Computational methods in physics, chemistry and biology. An introduction (Q2762627)

The key purpose is stated as a ``single semester undergraduate course in computational physics''. Well done job. Both the contents and the style fit this plan very well. The book is fresh in its spirit. It starts by the praise of computing in the first of its five prefaces, and one finds the address of its web-page in its final, fourth Appendix. The text is packed with exercises (with algorithms implemented mainly in C-code) and the comfort of the reader is maximalized up to his/her possibility of downloading the longer codes directly from the web-page. NEWLINENEWLINENEWLINEThe material is carefully selected, and its presentation emphasizes the maximal accessibility, not only to the student. All ``Evertonians'' (= dedication of the book) might use it as a set of solved problems presenting, mainly though not solely, the applications of quantum mechanics and statistics which range from the simple perturbation recipes up to some applications of stochastic simulations and percolation theory. Thus, the methods which are presented and explained in this book include solvers of differential and matrix equations as well as the Monte Carlo algorithms of several types. NEWLINENEWLINENEWLINEThe set of systems which are picked up and analyzed is broad and covers the classical motion of rockets and diffusion as well as the quantum molecular dynamics or the critical phenomena involving magnetic phases in condensed matter etc. Beyond the realm of physics and chemistry, the reader finds, to his/her great surprise, that the same methods can work equally well in the models of populations in biology (describing, say, a disease propagation) or for an efficient generation of genomes in molecular biology etc. NEWLINENEWLINENEWLINEThe concise text has its natural limitations in its devised ``teaching by example'' (the student cannot use it as its sole resource). At the same time the span of its ideas is impressive (pars pro toto: I liked the short outline of the rich topic of genetic algorithms) and its basic paedagogical philosophy of ``just doing it'' seems to be simply the best one.