"What's left when you eliminate everything else IS the truth." — Sherlock Holmes
The space BETWEEN agents IS the computation.
FLUX(A,B) = L_composed - L_A - L_B
Where:
L_A= Agent A's Laplacian (its internal constraint structure)L_B= Agent B's Laplacian (its internal constraint structure)L_composed= Their combined Laplacian (with coupling)
The residual — what exists in the composed system but not in either individual — is the collaborative intelligence. It only exists in the negative space between agents.
FluxNegativeSpace.compose()— Compute FLUX between two agentsFluxNegativeSpace.multi_compose()— FLUX across 3+ agents- Returns eigenvalues, collaborative modes, flux energy, structure detection
- Tasks are Laplacians (task structure)
- Agent resumes are spectral fingerprints
- Best match = best FLUX energy with the task
- Agent affinity = FLUX between any two agents
- Agent outputs are Laplacians
- Conservation ratio = how expected the output is
- Rayleigh quotient = the review score
- Low conservation = anomaly detected
- Complex tasks → Fiedler partition → subtasks
- Each subtask's FLUX with available agents is computed
- Optimal assignment = max total FLUX energy
- Greedy with diversity bonus
- Rows × columns = bipartite graph
- Cell values = edge weights
- Column correlations = structural Laplacian
- Conservation = data integrity
- Anomaly detection = conservation drop under perturbation
pip install numpyfrom flux_negative_space import FluxNegativeSpace
flux = FluxNegativeSpace()
result = flux.compose(agent_A_laplacian, agent_B_laplacian, coupling_strength=0.1)
print(f"Collaborative modes: {result.collaborative_modes}")
print(f"FLUX energy: {result.flux_energy}")
print(f"Structured: {result.is_structured}")python demo.py- Built on FLUX Constraint Language
- Uses SpectralMessage for agent Laplacian construction
numpyfor linear algebra
MIT
Part of the SuperInstance OpenConstruct ecosystem.