Understanding how radiation and charged particles interact with materials is essential for medical physics, aerospace engineering, and semiconductor design. This text-based course guides you from the fundamental physics of particle transport to building your own simulation models using the Monte Carlo method. You will learn to write clean, modular simulation code to track particle trajectories, calculate energy loss, and analyze scattering patterns in complex, multi-layered media. What you'll learn: - Understand the core physics of charged particle interactions and energy deposition in matter. - Apply probability theory to sample physical quantities like scattering angles and free path lengths. - Build structured simulation algorithms using modern Python patterns, including type hints and dataclasses. - Model particle transport across boundaries in heterogeneous and multi-layered materials. - Analyze statistical convergence and estimate simulation uncertainty. The course begins with essential theoretical concepts of radiation physics and probability sampling. You will then progress through step-by-step algorithms, learning how to structure your simulation, handle boundary conditions, and extract meaningful physical data. This course is designed for beginners in scientific computing, engineering students, and software developers looking to understand computational physics. No prior simulation experience is required, though basic Python knowledge is helpful. Start reading today to master the fundamentals of Monte Carlo particle simulations.
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