rssn: A Comprehensive Scientific Computing Library for Rust

rssn is an open-source scientific computing library for Rust, combining symbolic computation, numerical methods, and physics simulations in a single ecosystem.
It is designed to provide a foundation for building a next-generation CAS (Computer Algebra System) and numerical toolkit in Rust.

✨ Features

The library is organized into five major components:

Symbolic:
Computer algebra system foundations, differentiation & integration, group theory, Lie algebras, polynomial algebra, PDE/ODE solvers, Grobner bases, quantum mechanics operators, graph algorithms, and more.
Numerical:
Linear algebra, optimization (Rastrigin, Rosenbrock, Sphere, Linear Regression), numerical integration, probability distributions, FFT, combinatorics, special functions, PDE solvers (heat, wave, Schrödinger 1D–3D), root finding, and statistical analysis.
Physics:
Simulation modules covering FDM/FEM/FVM solvers, multigrid methods, molecular mechanics (SPH), electrodynamics (FDTD), Navier–Stokes fluid dynamics, relativity (geodesics, Schwarzschild), elasticity, quantum simulations, and more.
Output:
Pretty-printing, LaTeX/Typst export, NumPy-compatible I/O, and plotting utilities (2D/3D surfaces, vector fields, parametric curves).
Plugins:
Optional extensions (enabled with the full feature).

🚀 Quick Start

Add rssn to your Rust project:

cargo add rssn

Then start exploring:

use num_bigint::BigInt;
use rssn::symbolic::calculus::differentiate;
use rssn::symbolic::core::Expr;

fn test_differentiate_x_squared_stack_overflow() {
    let x = Expr::Variable("x".to_string());
    let x2 = Expr::Mul(Box::new(x.clone()), Box::new(x.clone()));
    let d = differentiate(&x2, "x");

    // The derivative of x^2 is 2*x.
    // The simplification process might result in Constant(2.0) or BigInt(2).
    let two_const = Expr::Constant(2.0);
    let expected_const = Expr::Mul(Box::new(two_const), Box::new(x.clone()));

    let two_int = Expr::BigInt(BigInt::from(2));
    let expected_int = Expr::Mul(Box::new(two_int), Box::new(x.clone()));

    println!("Derivative: {:?}", d);
    println!("Expected (const): {:?}", expected_const);
    println!("Expected (int): {:?}", expected_int);

    assert!(d == expected_const || d == expected_int);
}

For more examples, see the project repository.

📚 Documentation

API Docs: docs.rs/rssn
Project Website: Apich-Organization.github.io/rssn

🗺️ Roadmap

v0.1.0 — First public release
v0.2.0 — Stabilization release
v0.3.0 — Performance improvements & broader coverage
v0.4.0 — Optional FFI for HPC, start development of rsst scripting toolkit
v1.0.0 — API stabilization

🤝 Contributing

We welcome contributions of all kinds — bug fixes, performance optimizations, new algorithms, and documentation improvements. See CONTRIBUTING.md for detailed guidelines.

💰 Sponsorship & Donations

Scientific computing requires heavy resources for CI/CD, benchmarking, and cloud testing. You can support development via GitHub Sponsors.

Enterprise sponsors will receive:

Priority support from the core maintainers
Ability to request features
Direct collaboration on integration needs

Excess donations will be redirected to upstream Rust ecosystem projects (e.g., rust-LLVM) or community initiatives.

Updates: Due to temporary issues, GitHub Sponsors is currently unavailable. If you would like to make a donation, please use PayPal to donate to @panayang338.

👥 Maintainers & Contributors

Author: Pana Yang (ORCID: 0009-0007-2600-0948, email: Pana.Yang@hotmail.com)
Consultants:
- X. Zhang (Algorithm & Informatics, @RheaCherry, 3248998213@qq.com)
- Z. Wang (Mathematics)
- Y. Li (Physics) (xian1360685019@qq.com)
Additional contributors: Owen Yang (yangguangyong@gmail.com)

📜 License

Licensed under the Apache 2.0. See LICENSE for details.

rssn 0.1.2