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All students taking laboratory courses within the physical sciences
and engineering will benefit from this book, whilst researchers
will find it an invaluable reference. This concise, practical guide
brings the reader up-to-speed on the proper handling and
presentation of scientific data and its inaccuracies. It covers all
the vital topics with practical guidelines, computer programs (in
Python), and recipes for handling experimental errors and reporting
experimental data. In addition to the essentials, it also provides
further background material for advanced readers who want to
understand how the methods work. Plenty of examples, exercises and
solutions are provided to aid and test understanding, whilst useful
data, tables and formulas are compiled in a handy section for easy
reference.
The simulation of physical systems requires a simplified,
hierarchical approach which models each level from the atomistic to
the macroscopic scale. From quantum mechanics to fluid dynamics,
this book systematically treats the broad scope of computer
modeling and simulations, describing the fundamental theory behind
each level of approximation. Berendsen evaluates each stage in
relation to its applications giving the reader insight into the
possibilities and limitations of the models. Practical guidance for
applications and sample programs in Python are provided. With a
strong emphasis on molecular models in chemistry and biochemistry,
this 2007 book will be suitable for advanced undergraduate and
graduate courses on molecular modeling and simulation within
physics, biophysics, physical chemistry and materials science. It
will also be a useful reference to all those working in the field.
Additional resources for this title including solutions for
instructors and programs are available online at
www.cambridge.org/9780521835275.
All students taking laboratory courses within the physical sciences
and engineering will benefit from this book, whilst researchers
will find it an invaluable reference. This concise, practical guide
brings the reader up-to-speed on the proper handling and
presentation of scientific data and its inaccuracies. It covers all
the vital topics with practical guidelines, computer programs (in
Python), and recipes for handling experimental errors and reporting
experimental data. In addition to the essentials, it also provides
further background material for advanced readers who want to
understand how the methods work. Plenty of examples, exercises and
solutions are provided to aid and test understanding, whilst useful
data, tables and formulas are compiled in a handy section for easy
reference.
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