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Miloslav Znojil
Reviewer number:
Item's zbl-Number:
Harrison, Paul
Computational methods in physics, chemistry and biology
Chichester: Wiley, 2001
Primary Classification:
65-01Instructional exposition textbooks, tutorial papers, etc.
Secondary Classification:
81-04 82-08 92-08 15-04 34-04 65C05 65Z05 92D25 Sorry no match found within MSC 2000.
numerical methods; Schroedinger equation; simulation; Monte Carlo methods; percolation; genetic algorithms; molecular dynamics; population dynamics

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.

The 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.

The 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.

The 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.
Remarks to the editors:
corrected version (classification misprint and misread); difficulties caused by your server
(connection denied with the new fill-out form filled)

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