Department of Computer Science
The University of Texas at Austin
CS 309 - Geometry of Space - FRI (Spring 2025)
Section: 50595, TTH 3:30 PM - 5:00 PM, WEL 3.320
Instructor: Dr. Shyamal Mitra
Office Hours: by appointment
Location: Zoom
E-mail: mitra@cs.utexas.edu
Do not send mail on Canvas.
Overview of CS 309
Welcome to CS 309. This is an intensive research course that spans one year.
Our program aims to produce original research that we can publish.
Here are our core beliefs:
- We believe in self-directed learning. You will be responsible for crafting
a research question and executing the research.
- We are grounded in reality. We work with actual observational data from
professional astronomical databases.
- We believe in contributing to science by publishing our research in
professional journals.
- We aim to build a strong community because successful research is a result
of teamwork.
- We want to enjoy the process as we learn together.
Take this course if you share our values!
Scope of the Course
Our FRI stream is a two-semester research sequence that is designed to be
hands-on, engaging, and intense. In the first semester (spring 2025), we will
cover the foundational knowledge you need in astronomy, programming, and data
science, with a focus on practical applications. In summer, we will meet
virtually once a week. There will be reading assignments that we will discuss
and online courses that we will complete, all geared toward research in
computational astrophysics. In the second semester (fall 2025), you will
formulate a research problem, review the work that has already been done,
design a research plan, and then execute that plan. The end goal will be a
paper you will present in class and submit for publication to contribute to
scientific research.
Research Goal
In this research stream, we will embark on a journey to understand the large
scale structure of the universe. We will achieve this by studying the
distribution of galaxies and clusters of galaxies, using algorithms developed
in computational geometry and applying techniques in data analytics. Our data
will be sourced from highly credible professional databases such as the Sloan
Digital Sky Survey (SDSS), NASA Extragalactic Database (NED), and others,
ensuring the credibility and trustworthiness of our research.
We will use computational geometry to obtain the size and center of clusters
of galaxies and data analytics to determine member galaxies and outliers. We
will compute the velocity dispersion of the clusters and their mass-to-light
ratio. Specifically, one of the questions that we will try to answer is: Are
there interconnections between clusters, and are the clusters themselves
clustered to form superclusters? We will provide three-dimensional maps of
the distribution of galaxies.
Our research will also explore other significant questions related to quasars,
active galaxies, star clusters, and variable stars. We will apply machine
learning models and statistical methods to extract knowledge from raw data
and information. Importantly, we will use real data throughout our research,
ensuring the authenticity and reliability of our findings.
Hybrid Lectures
Our lectures will be either in-person or delivered online on Zoom in
Canvas. You will be given advanced notifications on what mode the
lectures will be delivered. Attendance to the in-person lectures is
mandatory. The online lectures will be recorded. The class recordings
are confidential to the class and are only for educational purposes.
The recordings must not be shared in any form. Any dissemination of
the recordings is a violation of the University policies and will be
subject to Student Misconduct proceedings through the Office of Student
Conduct and Academic Integrity. Our office hours will not be
recorded.
Learning Outcomes
At the conclusion of this course, students will be able to:
- describe the scientific method and apply it in the context of computational
astrophysics
- explain some of the basic concepts in astronomy and apply them to numerical
problems
- analyze a computational problem, design an algorithm, and then code the
algorithm in Python
- apply the tools in data science such as Jupyter Notebook, NumPy, SciPy,
Pandas, and Matplotlib to computational problems in astrophysics
- write in a style suitable for publication in a scientific journal
Research Journal
You will be maintaining a research journal where you record the work
that you did that week. You will note what you accomplished that week,
the problems that you encountered, the work that you plan to do the
following week, and any other issues that you would like to discuss.
All journal entries will be due on Sundays on Canvas for the whole
year.
Quizzes
Quizzes will be held on every lecture day. These short quizzes will be based
on your readings and the previous days' lecture material. Your lowest quiz
score will be dropped, providing you with some flexibility in managing your
study time.
Tests
There will be two tests - a midterm (Thursday, 13 Mar 2025) and a final
(Thursday, 24 Apr 2025). The midterm and final will be in class, and the
final will be comprehensive. Both tests will have short answer questions
in astronomy and programming.
Online Courses
Our research stream spans multiple disciplines, including astronomy, computer
science, data science, mathematics, and physics. To ensure a comprehensive
understanding, we will supplement our course materials with online courses
from Coursera and LinkedIn Learning. You will be assigned specific units to
complete, with deadlines to keep you on track. Please note that there will be
a late penalty for missed deadlines.
