ODE Solver Library
SkillDev toolsNumerical methods for ordinary differential equations
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Details
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What this skill tells your AI
The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/science/mathematics/skills/ode-solver-library/SKILL.md and read by Ahel’s review.
Purpose
Provides numerical methods and solvers for ordinary differential equations in mathematical modeling and dynamical systems analysis.
Capabilities
- Runge-Kutta methods (explicit and implicit)
- Multistep methods (Adams-Bashforth, BDF)
- Stiff equation handling
- Adaptive step size control
- Event detection and root finding
- Sensitivity analysis
Usage Guidelines
- Stiffness Assessment: Determine if problem is stiff
- Method Selection: Choose explicit or implicit methods accordingly
- Tolerance Setting: Set appropriate error tolerances
- Event Handling: Configure event detection for discontinuities
Tools/Libraries
- SUNDIALS
- scipy.integrate
- DifferentialEquations.jl
Signals
- GitHub stars
- 2k
- Forks
- 113
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
ode-solver-library- Source
- github.com/a5c-ai/babysitter