PHYS/ASTR 7730 - Spring 2024#
This website hosts the course materials and labs for PHYS/ASTR 7730, Statistical and Computational Methods in Physics and Astronomy, taught by Yao-Yuan Mao at the University of Utah, in Spring 2024.
Warning
You are looking at the course contents for Spring 2024. The Spring 2025 course will have similar but updated contents.
This course will discuss a few widely applicable statistical and computational methods of analyzing and modeling phenomena in astrophysics, biophysics, and physics in general. The learning objective is to apply the methods learned in this course to connect experimental or observational data with underlying physical processes through numerical simulations and statistical analyses. Topics that will be covered in this course include stochastic process simulations, Monte Carlo methods, Bayesian analysis, and basic machine learning algorithms. This is a graduate-level course. The course will use Python as the programming language for demonstration and use many examples in physics and astronomy. Students are assumed to be comfortable in programming and have an introductory-level knowledge in physics.
Class Information#
Meeting Time & Days: 3:00–4:45 pm on Mondays & Wednesdays
Meeting Location: South Physics (PHYS) 205
Credit Hours: 4
Instructor Information#
Instructor: Yao-Yuan Mao
Instructor Office: INSCC 314
Instructor Email: yymao@astro.utah.edu
Office hours: 1:45–2:45 pm on Mondays
Prerequisites#
No required course prerequisites, but students are expected to be comfortable in coding (preferably in Python) to be able to complete assignments and projects independently.
Useful Links#
Canvas page (uNID login required): Canvas will be used for announcements, official policies, assignment submission, and grading.