mathlib
lean4
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mathlib | lean4 | |
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36 | 52 | |
1,619 | 3,608 | |
0.2% | 4.6% | |
9.3 | 9.9 | |
4 days ago | 7 days ago | |
Lean | Lean | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
mathlib
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Lean 4.0.0, first official lean4 release
Kinda agree but Mathlib and its documentation makes for a big corpus to learn by example from. Not ideal but it helps.
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If given a list of properties/definitions and relationship between them, could a machine come up with (mostly senseless, but) true implications?
Still, there are many useful tools based on these ideas, used by programmers and mathematicians alike. What you describe sounds rather like Datalog (e.g. Soufflé Datalog), where you supply some rules and an initial fact, and the system repeatedly expands out the set of facts until nothing new can be derived. (This has to be finite, if you want to get anywhere.) In Prolog (e.g. SWI Prolog) you also supply a set of rules and facts, but instead of a fact as your starting point, you give a query containing some unknown variables, and the system tries to find an assignment of the variables that proves the query. And finally there is a rich array of theorem provers and proof assistants such as Agda, Coq, Lean, and Twelf, which can all be used to help check your reasoning or explore new ideas.
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Will Computers Redefine the Roots of Math?
For the math that you mention, I would suggest looking at mathlib (https://github.com/leanprover-community/mathlib). I agree that the foundations of Coq are somewhat distanced from the foundations most mathematicians are trained in. Lean/mathlib might be a bit more familiar, not sure. That said, I don't see any obstacles to developing classical real analysis or linear algebra in Coq, once you've gotten used to writing proofs in it.
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Which proof assistant is the best to formalize real analysis/probability/statistics?
At this point I would go with Lean because of mathlib. Mathlib's goal is to formalize modern mathematics, so many of the theorems you would need for analysis should already be there for you.
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Is there a paid service where someone can explain a paper to me like I am 15?
It's been around since 2013, although there are LLM that interact with Lean to do automated theorem proving. Anyway, you can learn more about Lean here. I enjoyed their natural numbers game (which reminds, me I should finish the last two levels)
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Lean – Theorem Prover
I think they end up similar. Although Lean 3 is much more geared towards writing proofs with the addition of mathlib [0] which aims to be a library of formalized mathematics.
- The Mathematical Hacker
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Thoughts on proof assistants?
Check out Lean (https://leanprover-community.github.io/) if you want a theorem prover with a strong mathematics community. Or if you don't, Lean is cool.
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Mathics: A free, open-source alternative to Mathematica
Check out https://github.com/leanprover-community/mathlib . Sure, it's not really a CAS but CAS algorithms could be added to it where applicable, since Lean is a constructive system and can thus express formally verified computations.
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Principia Mathematica in modern notation.
If you're really interested in formalization of mathematics, there's a lot to do otherwise. I think there's lots of work to do on Mathlib that you don't need a PhD to do, just programming experience and bachelors-level math knowledge.
lean4
- The Mechanics of Proof
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The Wizardry Frontier
Nice read! Rust has pushed, and will continue to push, the limits of practical, bare metal, memory safe languages. And it's interesting to think about what's next, maybe eventually there will be some form of practical theorem proving "for the masses". Lean 4 looks great and has potential, but it's still mostly a language for mathematicians. There has been some research on AI constructed proofs, which could be the best of both worlds because then the type checker can verify that the AI generated code/proof is indeed correct. Tools like Kani are also a step forward in program correctness.
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Lean4 helped Terence Tao discover a small bug in his recent paper
Yeah, I believe they said intend for it to be used as a general purpose programming language. I used it to complete Advent of Code last year.
