SciML/OrdinaryDiffEq.jl

Highly stable symplectic methods

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#82 opened on Jul 14, 2017

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 (2 comments) (0 reactions) (0 assignees)Julia (656 stars) (262 forks)batch import
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Description

https://arxiv.org/pdf/1701.02434.pdf

https://arxiv.org/pdf/1405.3153.pdf

Contributor guide

Tech stack
None
Domain
datamachine learning
Issue type
feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
5
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
over 1 week
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
stale
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
unclear
Prerequisites
numerical methods for ODEssymplectic integratorsJulia
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
5
Research direction
This issue requires implementing highly stable symplectic methods for Hamiltonian ODEs, as described in the linked arXiv papers. A first step would be to review existing symplectic integrators in the OrdinaryDiffEq.jl source code (e.g., in the src/ directory) to understand the current implementation patterns. Then, implement the new methods following the mathematical derivations from the papers, ensuring they pass convergence and stability tests.