Scientific Computing

by Peter Staab

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Solving problems is the essence of scientific computing. Many problems arise naturally from the sciences or mathematics and often to solve difficult problem relies on some computing resources. In a nutshell, this text is the blend of science, mathematics and computer science needed to solve problems. The intended audience for this text one who is interested in writing computer code that will solve a problem that you have.

Description from LibreTexts.

Publisher
Fitchburg State University
Subjects
Mathematics, Scientific Computing Simulations and Modeling
Licence
CC BY-NC-SA, as LibreTexts states it. Non-commercial use only.
Who can read
Tweens profiles and older, judged from its title and subjects

Contents

LibreTexts writes equations in TeX, and here they show as TeX; the PDF has them typeset.

  1. Front Matter
  2. TitlePage
  3. InfoPage
  4. Table of Contents
  5. Licensing
  6. Preface
  7. 1: Introduction to Scientific Computing
  8. 1.1: Examples of Scientific Computing
  9. 1.2: Modeling
  10. 1.3: Computing
  11. 1.4: Ideas needed to do Effective Scientific Computing
  12. 1.5: Examples of Scientific Computing
  13. 1.6: Writing Code for Scientific Computing
  14. 1.7: Let's get started
  15. 2: Storing number and strings and using Julia syntax
  16. 2.1: Numbers
  17. 2.2 Assignment Statement and Variables
  18. 2.3: Strings
  19. 2.4: Expressions and Operator Precedence
  20. 3: Introduction to Data Types
  21. 3.3: Extending integers, the BigInt type
  22. 3.1: Integers
  23. 3.2: Floating Point Numbers
  24. 3.4: Rational and Complex Numbers
  25. 4: Introduction to Functions
  26. 4.1: Simple Examples of Functions
  27. 4.2: Input and Output of Functions
  28. 4.3: Multiple Dispatch
  29. 4.4: Variable Number of arguments
  30. 4.5: Factorial Function
  31. 4.6: Variable Scope
  32. 5: Boolean Statements, Loops and Branching
  33. 5.1: Boolean values and if statements
  34. 5.2: If Statements
  35. 5.3: While Loops
  36. 6: Arrays
  37. 5.1: Introduction to Linear Algebra
  38. 5.2: Advanced Topics in Linear Algebra
  39. 7: Functional Programming and an Introduction to Writing fast code
  40. 6.1: Numerical Integration
  41. 6.2: Differential Equations
  42. 6.3: Optimization
  43. 6.4: Complex Numbers and Analysis
  44. 8: Number theory and Algorithm Development
  45. 7.1: Calculating pi
  46. 7.2: Newton's Method in the Complex Plane
  47. 7.3: Installing and Getting Started with Julia
  48. 7.4: Loading Packages
  49. 7.5: Binary Representation of Numbers
  50. 7.6: References
  51. 9: Algorithm Analysis
  52. 10: Solving Quadratics and Rootfinding
  53. 10.1: Absolute and Relative Errors
  54. 10.2: Rounding Errors and the Quadratic Formula
  55. 10.3: Re-examining the Quadratic Formula
  56. 10.4: Newton’s Method
  57. 11: Plotting Data and Functions
  58. 11.1: The Plots Package
  59. 11.2: Presenting Results with Visualization, an overview
  60. 11.3: Other Function Plots
  61. 11.4: Plotting Data
  62. Back Matter
  63. Index
  64. Glossary
  65. Glossary
  66. Detailed Licensing