Instructor: Dr. Aleksandra Kuznetsova (CUNY GC; Center for Computational Astrophysics, Flatiron Institute)
Email: akuznetsova@flatironinstitute.org
Class meets: Mondays and Wednesdays 2:00PM-3:45PM at the Graduate Center Campus
Office Hours: Thursdays 10:00am-11:30am CCA 11th floor
Course Website: https://github.com/akuznetsova/spf-2024
In this course, we will lay the foundation for our current understanding of star and planet formation, from physical processes in the interstellar medium on giant molecular cloud scales down to the assembly of planets. We will discuss how observational evidence informs the theoretical picture of how stars and planets are born in our Galaxy, learn how to construct basic models of planet-forming environments, and survey open questions in the field.
Introduction to the Interstellar Medium, by Jonathan Williams
ISBN: 9781108691178
Course textbook (recommended): excellent reference for material in the first > half of the course. This book has a companion website that hosts the data and code behind the figures
Accretion Processes in Star Formation 2nd Ed., by Lee Hartmann
ISBN: 9780511552090
Textbook (v. optional): an overarching review of relevant literature spanning many of the topics covered in this course
Physics of the Interstellar and Intergalactic Medium by Bruce T. Draine.
ISBN: 9780691122144
Textbook (v. optional): An incredibly thorough review of microphysical processes and radiative transfer in the interstellar medium. I won't be teaching out of this book, but it can be very useful as a technical reference for future career astronomers.
(Tentative): Exact timing subject to change. This is a live syllabus which will be updated throughout the course.
Week 1 - Jan 29, Jan 31
Week 2 - Feb 5, Feb 7
Week 3 - Feb 14
Multi-phase magic: Star Formation in the Wild with the Orion Complex
Week 4 - Feb 21
Week 5 - Feb 26, Feb 28
Population level star formation metrics
Week 6 - Mar 4, Mar 6
Week 7 - Mar 11, Mar 13
Week 8 - Mar 18, Mar 20
Week 9: (prep for) + Midterm - Mar 25, Mar 27
Week 10 - Apr 1, Apr 3
Week 11 - Apr 8, Apr 10
Week 12 - Apr 15, Apr 17
Week 13 - May 1
Week 14 - May 6, May 8
Week 15 - May 13, May 15
Finals Week - Final projects due
This is a graduate course for early career scientists. In addition to content knowledge, we will be working on building and reinforcing the skills that constitute scientific practice. As part of that you can expect to be asked to use outside sources, engage with the literature, practice technical and programming skills, work collaboratively, and synthesize and communicate information to your colleagues. Most of the course materials and resources will be hosted on this github repository. As part of the course, you will be made collaborators and asked to upload to this repository and contribute to shared resources (such as the class recaps and annotated bibliography).
The grading for the course will be somewhat non-traditional, rather than relying strictly on a weighted average of required assignments, grades will be assigned based on a total accrued amount of points across categories:
| category | points |
|---|---|
| Homework | 60 |
| Menu | 15 |
| Midterm | 10 |
| Final | 15 |
| Total | 100 |
where ranges for passing grades are as follows:
A-/A/A+: [88-92-96-100+), B-/B/B+: [76-80-84-88), C-/C/C+: [64-68-72-76)
Required weekly assignments e.g. problem sets and computational assignments, typically due by EOD on Fridays. Will provide ~4 total points each week.
Assignments on the menu each week provide multiple options to earn toward your grade total (or can be used to supplement points from other categories) -- you can think of this as a slush pile of points up for grabs. These may be turned in any time, but for steady progression, I would highly recommend to aim for ~ 1pt/week. The menu category is meant to award credit for engaging with the course content and generally doing the kinds of activities that comprise "learning" that you may have been doing anyway. Point values are provided as expected ranges for good faith contributions, awarded values are at instructor discretion. Students may choose from the standard menu options below in addition to any weekly 'specials'.
The Standard Menu
Class Recap (1 pt)
For each class, a student will be assigned to produce a class recap, due before the start of the next class, uploaded to the directory for that week in markdown format (templates and instructions are found in the weekly folders). Completing this assignment is worth the week's worth of menu points (and contributes to a valuable communal resource!) If something comes up, please arrange for a classmate to take over the duty before the deadline.
Resource Contribution (~0.1-0.5 pts / contribution)
Did you find a link to a useful set of online lecture notes that relate to the class material? Do you have an analogy, conceptual explanation, or example for a topic discussed in class or find an online resource that helped you better understand a concept? Do you have a question that you haven't been able to find an answer for (or an answer to one you see)? Any of these are fair game submissions to get credit as resource contributions (and are a great way to share resources with your colleagues).
You can add links/notes/questions/images directly to where they would be relevant in the week's recap or upload pdfs/images to the week's folder and link them in the Resources section of the week's recap with a short description. These can even be added to a folder from a prior week.
To be eligible for points, contributions should be committed with a commit message title "CONTRIBUTION - [NAME]" with a brief commit description that states the relevance of the contribution to the material.
Annotated Bibliography (~ 0.5 pts / paper)
Add a paper to the class annotated bibliography. If you read a paper relevant to the course material in this class, add an ads link to the abstract, a paragraph or two summarizing the paper's message, any insights you have, and its relevance to the course material (template provided here).
To be eligible for points, uploads should be committed with a commit message title "BIB CONTRIBUTION - [NAME]" with a brief commit description of topic keywords. You are welcome to split the work and credit with a classmate, simply put multiple names in the commit title so that total points can be split between contributors.
Homework Reflection (1/2-full pts back)
Making mistakes is part of learning. If you would like to earn points back on a homework, you may re-submit the corrected assignment with a reflection component. The reflection should address the source of the initial error and the reasoning for the revised solution. Reflections may be submitted in written form with the resubmission or as a discussion during office hours/by appt. By its nature, this is easier to complete sooner rather than later.
The midterm consists of a contribution to a class project contextualizing observations of star formation across Galactic scales and environment. The midterm will take place at the conclusion of Part I in class on Mar 27.
(9pts) Each student will be responsible for the presentation of their individual contribution and participation in the discussion on the day of the midterm.
(1 pt) Attend a brief meeting with the instructor to cross-check grade records and provide/receive feedback on course progression.
Midterm Instructions
For the final, students have the choice of (1) a longer form research project with a modeling component or (2) a one hour oral final exam. By X date, students will have submitted their pitches for the final project topic or scheduled a date/time for the final examination.
The structure of this course is meant to provide transparency and flexiblity for you as the student, giving you the tools to earn your grade and multiple pathways by which to demonstrate your learning. While this is meant to give you some room to sustainably pace yourself through the course without formally incurring penalties, at the end of the day, you are also responsible for your learning and learning generally doesn't happen without putting in the work. You know yourself best -- make good choices.