Skip to main content
Chaptra
Cover of Computing for Scientists

Computing for Scientists

Written by R. J. Barlow,A. R. Barnett

Not rated yet — tap a star to review it

300 pages, about 6 hours of reading

Chaptra reads alongside you — AI insights, chapter breakdowns and reader discussions for every book. Join free

About this book

The Manchester Physics Series General Editors: D. J. Sandiford; F. Mandl; A. C. Phillips Department of Physics and Astronomy, University of Manchester Properties of Matter B. H. Flowers and E. Mendoza Optics Second Edition F. G. Smith and J. H. Thomson Statistical Physics Second Edition F. Mandl Electromagnetism Second Edition I. S. Grant and W. R. Phillips Statistics R. J. Barlow Solid State Physics Second Edition J. R. Hook and H. E. Hall Quantum Mechanics F. Mandl Particle Physics Second Edition B. R. Martin and G. Shaw The Physics of Stars A. C. Phillips Computing for Scientists R. J. Barlow and A. R. Barnett Computing for Scientists focuses on the principles involved in scientific programming. Topics of importance and interest to scientists are presented in a thoughtful and thought-provoking way, with coverage ranging from high-level object-oriented software to low-level machine-code operations. Taking a problem-solving approach, this book gives the reader an insight into the ways programs are implemented and what actually happens when they run. Throughout, the importance of good programming style is emphasised and illustrated. Two languages, Fortran 90 and C++, are used to provide contrasting examples, and explain how various techniques are used and when they are appropriate or inappropriate. For scientists and engineers needing to write programs of their own or understand those written by others, Computing for Scientists: * Is a carefully written introduction to programming, taking the reader from the basics to a considerable level of sophistication. * Emphasises an understanding of the principles and the development of good programming skills. * Includes optional "starred" sections containing more specialised and advanced material for the more ambitious reader. * Assumes no prior knowledge, and has many examples and exercises with solutions included at the back of the book.

Read it with a club

Chaptra's ideas and essays clubs — small groups reading the same books and talking as they go.

All clubs
A bright library atrium seen from above

Books That Changed My Mind

Ideas and essays

  • 5 members
  • 4 discussions
  • Active 10h ago

Not books you enjoyed. Books that moved you off a position you'd genuinely held for years. This is a Chaptra house club — set up and moderated by us to get the conversation going. Open to everyone; jump in anywhere.

Read Computing for Scientists alongside people who are reading it too.

Chaptra Prime — paid clubs, every club feature, and unlimited reading support, for $5 a month or $60 once.

See Prime

Reading guide

Themes, characters and key ideas in Computing for Scientists, written by Chaptra AI.

  • about 40 hours
  • intermediate
  • informative
  • instructive
  • practical

''Computing for Scientists'' by Barlow and Barnett is a foundational textbook designed to introduce scientists and engineers to the principles of scientific programming. It emphasizes a problem-solving approach, guiding readers from basic concepts to sophisticated programming techniques, with a strong focus on developing good programming style. The book covers a wide spectrum of topics, from high-level object-oriented design to low-level machine operations, providing insights into program implementation and execution. By contrasting Fortran 90 and C++, it illustrates diverse programming paradigms and their appropriate applications, making it an invaluable resource for those needing to write or understand scientific code.

''Computing for Scientists focuses on the principles involved in scientific programming.''

Key themes

Good Programming Style
This theme is paramount, emphasizing the critical importance of writing clear, efficient, maintainable, and robust code. The book doesn't just mention style but illustrates it through contrasting examples and practical advice, showing how good style prevents errors, facilitates collaboration, and improves long-term usability of scientific software.
Problem-Solving Approach
The book frames programming as a tool for solving scientific problems, guiding the reader to think computationally about real-world challenges. It focuses on breaking down complex problems, designing algorithms, and implementing solutions, rather than just learning language syntax in isolation. This cultivates a critical and analytical mindset essential for scientific inquiry.
Understanding Underlying Mechanisms
Beyond just writing code, the book aims to provide insight into how programs are executed and what happens at a lower level. This includes concepts ranging from memory management to machine-code operations, which are crucial for optimizing performance, debugging complex issues, and making informed choices about language features and data structures in computationally intensive scientific tasks.

Worth discussing

How do the principles of good programming style discussed in the book translate to modern software development practices?

Chapter-by-chapter breakdowns, character arcs and the full thematic analysis come with a free account.

Discussions

No one has started one yet

Join

Questions this book opens up

No discussions yet

Be the first to start a discussion about this book!

Sign up to start the discussion

Reviews

No reviews yet

Be the first to review this book!