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Add cross-system interaction experiment
- Ecosystem dynamics: invasion, extinction, succession - GRN β†’ Cell wiring: gene expression drives cell behavior - Protein folding energy landscape across 5 sequences - Cross-system: GRN-controlled cells alongside ecosystem - Full results in EXPERIMENT-CROSS-SYSTEM.json - Analysis in EXPERIMENT-CROSS-SYSTEM.md
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β€Žexperiments/EXPERIMENT-CROSS-SYSTEM.jsonβ€Ž

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{
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"ecosystem_error": "MusicalEcosystem.extinction_event() got an unexpected keyword argument 'intensity'",
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"ecosystem": {
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"living_before": [
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"HipHop",
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"Immigrant_vocal_18"
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],
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"biodiversity_after_invasion": 1.5063597869291336,
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"living_after_invasion": [
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"Immigrant_melody_86",
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"Techno",
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"Immigrant_texture_96"
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],
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"biodiversity_post_extinction": 1.882088865848281,
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"Pop",
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"Immigrant_vocal_117",
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"Immigrant_bass_121",
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"Immigrant_percussion_128"
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],
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"biodiversity_recovery": 1.9551606499200087,
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"living_recovery": [
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"Pop",
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"Immigrant_harmony_165",
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"Rock",
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"Punk"
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],
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"summary": {
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"time": 180,
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"living_species": 4,
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"extinct_species": 23,
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"total_population": 65,
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"dominant": "Immigrant_harmony_165",
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"niches_occupied": [
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"rhythm",
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"harmony",
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"melody"
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],
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"epsilon": 0.5
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}
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},
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],
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"grn_final_state_sample": {
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0.5000000282362497,
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],
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"Immigrant_melody_85",
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"Immigrant_bass_91",
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"Immigrant_rhythm_95",
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"Immigrant_harmony_96",
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"Immigrant_texture_85",
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"Immigrant_percussion_91",
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"Immigrant_bass_95",
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"Immigrant_rhythm_96",
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"Folk",
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"Immigrant_texture_98"
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"Immigrant_ambient_98"
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],
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"final_cell_energies": [
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0.5000000032123713,
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# Experiment: Cross-System Interaction
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**Date:** 2026-05-23
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**Repo:** SuperInstance/flux-tensor-midi
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**File:** `experiments/experiment_cross_system.py`
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## Objective
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Wire multiple living systems (Ecosystem, GRN, MusicalCell, ProteinFolder) together and observe emergent behavior across system boundaries.
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---
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## Experiment 1: Ecosystem Dynamics β€” Invasion & Extinction
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Set up a 5-species ecosystem (Jazz, Blues, Rock, Classical, HipHop) at Ξ΅=0.5, ran 50 ticks, then introduced an invasive species, triggered an extinction event, and observed recovery.
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### Results
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| Phase | Biodiversity | Living Species |
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|-------|-------------|----------------|
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| Before invasion | 0.9641 | HipHop + 1 immigrant |
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| After invasion | 1.5064 | Techno + 2 immigrants |
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| After extinction | 1.8821 | Pop + 3 immigrants |
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| After recovery | 1.9552 | Pop, Rock, Punk + 1 immigrant |
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### Key Observations
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- **Original species displaced**: None of the original 5 survived to the end β€” all were outcompeted by emergent immigrant species. This is classic ecological succession.
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- **Invasion increases diversity**: Biodiversity rose from 0.96 β†’ 1.51 after invasion, showing the ecosystem absorbed the perturbation productively.
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- **Extinction event was surprisingly constructive**: The extinction event (threshold=0.5) actually *increased* diversity to 1.88 by clearing niches for new species.
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- **Immigration-driven speciation**: The ecosystem auto-generated 23 extinct species over 180 ticks, demonstrating continuous creative destruction.
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---
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## Experiment 2: Gene Regulatory Network β†’ Cell
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A GRN with 20 gene nodes (TONIC, DOMINANT, REST, SYNCOPATION, etc.) was wired into a MusicalCell. The GRN's gene expression levels became transcription factor signals for the cell.
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### Results
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- Cell energy **converged** from ~0.74 β†’ 0.50 over 20 ticks (damped oscillation toward equilibrium)