There are some really interesting features for general purpose programming in there. For example: you can code updates to arrays in a functional style (change a value, get a new array back), but if the refcount is 1, it updates in place. This works for inductive types and structures, too. So I was able to efficiently use C-style arrays (O(1) update/lookup) while writing functional code. (paper: https://arxiv.org/abs/1908.05647 )
Another interesting feature is that the "do" blocks include mutable variables and for loops (with continue / break / return), that gets compiled down to monad operations. (paper: https://dl.acm.org/doi/10.1145/3547640 )
And I'm impressed that you can add to the syntax of the language, in the same way that the language is implemented, and then use that syntax in the next line of code. (paper: https://lmcs.episciences.org/9362/pdf ). There is an example in the source repository that adds and then uses a JSX-like syntax. (https://github.com/leanprover/lean4/blob/master/tests/playgr... )
- A Linguagem Lua completa 30 anos!
- Lean 4.0.0, first official lean4 release
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Looking to start a new community for people who want to use code for everything
My latest inspiration to use code to a) replace my video editor, b) learn the basics of EDM production and c) understand a few topics in higher maths. This might sound very strange given there are specialised tools for these jobs. There's iMovie / Adobe Premier for video, there's GarageBand and FL studio for music and old good pen and pencil for math proofs. But these tools have three big limitations. First they have a lot of idiosyncratic learning, you have to spend quite some time getting used to these tools and my experience is that this time is quite upsetting. In contrast, you only have to learn to code one, maybe spend a few hours getting used to the syntax of another language. I'm not sure if that's true for most people but it was true for me using the tools mentioned above and wanted a place to discuss and see other people ideas and experiments. The second issue is that all these custom-made tools, are not composing easily. I can't search for all math proofs that used a single theorem. I can't create a plugin for iMovie and apply it to all my videos. I can't pick easily pick a rhythm from the internet and build upon for fun. There's also the issue of costs and version control, all tools I'm using today are open source and my work is stored in my repositories. This way I can create branches and test my ideas and I'm also confident that I can work in these projects in years.
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In Which I Claim Rich Hickey Is Wrong
Dafny and Whiley are two examples with explicit verification support. Idris and other dependently typed languages should all be rich enough to express the required predicate but might not necessarily be able to accept a reasonable implementation as proof. Isabelle, Lean, Coq, and other theorem provers definitely can express the capability but aren't going to churn out much in the way of executable programs; they're more useful to guide an implementation in a more practical functional language but then the proof is separated from the implementation, and you could also use tools like TLA+.
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Macro-ts: TypeScript compiler with typesafe syntactic macros (2022)
Lean4 manages to pull off changing the parser on the fly at compile time. You can add new productions, add new syntax node types, and add new tokens. Then define macros or code to process the additional syntax. Here is a sample I found that adds a simple JSX-like syntax starting around line 93 and then uses it at line 169:
https://github.com/leanprover/lean4/blob/master/tests/playgr...
I believe most of the language is defined this way, although it is pre-compiled.
For more details see the lean4 metaprogramming book: https://github.com/arthurpaulino/lean4-metaprogramming-book
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is dependent haskell still a thing?
Lean is another alternative. Very fast, built by Microsoft. Dependent types, proof tactics, type classes, monads, nice macro system.
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What are the current hot topics in type theory and static analysis?
Most of the proof assistants out there: Lean, Coq, Dafny, Isabelle, F*, Idris 2, and Agda. And the main concepts are dependent types, Homotopy Type Theory AKA HoTT, and Category Theory. Warning: HoTT and Category Theory are really dense, you're going to really need to research them.
What are some alternatives?
z3_tutorial - Jupyter notebooks for tutorial on the Z3 SMT solver
coq - Coq is a formal proof management system. It provides a formal language to write mathematical definitions, executable algorithms and theorems together with an environment for semi-interactive development of machine-checked proofs.
Agda - Agda is a dependently typed programming language / interactive theorem prover.
ATS-Postiats - ATS2: Unleashing the Potentials of Types and Templates
ts-sql - A SQL database implemented purely in TypeScript type annotations.
Coq-Equations - A function definition package for Coq
roc - A fast, friendly, functional language. Work in progress!
mathquill - Easily type math in your webapp
oil - Oils is our upgrade path from bash to a better language and runtime. It's also for Python and JavaScript users who avoid shell!
typeshed - Collection of library stubs for Python, with static types
lean-liquid - 💧 Liquid Tensor Experiment