Assignments
There will be programming assignments in Python and in data science
using Jupyter notebooks. You will also have assignments in astronomy
using the sources of data as mentioned above as well as other sources
of online data. These assignments will have deadlines with late penalty
for missed deadlines.
Grades
Your performance in this class will be evaluated using your scores for the
journal entries that you record, the quizzes we conduct in class, the two
tests that you take, the online courses that you complete, and the assignments
that you work on. The weights of each of these components are listed below.
There are no extra credit projects or assignments to improve your grade.
Other than the quiz scores, we do not drop any of the scores to compute
the weighted average.
- Journal Entry: 15%
- Quizzes: 15%
- Tests (Midterm and Final): 30%
- Online Courses: 20%
- Assignments: 20%
All scores will be entered on Canvas. Check your scores regularly on
Canvas to make sure that we have entered them correctly. Remember the
average score as shown on Canvas is not correct. It does not
weight the average with weights as shown above. Your final grade will
be assigned after we obtain the weighted average according to the weights
as given above. Your grade will be based on the traditional scheme:
- A: 90 - 100
- B: 80 - 89
- C: 70 - 79
- D: 60 - 69
- F: 0 - 59
We do assign grades on the +/- system. But those finer cutoffs will be
determined at the very end after the weighted average and standard
deviation of the class are computed.
Class Responsibilities
- Each lecture day, you will have the chance to sit with a different group
of your peers. This is a unique opportunity to build relationships and get to
know everyone in our class community.
- Each assignment will be a collaborative effort, as you will work with a
different partner each time. By the end of the semester, you will have engaged
with and learned from a variety of your peers, preparing you for the research
project.
- For class-related questions, we will use EdDiscussion, integrated into
Canvas. Our peer mentors will be there to guide and support you. For more
informal discussions, you will use Discord, where we expect your posts to be
professional and respectful to all members of our class community.
- You will determine your performance in this class! It will require a
strong dedication to learning the material and a substantial time commitment
to complete all the readings and assignments.
- Your presence is crucial. You are expected to attend all class meetings
on time and stay for the whole class period. Your time is valuable, and we
respect that.You are required to have your cell phones off at all times during
the class. You may not make or receive calls on your cell phone or send or
receive text messages during class.
- You are responsible for all material posted to the website and sent as
an email. Ignorance of such material is no excuse.
- You are responsible for all material presented in the class, and your
reading of online resources.
- We hold honesty in high regard. We expect scrupulous honesty in all the
work that you do. Your integrity is a key part of your academic journey.
- Your conduct in class should always contribute to a positive learning
environment for your classmates and yourself.
University Time Table
- 13 Jan 2025: First day of class
- 16 Jan 2025: Last day of official add / drop
- 29 Jan 2025: 12th class day, official enrollment count is
taken
- 17 Mar - 22 Mar 2025: Spring Break
- 16 Apr 2025: Last day to drop (with dean's approval) except for urgent
and substantiated, non-academic reasons or to change to or from
pass/fail basis.
- 28 Apr 2025: Last class day
Policy on Generative AI
If your laptop could think, we would call it a thinker. It cannot think; it
can compute. Therefore, we call it a computer. The computer is an excellent
tool for problem-solving, but it is important to remember that it is us, not
the computer, that ultimately solves the problem. The computer handles the
grunge work, leaving the thinking to us.
Generative AI is a tool that is here to stay. It is designed to assist in
our thinking processes, not to replace them. The danger lies in over-reliance,
in believing that Generative AI can think for us. It is important to use this
tool with caution, without sacrificing our good thinking habits. Remember, AI
can be a powerful ally, but it is not a substitute for our critical thinking
skills.
Our stance on Generative AI use is neutral. Whether you choose to incorporate
it into your work or not, your decision is respected. There are no penalties
or restrictions associated with its use. However, we strongly advocate for the
responsible use of Generative AI and the preservation of your critical thinking
skills. We are interested to hear about your experiences with Generative AI
in your work.
General Policies
If you are absent from class for the observance of a religious holy day
you may turn in your assignment or paper on an alternate date provided
you have given me written notice fourteen days prior to the class absence.
For religious holy days that fall within the first two weeks of class
notice must be given on the first class day.
Students with disabilities who need special accommodations should contact
the Services for Students with Disabilities (SSD) Office (471-6259 or
471-4641 TTY).
These are the
University Policies and Resources for Students.