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FLUX Negative Space Engine

"What's left when you eliminate everything else IS the truth." — Sherlock Holmes

The space BETWEEN agents IS the computation.

Core Insight

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.

Architecture

Core Engine (core.py)

  • FluxNegativeSpace.compose() — Compute FLUX between two agents
  • FluxNegativeSpace.multi_compose() — FLUX across 3+ agents
  • Returns eigenvalues, collaborative modes, flux energy, structure detection

Casting Call Engine (casting_call.py)

  • 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

Peer Review Engine (peer_review.py)

  • Agent outputs are Laplacians
  • Conservation ratio = how expected the output is
  • Rayleigh quotient = the review score
  • Low conservation = anomaly detected

Decomposition Engine (decomposition.py)

  • Complex tasks → Fiedler partition → subtasks
  • Each subtask's FLUX with available agents is computed
  • Optimal assignment = max total FLUX energy
  • Greedy with diversity bonus

Spreadsheet-as-Graph Engine (spreadsheet.py)

  • Rows × columns = bipartite graph
  • Cell values = edge weights
  • Column correlations = structural Laplacian
  • Conservation = data integrity
  • Anomaly detection = conservation drop under perturbation

Installation

pip install numpy

Usage

from 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}")

Run Demo

python demo.py

Dependencies

License

MIT

Part of the SuperInstance OpenConstruct ecosystem.

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FLUX negative-space learning — discovering structure from what's absent in spectral graph data

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