Problem-solving strategies for graph algorithms in graph number theory
Use this skill when working on graph-algorithms problems in graph number theory.
Traversal selection
Shortest path algorithms
| Algorithm | Use Case | Complexity |
|---|---|---|
| Dijkstra | Non-negative weights | O((V+E) log V) |
| Bellman-Ford | Negative weights | O(VE) |
| Floyd-Warshall | All pairs | O(V^3) |
Minimum Spanning Tree
z3_solve.py prove "cut_property"Network Flow
sympy_compute.py linsolve "flow_conservation"Graph properties
uv run python -m runtime.harness scripts/sympy_compute.py eigenvalues "adjacency_matrix"
uv run python -m runtime.harness scripts/z3_solve.py prove "d[v] >= d[u] + w(u,v) for all edges"
uv run python -m runtime.harness scripts/z3_solve.py prove "min_edge_crossing_cut_in_mst"
uv run python -m runtime.harness scripts/sympy_compute.py linsolve "flow_conservation_equations"
From indexed textbooks:
See .claude/skills/math-mode/SKILL.md for full tool documentation.