Computation in science : from concepts to practice /

In the course of only a few decades computers have revolutionized scientific research and more and more scientists are writing computer programs for doing their work. In spite of the ubiquitous use of computers in science, few researchers in the natural sciences have any schooling in computer scienc...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Hinsen, Konrad (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Bristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) : IOP Publishing, [2020]
Edición:Second edition.
Colección:IOP ebooks. 2020 collection.
Temas:
Science > Mathematics.
Computer modelling & simulation.
SCIENCE / Physics / Mathematical & Computational.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • 1. What is computation?
  • 1.1. Defining computation
  • 1.2. The roles of computation in scientific research
  • 1.3. Analog computing
  • 1.4. Further reading
  • 2. Computation in science
  • 2.1. Traditional science : celestial mechanics
  • 2.2. Scientific models and computation
  • 2.3. Computation at the interface between observations and models
  • 2.4. Computation for developing insight
  • 2.5. The impact of computing on science
  • 2.6. Further reading
  • 3. Formalizing computation
  • 3.1. From manual computation to rewriting rules
  • 3.2. From computing machines to automata theory
  • 3.3. Computability
  • 3.4. Restricted models of computation
  • 3.5. Computational complexity
  • 3.6. Computing with numbers
  • 3.7. Further reading
  • 4. Automating computation
  • 4.1. Computer architectures
  • 4.2. Programming languages
  • 4.3. Observing program execution
  • 4.4. Software engineering
  • 4.5. Further reading
  • 5. Taming complexity
  • 5.1. Chaos and complexity in computation
  • 5.2. Verification, validation, and testing
  • 5.3. Abstraction
  • 5.4. Managing state
  • 5.5. Incidental complexity and technical debt
  • 5.6. Further reading
  • 6. Computational reproducibility
  • 6.1. Reproducibility : a core value of science
  • 6.2. Repeating, reproducing, replicating
  • 6.3. The role of computation in the reproducibility crisis
  • 6.4. Non-reproducible determinism
  • 6.5. Staged computation
  • 6.6. Replicability, robustness, and reuse
  • 6.7. Managing software evolution
  • 6.8. Best practices for reproducible and replicable computational science
  • 6.9. Further reading
  • 7. Outlook : scientific knowledge in the digital age
  • 7.1. The scientific record goes digital
  • 7.2. Procedural knowledge turns into software
  • 7.3. Machine learning : the fusion of factual and procedural knowledge
  • 7.4. The time scales of scientific progress and computing
  • 7.5. The industrialization of science
  • 7.6. Preparing the future
  • 7.7. Further reading.

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