rssn-advanced 0.0.2

A crate containing complex and delicate mathematical algorithms exspcialy heuristic one based on rssn.
Documentation 
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# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: >-
  The Rust Scientific, Symbolic and Numerical Computing
  Library Project Advanced Computing Part (RSSN-Advanced)
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Xinyu
    family-names: Yang
    email: Pana.Yang@hotmail.com
    affiliation: >-
      Jinan Zhensheng Middle School, Jinan 250100, Shandong,
      China
    orcid: 'https://orcid.org/0009-0007-2600-0948'
identifiers:
  - type: doi
    value: 10.6084/m9.figshare.31044715
    description: (RSSN) First Published on Figshare
  - type: url
    value: 'https://crates.io/crates/rssn-advanced'
    description: First Published on crates.io (Rust Package Registry)
  - type: url
    value: 'https://docs.rs/rssn-advanced'
    description: First Published on docs.io (Rust Package Docs Index)
repository-code: 'https://github.com/Apich-Organization/rssn-advanced'
url: 'https://apich-organization.github.io/rssn-advanced/'
repository: 'https://codeberg.org/Apich-Organization/rssn-advanced'
repository-artifact: >-
  https://github.com/Apich-Organization/rssn-advanced/releases
abstract: >-
  This is the Rust Scientific, Symbolic and Numerical
  Computing Library Project Advanced Computing Part source
  code archive. In this project, we explore the
  possibilities of using modern technology (like LLVM) and
  programming language (like Rust) to build computing tools
  for our research. Our main develop focus of the project
  are symbolic computing functionalities, along side modules
  for physics simulation functionalities and numerical
  functionalities. A significant portion of our research
  investigates how modern compiler technologies could have
  an impact on modernizing programming language and in the
  mean time maintain high performance. Special attention is
  also given to the pros and cons of LLM assistant coding
  and testing the boundary for its application. The project
  is still under active development and research findings
  are subject to updates. Community feedback and
  contributions are highly welcome.
keywords:
  - Computational complexity and computability
  - Mathematical physics not elsewhere classified
  - Physics
  - Computer Simulation/history
  - Physics/methods
  - Rust
  - Numerical Analysis
  - Optimization
  - Physics Simulation
  - Scientific Computing
  - Symbolic Mathematics
  - Advanced Algebras
license: Apache-2.0
commit: 5fe1ff2fd9056b397f21d02a87402c6f1dbd7
version: v0.0.2
date-released: '2026-02-14'