PHYS170X HM - Computational Physics

Credit(s): 3

Instructor(s): Sahakian

Description: A modern exposition to the subject of computational physics, drawing examples from various disciplines of physics and the sciences. The first part of this course covers classic algorithms for matrix manipulations, integration and exact numerical differentiation, finding roots and minimization, generating random numbers, Fourier transforms and spectral analysis, optimizing linear and non-linear systems, and Monte Carlo simulations. The second part of the course explores regular and stochastic differential equations, meta-programming and analytical techniques, machine learning techniques such as regressions and classifications, and neural networks. Students will use the Julia programming language throughout, but also explore analytical techniques using Mathematica. (Students may not take both PHYS170 HM and PHYS170X HM.)

Prerequisite(s): PHYS052 HM, PHYS064 HM, and PHYS111 HM