# 18.225 Graph Theory and Additive Combinatorics

Quick links: [Class files on Dropbox] [Canvas]

Class meetings: Mondays and Wednesdays 2:30–4pm, room 4-153

Instructor: Prof. Yufei Zhao

Emails and Piazza

• My policy is to not answer by email any math questions related to the class, due to time constraints and also that emails are not a great medium for such Q&As (ask them during office hours instead).
• Clarification questions (about homework or lectures) should be asked on Piazza (link in Canvas), as they may benefit the rest of the class. The same goes for other discussions of general interest. Do not discuss hints or solutions to homework problems on Piazza until after the latest possible submission time after due date.
• Email the lead grader and cc me if it is homework related (submission, extensions, grading, etc.)
• Begin your email subject line with “[18.225]”

Office hours

• Instead of holding regular office hours, I will stay around after class to answer questions – we may move to the math common room (2-290).
• I plan to also schedule ad-hoc office hours for each problem set. Stay tuned for Canvas announcements.
• You may ask me about unstarred problems (but not starred ones) during office hours. I will ask you to first explain on the board the progress you have made so far.

Course files: Dropbox folder. Will be updated throughout the term.

• Lectures outline
• Problem sets
• Book draft

## Course description

The course examines classical and modern developments in graph theory and additive combinatorics, with a focus on topics and themes that connect the two subjects. The course also introduces students to current research topics and open problems.

A foundational result in additive combinatorics is Roth’s theorem, which says that every subset of {1, 2, …, n} without a 3-term arithmetic progression contains o(N) elements. We will see a couple of different proofs of Roth’s theorem: (1) a graph theoretic approach and (2) Roth’s original Fourier analytic approach. A central idea in both approaches is the dichotomy of structure versus pseudorandomness, and it is one of the key themes of the course.

Roth’s theorem laid the groundwork for many important later developments, e.g.,

• Szemerédi’s theorem. Every set of integers of positive density contains arbitrarily long arithmetic progressions;
• Green–Tao theorem. The primes contain arbitrarily long arithmetic progressions.

The course will explore these and related topics, including:

• Extremal graph theory. What is the maximum number of edges in a triangle-free graph on n vertices? What if instead we forbid cycles of length 4? At most how many edges can an n-vertex graph have if every edge is contained in exactly one triangle?
• Szemerédi’s regularity lemma. A powerful tool in combinatorics that provides an approximate description/decomposition for every large graph.
• Pseudorandom graphs. What does it mean for some graph to resemble a random graph?
• Graph limits. In what sense can a sequence of graphs, increasing in size, converge to some limit object?
• Fourier analysis in additive combinatorics. An important technique for studying combinatorial properties in arithmetic settings, e.g., in the proof of Roth’s theorem.
• Freiman’s theorem and the structure of sum sets. What can one say about sets A such that the sum set $A + A = \{a + a' : a,a' \in A\}$ is small?
• Sum-product phenomenon. Can a set A simultaneously have both small sum set $A + A$ and product set $A \cdot A$?

Although the course will be largely divided into two parts (graph theory in the first half and additive combinatorics in the second), we will emphasize the interactions between the two topics and highlight the common themes.

Lecture video recordings from Fall 2019 (may not correspond exactly to the current semester) may be found on MIT OpenCourseWare and YouTube.

### Prerequisites

Mathematical maturity at the level of a first-year math graduate student. Comfortable with undergraduate real analysis (18.100) and algebra (18.701/3).

• 90% based on problem sets
• Only non-starred problems are considered for the calculations of letter grades other than A and A+
• 10% based on (graded holistically at the end of term and can be used for deciding borderline grades)

• A− : ≥ 85%
• B− : ≥ 70%
• C− : ≥ 50%

Grades of A and A+ are awarded at my discretion based on overall performance. Solving a significant number of starred problems is a requirement for grades of A and A+ (please don’t ask me what “a significant number” means). Note that for MIT students, ± grade modifiers do not count towards the GPA and do not appear on the external transcript.

Students needing support should consider reaching out to Student Support Services (S3), GradSupport, or Student Disability Services.

## Problem sets

See Dropbox folder for the problem set. It will be updated over the course of the semester. I will announce on Canvas when each problem set is complete.

You should only submit the designated problems, but are encouraged to try the rest as well.

Starred problems are generally more challenging.

To get the most out of this course, you are expected to spend a significant amount of time solving these problems. It will be essential to start thinking about these problems early.

### Schedule

Problem set Due date
PS 1 Sun Sep 26
PS 2 Sun Oct 10
PS 3 Sun Oct 24
PS 4 Sun Nov 7
PS 5 Sun Nov 21
PS 6 Sun Dec 5

Starred problems on each problem set should be submitted separately, with an automatic 7-day extension without penalty (and no additional extensions permitted).

### Submissions

• Must be typed in LaTeX and submitted as PDF on Gradescope (accessed from Canvas).
• Due time: 11:59pm of each due date
• Begin each solution on a new page
• Each box on the left-margin of the problem set PDF indicates a single problem worth 10 points

### Late policy

• Penalty. Late submissions will be penalized by 20% per each late day (24-hour increments, without fractional accounting).
• Example: for an assignment due on Sunday, a submission worth x points if turned in on time will be worth 0.6x points if submitted on Tuesday.
• Multiple submissions. You are allowed to submit some of the problems on time and some of the problems in a separate “late” batch and have the late penalty applied only to the late batch.
• You are allowed to submit at most two batches (i.e., 1 ontime + 1 late batch, or 2 separate late batches)
• The second batch may not contain any updates or replacement to an already submitted problem.
• The final submission should include everything, with the late problems clearly marked as “late” in the PDF.
• Please email the lead grader if you submit in two batches, with details on which problems are submitted in which batch, as multiple submissions complicate our grading process.
• This policy is provided as a courtesy; it may be rescinded if abused.
• Extensions. If you need an extension for valid excuses (e.g., unanticipated health or family issues), please email the lead grader and me in advance or have S3 send us a message. Let us know how many days extension you would need.
• My policy is to not grant extension based on forseeable circumstances including other academic workload, extracurriculars, and poor study habits.

