WVU Center for Astrophysics

ASTR 701 – Computational Astrophysics – Fall 2013

Instructor: Dr. Duncan Lorimer

Contact details: Duncan dot Lorimer at mail dot wvu dot edu

Office hours: M/W 1030-1200 in G61 White Hall (or by appointment)

Class times: M/W 0900-1015 in G4/103 White Hall

Overview: This course will give you the basic tools to efficiently analyze astronomical data and address common astrophysics problems. The course will introduce observational astrophysics, data analysis and algorithms. For some of you, this may be your first exposure to computational basics such as the Linux operating system, shell scripts, Latex as a scientific text editor, and the C programming language. The methodologies used will include least squares fitting, Fourier transforms, spectral analysis, Monte Carlo analysis and numerical integration. While this course is designed to prepare students for careers as observational astrophysicists, the analytical skills and programming techniques acquired should be useful for students in any physical science field.

Prerequisites: You are expected to have had a course on differential equations and to have a good background in the general physics that will form the basis for some of our problems. However, no prior knowledge of astronomy is required. Similarly, no knowledge of Linux or any programming language is assumed. Given that some of you coming into the course will have a wide range of backgrounds, I will do my best to optimize our time together by having you complete a questionnaire on day one. Based on your responses, I will dedicate whatever time I consider necessary in the following three class meetings to provide you with enough material to proceed with the rest of the course.

Text: There is no required text book for this course. The following books may be useful: “Astrophysics through computation” by Koberlein & Meisel, “Numerical Recipes” by Press et al., “The C programming language” by Kernighan and Ritchie.

Assessment: 30% Homeworks; 10% mid-term exam; 45% Projects; 15% Final Presentation. In order to develop your writing skills, each homework will be in the form of a short research paper. There will be six assignments (see schedule on next page). In the week following Fall break, there will be an in-class mid-term exam which is designed to test your understanding of the concepts introduced through the six assignments. In the remaing weeks of class, we will work on three different astronomical projects. The projects are more focused assignments on specific astronomical topics. To help you hone your presentation skills, in the final week of class, you will present your analysis of one of these projects in the form of a short (15 minute) talk to the rest of the class.

Grading: 90% or higher = A+; 80-89% = A; 70-79% = B; 60-69% = C; 50-59% = D

Expectations: This is a three credit hour graduate-level course. Be prepared to be challenged! I expect you to come to class and then put in the necessary amount of time outside of class reviewing material and doing assignments. Ask questions to me and your fellow students. Come along to each class prepared and ready to participate.

Class schedule: We will typically meet in G04 on Monday mornings for lectures and in the computer lab (104) on Wednesday mornings to work on the computers. The schedule below is subject to alterations which will be announced in class if necessary.

08/19 Course overview, astronomical resources on the web and course survey
08/21 Linux and LaTeX
08/26 C programming
08/28 C programming
09/04 Data analysis project (HW #1)
09/09 Lecture on hypothesis testing
09/11 Hypothesis testing project (HW #2)
09/16 Lecture on Monte Carlo simulation basics
09/18 Monte Carlo project (HW #3)
09/23 Lecture on time series analysis
09/25 Time series project (HW #4)
09/30 Lecture on Bayesian analysis
10/02 Bayesian project (HW #5)
10/07 Lecture on Fourier analysis
10/09 Fourier project (HW #6)
10/16 In-class mid-term exam
10/21 Project #1: Monte Carlo Simulation of the pulsar population
10/23 work on project #1
10/28 work on project #1
10/30 Project #2: Data analysis of neutral hydrogen observations
11/04 work on project #2
11/06 work on project #2
11/11 Project #3: Data analysis of Chandra X-ray photons
11/13 work on project #3
11/18 work on project #3
11/20 Preparation for final presentations
12/02 Final presentations
12/04 Final presentations

Social justice statement: I aim to maintain a positive learning environment based upon open communication, mutual respect, and non-discrimination. WVU does not discriminate on race, sex, age, disability, veterans status, religion, sexual orientation, color or national origin. I welcome suggestions on furthering this environment.

Academic dishonesty statement: It is assumed that you will follow the University’s policies on academic honesty during this course. Students found engaging in plagarism, cheating or forgery during any assignment or test will be subject to the conduct code policies of WVU which can be found on-line at http://www.arc.wvu.edu/rightsa.html.

© 2015 West Virginia University. Last modified: January 14, 2015. Site design by University Relations, Web.
West Virginia University is an Equal Opportunity/Affirmative Action Institution.
  • MIX
  • Explore the hills of WVU with foursquare
  • WVU on YouTube
  • WVU on Twitter
  • WVU on Facebook
  • WVU on iTunes U
  • Give
  • WVU Alert
  • Mountaineer TRAK
  • MyAccess
  • WVUToday
  • Google+