18. Appendices

The following appendices take a step back from specific Julia commands to explore two foundational topics in computer science that are essential for any computational work. These sections look “under the hood” to explain the “how” and “why” behind your code’s performance and numerical behavior. First, we will demystify floating-point arithmetic, revealing how computers approximate real numbers and why this is crucial for understanding numerical precision and avoiding common pitfalls. Next, we will introduce algorithmic efficiency and Big O notation, providing you with the essential tools to reason about how your programs scale in time and memory. A solid grasp of these concepts is what separates a casual coder from a skilled computational scientist.