### Collaborations

• You are encouraged to first work on the homework problems independently before seeking collaboration.
• Meaningful collaboration is allowed if it helps with your learning (e.g., solving a problem together)
• Unacceptable practices include: “dividing up” the problems among a group and then distributing the solutions; asking for a solution from a friend.
• You must write up your own solutions.
• Pset partners — a tool for finding problem set collaborators (MIT Touchstone required)

### Acknowledging collaborators and sources

It is required to acknowledge your sources (even if you worked independently)

• At the beginning of the submission for each problem, write Collaborators and sources: followed by a list of collaborators and sources consulted (people, books, papers, websites, software, etc.), or write none if you did not use any such resources.
• Failure to acknowledge will result in an automatic 1pt penalty per problem.
• Acceptable uses of resources include: looking up a standard theorem/formula/technique; using Wolfram Alpha/Mathematica/Python for a calculation (no need to mention lectures or book draft)
• Unacceptable uses of resources include: directly looking up the problem online or in the research literature for a solution. (Once you have solved a problem, it is fine to seek and learn alternate solutions.)

Intentional violations of the above policies may be considered academic dishonesty/misconduct.

## Book draft

I am in the process of editing and rewriting the course notes from Fall 2019 into a textbook. I will be updating the book draft in the Dropbox folder as the semester progresses. Check there for the latest available version. This book draft will also serve as course notes.

The book is still very much in an unfinished state, especially in the later sections.

The numberings (sections, theorems, etc.) in the book draft are unstable. When quoting theorems for homework, please include the statement or a description of the result rather than simply the theorem number.

Your feedback on the book draft is appreciated. Please help me find errors (both of the English and math kind). Also point out places where the exposition is unclear. Suggestions are welcome. Please post your comments in Piazza in the “book” folder. Your active participation in giving feedback on the book draft contributes to the 10% of the grade as discussed in the grading scheme.

## Wikipedia assignment

Wikipedia is often the first landing page for students (and even researchers) when looking to learn about a new concept. Unfortunately, many of topics in combinatorics are poorly represented on Wikipedia.

Your assignment: pick some topic related to this course (even tangentially related is okay) where the Wikipedia page is either non-existent or has room for substantial improvements. Edit Wikipedia to make it better.

Tutorial: editing Wikipedia

You are asked to do more than simply editing. This is a literature research and expository writing assignment. It is your job to look up and learn a topic and then distill the most important information in the format of a Wikipedia article.

How to select a topic:

• Hear a concept you don’t know? What happens if you Google keywords related to the topic? Is there a Wikipedia page? Is it actually helpful?
• Go for general concepts of wide interest and applicability.
• Avoid overly specialized topics (e.g., some specific recent research result). They are unsuitable for Wikipedia.
• Make sure that any new article satisfies the Wikipedia notability criteria, to avoid risk of article deletion.
• Do not ask me for suggestions. Part of your job is to find a good topic. Use your experience to judge what makes a good Wikipedia article.

Some components of a good Wikipedia article:

• A useful blurb at the beginning of each article, conveying the concept to an appropriately general audience;
• Precisely stated definitions and theorems, if suitable;
• Discussions of history, context, bounds, etc;
• Explanations, examples, counterexamples, figures;
• Short proofs;
• References pointing to additional resources;
• Not a simply a laundry list;
• Not a textbook or a research journal (don’t just copy theorems and proofs onto there).

We will do this assignment in several stages, mimicking a double-blind review process.

Everyone should contribute individually (not working in groups).

For this assignment, use “private” post on Piazza (your name hidden to other students but visible to me) in the folder wiki.

### Stage I - proposal (due Sat Nov 13)

• Post on Piazza, with post title [Wiki] Your topic, your proposed page to add/edit on Wikipedia.
• You may claim either an entire Wikipedia page (new or existing) or a substantial section (or multiple sections) of an existing Wikipedia page.
• If there is an existing page, add a link to both the most current page as well as a link to the current frozen version from its “View history”.
• Explain why this page needs to be added/edited, and what you propose to do. For new pages, briefly make a case for notability.
• Other students are welcome to comment on the proposals, or suggest additional content to add to the topic.
• Based on the comments or other considerations, you may decide to revise your topic at a later point in the process.
• Topics are chosen first-come first-serve by Piazza posting (though you may discuss through anonymous comments if you feel that a task is big enough to warrant splitting into multiple well defined tasks).

### Stage II - initial edit (due Sat Nov 27)

• Revise your initial Piazza post with a summary of your changes.
• Mention in your Piazza summary what resources you have found useful / drawn from for this assignment (this should be more than lectures / GTAC book)

### Stage III - peer review and comments (due Sat Dec 4)

• Provide substantive and constructive feedback to other students’ Wikipedia edits.
• Suggest improvements, e.g., what to add/delete/revise.
• Every student needs to respond to at least three posts. (More is fine.)
• Every post needs to have at least three responses. (More is fine.) It is each student’s responsibility to solicit more responses if they do not have at least three.
• Use best effort to preserve double-blind anonymity throughout this process (it won’t be perfect, but do your best)

### Stage IV - revision (due Wed Dec 8)

Please edit your initial Piazza post for all the stages rather than creating new ones (one post per student).

Use bold section headers (Stage I, II, IV) to clearly separate different parts of your post.

## References

Additional references for material covered in the course

Extremal graph theory

Pseudorandom graphs and graph limits