Calling all high school juniors!
We’re proud to announce a new educational service to
accompany last year’s ⛵IS:
Evan’s Chen’s Elite Cutting-Edge College Essay Consulting & Editing Center!
Abbreviated (EC)⁵.
Why trust Evan?
Evan Chen is one of the leading names in admissions to elite American colleges.
Students that Evan has mentored have gone on to prestigious institutions
such as Harvard, Princeton, Stanford — and of course,
MIT, the home of the illuMInaTi.
Evan is so successful at securing spots at selective universities
that nearly 1 in e^pi incoming MIT first-years are
alums of Evan’s programs [[citation needed]][[original research?]].
This is a figure unrivaled in the college prep industry.
Now, for the first time, you can join the ranks of Evan’s superstar students:
(EC)⁵ is the first endeavor led by Evan that doesn’t require any
sort of application or past achievements …
About five years ago I wrote a blog post warning that I thought it
was a bad idea to design math olympiads to be completely untrainable,
because I think math olympiads should be about talent development rather
than just talent identification, yada yada yada.
So now I want to say the other direction: I also don’t want to design
math olympiads so that every problem is 100% required to lie in a
fixed, rigid, and arbitrary boundary prescribed by some
nonexistent syllabus.
From a coach’s perspective, I want to reward “good” studying,
and whatever “good” means, I think it should include more than
zero flexibility and capacity to deal with slight curveballs.
I was reminded of this because there was a recent contest problem
(I won’t say which one to avoid spoilers) that quoted Brianchon’s theorem.
Brianchon’s theorem, for those of you that don’t …
Sometimes I get asked broad advice questions on solving problems, for example
questions like:
How do I know when to switch or prioritize approaches I come up with?
How do I know which points or lines to add in geometry problems?
How can I tell if I’m making progress on a problem?
How can I guess the answer if “find all” or “find min/max” problems?
How can I tell whether a conjecture I made is true or not?
What should I do on a problem when I am stuck?
and so on.
I think all of these questions have a certain quality that, for lack of a better
name, I’ll dub as being “NP-hard”.
This is a bit of abuse of terminology borrowed from
complexity theory,
but let me explain why I think the name fits.
We know that solving math problems is generally difficult.
There’s …
Editorial note: this post was mostly written in February 2023. Any resemblance
to contests after that date is therefore coincidental.
Background
A long time ago, rubrics for the IMO and USAMO were fairly strict. Out of seven,
the overall meta-rubric looks like:
7: Problem solved
6: Tiny slip (and contestant could repair)
5: Small gap or mistake, but non-central
2: Lots of genuine progress
1: Significant non-trivial progress
0: “Busy work”, special cases, lots of writing
In particular, traditional rubrics were often sublinear.
You’d see problems where you could split it into two parts, and solving
either part would only give 2 points, whereas solving both was worth 7.
Increasingly, I’ve noticed this is less and less common.
Particularly, at the IMOAs far as I know, the IMO rubrics aren’t really available anywhere.
(On the other hand, I’ve never been told that rubrics
explicitly need …
Here’s a mix of several publicity-related things I’d like to broadcast.
AlphaGeometry
A lot of you have already heard the buzz about the
AlphaGeometry news
and Nature paper.
(I’ve known about this paper for a while now,
so I’m glad I can finally talk about it!)
I managed to snag a cameo in the DeepMind post where I wrote
AlphaGeometry’s output is impressive because it’s both verifiable and clean.
Past AI solutions to proof-based competition problems have sometimes been
hit-or-miss (outputs are only correct sometimes and need human checks).
AlphaGeometry doesn’t have this weakness: its solutions have
machine-verifiable structure. Yet despite this, its output is still
human-readable. One could have imagined a computer program that solved
geometry problems by brute-force coordinate systems: think pages and pages of
tedious algebra calculation. AlphaGeometry is not that. It uses classical
geometry rules with angles and similar …
Some years ago I published a chart of my ratings of problem difficulty,
using a scale called MOHS.
When I wrote this I had two goals in mind.
One was that I thought the name “MOHS” for a Math Olympiad Hardness Scale
was the best pun of all time,
because there’s a geological scale of mineral hardness that
coincidentally has the same name.
The other was that I thought it would be useful for beginner students,
and coaches, to help find problems that are suitable for practice.
I think it did accomplish those goals.
The problem is that I also inadvertently helped catalyze an endless,
incessant stream of students constantly arguing …
This is a short advertisement announcing that the OTIS Mock AIME 2024 is out.
The short version is that I wanted to give my students a chance to try their hand at problem composition,
which they took enthusiastically, and from their submissions I chose 15 problems to replicate an AIME.
There’s some really nice problems on here (I have some favorites,
but to avoid spoilers for people using this as a practice test, I won’t say which ones yet).
You can check it out here:
I expect a number of students who plan to use this test as practice for the upcoming real AIME,
so I’ve set a “deadline” of January 15 and ask to avoid public discussion of spoilers before then.
I remember when I got the central aha, I justified it to my teammates as
“it’d be so cool, so it has to be right”.
— Nathan Pinsker
This is a post meant to explain what makes puzzle hunts appealing
to people who haven’t done them before.
If you do care about the actual mechanical details,
Brian’s introduction is great.
The one-sentence summary is: you’re (usually) trying to get an English
word/phrase as the final answer, there are (usually) no directions or
instructions, and I write “usually” everywhere because puzzle hunts love
breaking rules.
When I first tell people about puzzle hunts, their initial reaction is usually
that the fun must be in the challenge. And it is not untrue that there is a
notion of skill, and it’s satisfying to become a stronger solver. However, I
think this misses the point: it ignores the …
Note: if you are a prospective OTIS student,
read the syllabus instead. More useful, less bragging.
In the unlikely event that I’m a social gathering like a party or family
gathering, people will sometimes ask me about my teaching.
Invariably they ask, “so do you do like 1:1 meetings or group lessons?”.
Then I have to explain, no, I have 400 students, there are no synchronous meetings at all.
The core of the program is literally a
Python web server that serves PDF files.
Then it sounds less impressive.
I guess when people hear I’m a teacher, they expect me to teach classes,
and it’s a bit embarrassing to explain that I’m not a teacher in that sense anymore.
But the purpose of OTIS isn’t to make Evan sound cool at parties;
the purpose of OTIS to be effective for the students.
So this …
This was originally a diary entry, but I showed it to some students
who told me I should put it in my blog instead.
Imagine you’ve moved to a new town, and want to explore the local offerings,
because there’s a lot to do and see, and you’re expecting to live here a while.
The first few days, it’s really overwhelming. Everything is unfamiliar. You get
lost just trying to buy groceries. You constantly have to consult maps to get
anywhere. It takes a while to adjust.
But after the first week, you notice you don’t need a map as much. You can walk
to the grocery store yourself; you remember which turn to take each crossing.
You know the names of the biggest streets and a few landmarks, and you can get
around with familiar roads as anchors. Though you’ve only been inside …