Understand the relationship of computational physics to the broader discipline of computer science, models of computation, and measures of computational complexity. Apply concepts of numerical stability, precision, and convergence to analyze algorithms.

Be familiar with modern algorithms used in numerical linear algebra, integration and differentiation, Monte Carlo sampling, optimization, approximating solutions to differentiation equations, and Fourier analysis. Know the advantages and limitations of algorithms and how to determine whether an algorithm is appropriate for a particular task. Understand and remediate the complications that arise from finite precision arithmetic.

Be familiar with best practices in code organization, documentation, and version control, particularly for collaborative projects and reproducible science.