles. Monte Carlo is the uniquely appropriate tool for modeling the random factors that drive financial markets and simulating their implications.
The Monte Carlo method is introduced early and it is used in conjunction with the geometric Brownian motion model (GBM) to...
This text introduces upper division undergraduate/beginning graduate students in mathematics, finance, or economics, to the core topics of a beginn...