| Popis: |
This first, short, chapter sets the stage for the remainder of the book by introducing some of the underlying issues and some of the ways in which these can be tackled. Scientific Computing is by its very nature a subject that is important because it helps us solve real problems, and those real problems inevitably start with the need to “translate” a question from some other area of science into a mathematical model and then to solve the resulting mathematical problem. The solution will almost always be computational, and approximate, since most models are not amenable to paper and pencil approaches. Therefore we study the process of mathematical modeling and the fundamental topics of scientific computing per se. The latter includes the ability to code your solution algorithm. We have chosen Python as the language for this book and so this first chapter included introductions to both modeling and python programming. Any computational solution has errors inherent in the process. In this introduction we see that simplistic approaches to approximating a function through a power series are often not practical, but that a careful restructuring of the problem can overcome that. |