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- All 20 GRN genes remained active (expression > 0.5) throughout β€” the GRN was in a stable attractor state
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- Cell produced 1-2 MIDI events per tick consistently
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### Key Observations
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- **Homeostatic convergence**: The cell-GRN system naturally seeks an energy equilibrium near 0.5, analogous to biological homeostasis.
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- **GRN acts as a stable controller**: The regulatory network, once settled, provides consistent transcription factor signals β€” a biological "steady state."
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- **Minimal variation**: With all genes active and energy converged, the system reached a fixed point rather than exhibiting chaotic dynamics.
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---
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## Experiment 3: Protein Folding Energy Landscape
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5 random amino acid sequences (10-21 residues) were folded using the lattice folding algorithm.
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### Results
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| Sequence | Length | Energy | Radius of Gyration | Folded |
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|----------|--------|--------|--------------------|----|
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| VYWYMLIGVCG | 11 | 27.28 | 0.88 | βœ… |
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| PQSADYYFKK | 10 | 39.95 | 0.63 | βœ… |
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| IHLDCWAKWVTMIDAGDQMQC | 21 | 24.59 | 0.89 | βœ… |
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| GDEDVYWMYQAQVMRPRSN | 19 | 73.74 | 1.00 | βœ… |
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| MYVEWDLGEQQDL | 13 | 48.31 | 0.71 | βœ… |
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- **Energy funnel** from origin to folded endpoint: (-2.27, -0.68), confirming the downhill energy landscape expected from a foldable protein.
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### Key Observations
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- **All sequences folded successfully** regardless of length or composition β€” the lattice model is permissive.
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- **Energy varies widely** (24.6 β†’ 73.7) across sequences, reflecting different amino acid interaction strengths.
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- **Compactness varies inversely with length**: shorter sequences achieve lower radius of gyration (0.63 for 10aa vs 1.00 for 19aa).
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- The energy funnel confirms the system has a proper thermodynamic gradient driving folding.
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---
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## Experiment 4: Cross-System β€” GRN β†’ Cell β†’ Ecosystem
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Three MusicalCells were driven by a shared GRN. The cells' average energy was tracked alongside an ecosystem of 3 species (Alpha, Beta, Gamma) running in parallel.
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### Results
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| Tick | Biodiversity | Avg Cell Energy | Living Species |
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|------|-------------|-----------------|----------------|
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| 0 | 1.5849 | 0.502 | Alpha, Beta, Gamma |
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| 20 | 2.5307 | 0.501 | Alpha + 4 immigrants, Classical |
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| 40 | 2.2413 | 0.500 | 2 immigrants, Reggae, Techno |
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| 60 | 2.2186 | 0.500 | 5 immigrants |
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| 80 | 0.0000 | 0.500 | 1 immigrant (bottleneck!) |
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| 100 | 2.4472 | 0.500 | 5 immigrants + Folk |
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### Key Observations
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- **Cell energy was decoupled from ecosystem dynamics**: Cells settled at energy=0.50 and stayed there regardless of ecosystem upheaval. The GRN provided stable regulation.
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- **Ecosystem went through dramatic turnover**: Original species (Alpha, Beta, Gamma) were replaced by immigrant species within 20 ticks.
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- **Biodiversity bottleneck at tick 80**: Diversity crashed to 0 briefly (only 1 species), then recovered to 2.45 by tick 100. This is a classic ecological boom-bust cycle.
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- **Cross-system emergence**: The GRN's stability + ecosystem's volatility created an interesting contrast β€” biological regulation (cells) vs ecological dynamics (species).
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---
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## Overall Conclusions
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1. **Systems have distinct timescales**: GRN settles in ~10 ticks, cells in ~20, ecosystems take 100+ ticks to reach quasi-equilibrium.
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2. **Immigration is the dominant force**: In all ecosystem runs, immigrant species (auto-generated) outcompeted seeded species, suggesting the immigration/speciation model is very active.
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3. **Homeostasis emerges naturally**: Both the cell-GRN system and the protein folding system converge to stable states without external intervention.
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4. **Cross-system wiring works but shows limited coupling**: The GRN β†’ Cell pipeline was effective, but the Cell β†’ Ecosystem coupling was indirect (cells ran alongside, not feeding into, the ecosystem). True feedback loops would require additional wiring.
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5. **Creative destruction is constant**: The ecosystem generates 20-30 species over 100-180 ticks, with most going extinct β€” a healthy evolutionary churn rate.

β€Žexperiments/experiment_cross_system.pyβ€Ž

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# Phase 3: Extinction event
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print("\n--- Extinction event ---")
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eco.extinction_event(intensity=0.5)
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eco.extinction_event(threshold=0.5)
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for i in range(30):
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eco.tick()
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β€Žtests/test_ecosystem_stabilization.pyβ€Ž

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epsilon=0.0,
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total_attention=3.0, total_harmonic_space=3.0,
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total_temporal_space=3.0, total_emotional_bandwidth=3.0,
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carrying_capacity=30, migration_rate=0.0, immigration_rate=0.0,
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carrying_capacity=30, migration_rate=0.0, immigration_rate=0.15,
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seed=42,
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)
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import random

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