ABSTRACT
This chapter presents computing basics, starting with some of the tools available as part of the Python ecosystem, and particularly for visualization and matrix manipulations. It discusses number representations and the limits and consequences of using floating-point numbers. The chapter reviews some basic numerical methods for differentiation, integration, and random number generation. Symbolic manipulation software represents a supplementary, yet powerful, approach to computation in physics. Scientific computations must account for the limited amount of computer memory used to represent numbers. Standard computations employ integers represented in fixed-point notation and other numbers in floating-point or scientific notation. Errors and uncertainties are integral parts of computation. Some errors are computer errors arising from the limited precision with which computers store numbers, or because of the approximate nature of algorithm. A common type of uncertainty in computations that involve many steps is round-off errors.
