name: numerical-stability
description: >
Analyze numerical stability for time-dependent PDE simulations — check CFL
and Fourier criteria, perform von Neumann stability analysis, detect stiffness,
evaluate matrix conditioning, and recommend explicit vs implicit time-stepping
schemes. Use when selecting time steps, diagnosing numerical blow-up or solver
divergence, checking convergence criteria, or evaluating scheme stability for
advection, diffusion, or reaction problems, even if the user doesn't explicitly
mention "stability" or "CFL."
allowed-tools: Read, Bash, Write, Grep, Glob
metadata:
author: HeshamFS
version: "1.1.0"
security_tier: high
security_reviewed: true
tested_with:
- claude-code
- gemini-cli
- vs-code-copilot
eval_cases: 2
last_reviewed: "2026-03-26"
Numerical Stability
Goal
Provide a repeatable checklist and script-driven checks to keep time-dependent simulations stable and defensible.
Requirements
- Python 3.8+
- NumPy (for matrix_condition.py and von_neumann_analyzer.py)
- See
scripts/requirements.txt for dependencies
Inputs to Gather
| Input | Description | Example |
|---|
Grid spacing dx | Spatial discretization | 0.01 m |
Time step dt | Temporal discretization | 1e-4 s |
Velocity v | Advection speed | 1.0 m/s |
Diffusivity D | Thermal/mass diffusivity | 1e-5 m²/s |
Reaction rate k | First-order rate constant | 100 s⁻¹ |
| Dimensions | 1D, 2D, or 3D | 2 |
| Scheme type | Explicit or implicit | explicit |
Decision Guidance
Choosing Explicit vs Implicit
Is the problem stiff (fast + slow dynamics)?
├── YES → Use implicit or IMEX scheme
│ └── Check conditioning with matrix_condition.py
└── NO → Is CFL/Fourier satisfied with reasonable dt?
├── YES → Use explicit scheme (cheaper per step)
└── NO → Consider implicit or reduce dx
Stability Limit Quick Reference
| Physics | Number | Explicit Limit (1D) | Formula |
|---|
| Advection | CFL | C ≤ 1 | C = v·dt/dx |
| Diffusion | Fourier | Fo ≤ 0.5 | Fo = D·dt/dx² |
| Reaction | Reaction | R ≤ 1 | R = k·dt |
Multi-dimensional correction: For d dimensions, diffusion limit is Fo ≤ 1/(2d).
Script Outputs (JSON Fields)
| Script | Key Outputs |
|---|
scripts/cfl_checker.py | metrics.cfl, metrics.fourier, recommended_dt, stable |
scripts/von_neumann_analyzer.py | results.max_amplification, results.stable |
scripts/matrix_condition.py | results.condition_number, results.is_symmetric |
scripts/stiffness_detector.py | results.stiffness_ratio, results.stiff, results.recommendation |
Workflow
- Identify dominant physics (advection vs diffusion vs reaction)
- Run CFL checker with
scripts/cfl_checker.py
- Compare to limits and adjust
dt if needed
- Check stiffness with
scripts/stiffness_detector.py if multiple scales
- Analyze custom schemes with
scripts/von_neumann_analyzer.py
- Check conditioning with
scripts/matrix_condition.py for implicit solves
- Document the stability verdict and recommended time step
Conversational Workflow Example
User: My phase-field simulation is blowing up after 100 steps. I'm using explicit Euler with dx=0.01, dt=1e-4, and diffusivity D=1e-3.
Agent workflow:
- Check stability criteria:
python3 scripts/cfl_checker.py --dx 0.01 --dt 1e-4 --diffusivity 1e-3 --dimensions 2 --json
- Interpret results:
- Fourier number:
Fo = 1e-3 × 1e-4 / (0.01)² = 1.0
- 2D limit:
Fo ≤ 0.25
- Violation: Fo = 1.0 > 0.25, unstable!
- Recommend fix:
- Reduce dt to
2.5e-5 (to get Fo = 0.25)
- Or increase dx, or switch to implicit
Pre-Simulation Stability Checklist
CLI Examples
# Check CFL/Fourier for 2D diffusion-advection
python3 scripts/cfl_checker.py --dx 0.1 --dt 0.01 --velocity 1.0 --diffusivity 0.1 --dimensions 2 --json
# Von Neumann analysis for custom 3-point stencil
python3 scripts/von_neumann_analyzer.py --coeffs 0.2,0.6,0.2 --dx 1.0 --nk 128 --json
# Detect stiffness from eigenvalue estimates
python3 scripts/stiffness_detector.py --eigs=-1,-1000 --json
# Check matrix conditioning for implicit system
python3 scripts/matrix_condition.py --matrix A.npy --norm 2 --json
Error Handling
| Error | Cause | Resolution |
|---|
dx and dt must be positive | Zero or negative values | Provide valid positive numbers |
No stability criteria applied | Missing velocity/diffusivity | Provide at least one physics parameter |
Matrix file not found | Invalid path | Check matrix file exists |
Could not compute eigenvalues | Singular or ill-formed matrix | Check matrix validity |
Interpretation Guidance
| Scenario | Meaning | Action |
|---|
stable: true | All checked criteria satisfied | Proceed with simulation |
stable: false | At least one limit violated | Reduce dt or change scheme |
stable: null | No criteria could be applied | Provide more physics inputs |
| Stiffness ratio > 1000 | Problem is stiff | Use implicit integrator |
| Condition number > 10⁶ | Ill-conditioned | Use scaling/preconditioning |
Security
Input Validation
- All numeric parameters (
dx, dt, velocity, diffusivity, dimensions) are validated as finite positive numbers before any computation
--dimensions is restricted to {1, 2, 3}
- Comma-separated eigenvalue lists (
--eigs) are capped at 10,000 entries and validated as finite numbers
- Stencil coefficient lists (
--coeffs) are length-limited and validated as finite floats
File Access
matrix_condition.py reads a single matrix file (.npy format) specified by --matrix; no directory traversal beyond the given path
- Matrix files are rejected if they exceed 500 MB before parsing
np.load() is called with allow_pickle=False to prevent arbitrary code execution via crafted .npy files
- Scripts write only to stdout (JSON output); no files are created unless the agent explicitly uses the Write tool
Tool Restrictions
- Read: Used to inspect script source, references, and user configuration files
- Bash: Used to execute the four Python analysis scripts (
cfl_checker.py, von_neumann_analyzer.py, matrix_condition.py, stiffness_detector.py) with explicit argument lists
- Write: Used to save analysis results or generated reports; writes are scoped to the user's working directory
- Grep/Glob: Used to locate relevant files and search references
Safety Measures
- No
eval(), exec(), or dynamic code generation
- All subprocess calls use explicit argument lists (no
shell=True)
- Matrix dimension limits (100,000 per dimension) prevent memory exhaustion
- JSON output mode (
--json) produces structured, parseable results without shell-interpretable content
Limitations
- Explicit schemes only for CFL/Fourier checks (implicit is unconditionally stable)
- Von Neumann analysis assumes linear, constant-coefficient, periodic BCs
- Stiffness detection requires eigenvalue estimates from user
References
references/stability_criteria.md - Decision thresholds and formulas
references/common_pitfalls.md - Frequent failure modes and fixes
references/scheme_catalog.md - Stability properties of common schemes
Version History
- v1.1.0 (2024-12-24): Enhanced documentation, decision guidance, examples
- v1.0.0: Initial release with 4 stability analysis scripts