Course Syllabus

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Physics 345, Fall 2022: Introduction to Computational Astrophysics

Prof. Blakesley Burkhart 

Class meetings: Monday/Thursday 12:10-1:30pm, ARC 206

Office hours:

Communication - please use Canvas as much as possible:

  • For general questions about the course, please try Canvas Chat.
  • For questions about specific topics in the course, please use Canvas Discussions.
  • For confidential matters, please use email through Canvas Inbox.

Catalog description

Introduction to computational astrophysics, including key algorithms, their implementation in code, and their application to current research in astrophysics.  Extended projects feature analysis of real data and simulations.

 

Course Details:

Computation plays an increasingly important role in physics and astrophysics and many other fields, to the point that we view it as an essential part of an astrophysics degree. We designed this course to help you understand computational methods and how to use them. The latter phrase is critical; you can truly understand and learn computation only by doing it in a hands-on way.  In this course, you will have many opportunities to apply computational methods to astrophysical problems, and evaluate their validity. Computation expands the range of problems we can take on, bridging the gap between pencil-and-paper problem sets and bona fide research. Thus, this course also offers an introduction to research, inviting you to design and implement a computational analysis of two research problems in astrophysics, and deliver the results in a professional-style paper and presentation. I don’t even expect you to memorize intricate details of the computational methods we will use.  Rather, I hope you will learn how to learn computational methods. That way you can have both the skill and confidence to master new methods when you encounter them in the future.

You will gain experience using models to connect general concepts and theories with specific measurements and predictions. Talking with researchers and working on the projects will help you understand why models are necessary in the first place. You will also consider whether your models and methods are valid.  Last but not least, you will use scientific literature to place your work in context, both technically and conceptually. These are some of the intellectual skills that couple with technical ability to foster success in research.

It may not be immediately obvious, but this course will also help prepare you for a career in ways that are not limited to astrophysics. Employers routinely highlight critical thinking/problem solving, teamwork/collaboration, professionalism/work ethic, and oral/written communications. In this course, you will engage in problem-solving all semester, you will reflect on the context for your work, and you will explain your findings in both written and oral forms. Much of the effort will be collaborative such that your whole team benefits when you complete your responsibilities well and on time. I encourage you to look beyond the disciplinary content and ponder how the overall experience can enrich whatever steps you take next.

 

Technology requirements

You need to have access to python, especially jupyter notebooks; the (Links to an external site.) Anaconda distribution (Links to an external site.) is recommended and available for free. Additional,  tools include (Links to an external site.) GitHub (Links to an external site.) and (Links to an external site.) Overleaf (Links to an external site.). 

You should bring your laptop or device to class so you can work during our class time. Please speak with me if you encounter any challenges with the technology requirements.

 

Grading

The course grade will be computed as follows::

  • 1/3 - coding practicals
  • 1/3 - project #1 (both group and individual components)
  • 1/3 - project #2 (both group and individual components)

There are no exams.

Prerequisites

Any kind of programming experience is helpful but not required. You should have completed the sequence Physics 341-342, "Principles of Astrophysics" before taking this course; please speak with me if you will be taking 341 at the same time. 

 

Textbook

Johansson 2ed coverFor computational methods in Python, we will use the book Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib (2nd ed.) by Robert Johansson (ISBN 978-1-484242-45-2).
Click here for an earlier version, which includes links to python notebooks. (Links to an external site.)
Click here for more lectures/notebooks from the author. (Links to an external site.)

 

Supplemental resources:

For the astrophysics context and applications, we will use research papers and online resources to be provided. Your textbook from 341 and 342 will also be a valuable resource but is not required. 

Policies

  • Changes: The course schedule and guidelines are subject to change. I will communicate any changes promptly and clearly. Still, it is your responsibility to make yourself aware of any and all changes by attending class and maintaining communication with me.
  • Absences: Students are expected to attend all classes; if you expect to miss one or two classes, please use the University absence reporting website (Links to an external site.) to indicate the date and reason for your absence. An email is automatically sent to me.
    • If you have been told to quarantine, or are experiencing symptoms of any transmittable disease, please do not attend in-person class meetings. Contact me to make arrangements for handling such absences.

 

Resources for student success

The faculty and staff at Rutgers are committed to your success. Students who are successful tend to seek out resources that enable them to excel academically, maintain their health and wellness, prepare for future careers, navigate college life and finances, and connect with the RU community. Helpful resources include the Rutgers Learning Centers (Links to an external site.) and school-based advising (for SAS (Links to an external site.), SOE (Links to an external site.), SEBS (Links to an external site.), and RBS (Links to an external site.)). Additional resources that can help you succeed and connect with the Rutgers community can be found at https://success.rutgers.edu (Links to an external site.).

Please visit the Rutgers Student Tech Guide (Links to an external site.) for resources available to all students. If you do not have the appropriate technology for financial reasons, please email the Dean of Students (deanofstudents@echo.rutgers.edu) for assistance. If you are facing other financial hardships please visit the Office of Financial Aid (Links to an external site.).

 

Academic integrity

Rutgers University takes academic dishonesty very seriously. By enrolling in this course, you assume responsibility for familiarizing yourself with the Academic Integrity Policy (Links to an external site.) and the possible penalties (including suspension and expulsion) for violating the policy. As per the policy, all suspected violations will be reported to the Office of Student Conduct. Academic dishonesty includes (but is not limited to):

  • Cheating
  • Plagiarism
  • Aiding others in committing a violation or allowing others to use your work
  • Failure to cite sources correctly
  • Fabrication
  • Using another person’s ideas or words without attribution–re-using a previous assignment
  • Unauthorized collaboration
  • Sabotaging another student’s work

If in doubt, please consult the instructor. Also review the Academic Integrity Policy (Links to an external site.) and Academic Integrity Resources for Students (Links to an external site.).

Use of external website resources such as Chegg.com or others to obtain solutions to homework assignments, quizzes, or exams is cheating and a violation of the University Academic Integrity policy. Cheating in the course may result in grade penalties, disciplinary sanctions, and/or educational sanctions. Posting homework assignments, or exams, to external sites without the instructor's permission may be a violation of copyright and may constitute the facilitation of dishonesty, which may result in the same penalties as plain cheating. 

Almost all original work is the intellectual property of its authors. This includes not just books and articles, but the syllabi, lectures, lecture slides, recorded lectures, course materials, presentations, homework problems, exams, and other materials used in this course, in either printed or electronic form.  Providing course materials to commercial suppliers such as CourseHero, Chegg, etc. and/or publicly distributing or displaying course materials, or helping others to do so, is a violation of academic integrity. The authors hold copyrights in their works, which are protected by U.S. statutes. Copying this work or posting it online without the permission of the author may violate the author’s rights. More importantly, these works are the product of the author’s efforts; respect for these efforts and for the author’s intellectual property rights is an important value that members of the university community take seriously. For more instructions on copyright protections at Rutgers University, please refer to the Rutgers Libraries (Links to an external site.). 

 

Student Wellness Services

The university provides a number of resources to support your physical and mental well-being. I list several valuable resources here and encourage you to contact me for more guidance about university resources.

 

Course Summary:

Date Details Due