explaingit

evand/open-math-problems

Analysis updated 2026-05-18

3PythonAudience · researcherComplexity · 1/5Setup · easy

TLDR

A curated tier list ranking famous unsolved math problems by structural importance, with links to explanations, formal proofs, and prediction markets.

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What do people build with it?

USE CASE 1

Browse a ranked overview of the most important unsolved problems in mathematics.

USE CASE 2

Find prediction market odds on whether and when a specific open problem will be solved.

USE CASE 3

Look up a formal Lean 4 statement of a famous conjecture.

USE CASE 4

Contribute a pull request adding a missing market link or formalization to the list.

What is it built with?

PythonLean 4

How does it compare?

evand/open-math-problems0marildo/imago0xdfi/glm-5.2-1m-4x-dgx-spark
Stars333
LanguagePythonPythonPython
Setup difficultyeasyeasyhard
Complexity1/52/55/5
Audienceresearchergeneralresearcher

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · easy Time to first run · 5min

It is a reference document, not a runnable tool, so there is nothing to install.

In plain English

This project is a tier list that ranks the famous unsolved problems in mathematics, from the Riemann Hypothesis down to lesser known open questions. Instead of ranking by fame or raw difficulty, entries are ranked by how central they are to the structure of mathematics and how much a proof would change the field, with fame only used to break ties. That is why some very well known problems land lower than you might expect. Each entry in the tier list can include a link to a Wikipedia or arXiv article explaining the problem, a formal statement of the problem written in the Lean 4 proof language, usually pulled from Google DeepMind's formal conjectures project, and links to prediction markets on sites like Manifold and Metaculus where people bet on whether and when the problem will be solved. Those market odds are described as snapshots from a specific point in time that will shift as more information comes in. The list is organized into tiers, starting with S tier for problems described as load bearing pillars of mathematics, such as the Riemann Hypothesis, P versus NP, and the Langlands program, followed by an A tier of field defining problems including the Birch and Swinnerton-Dyer conjecture, the Hodge conjecture, and Navier-Stokes global regularity. The project also keeps a section tracking problems that have recently been solved or partially solved, used as a calibration check for the rest of the list. The README itself is the primary content here rather than runnable code, and the repository is open to contributions through pull requests, especially for adding prediction markets or formalizations that exist but are not yet linked. The full README is longer than what was shown.

Copy-paste prompts

Prompt 1
Explain the Riemann Hypothesis to me the way this project's S tier entry describes it.
Prompt 2
Walk me through why this tier list ranks problems by structural centrality instead of fame.
Prompt 3
Show me how to find the Lean 4 formal statement for a specific conjecture linked in this list.
Prompt 4
Help me understand what the Manifold prediction market links in this repo actually measure.

Frequently asked questions

What is open-math-problems?

A curated tier list ranking famous unsolved math problems by structural importance, with links to explanations, formal proofs, and prediction markets.

What language is open-math-problems written in?

Mainly Python. The stack also includes Python, Lean 4.

How hard is open-math-problems to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is open-math-problems for?

Mainly researcher.

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