GenesisAeon Entropy Atlas — Packages 25 (Apoptosis) & 26 (Neuromorphic SNN)
Project description
GenesisAeon Entropy Atlas — Packages 25 & 26
Package 25: Apoptosis / Programmed Cell Death ATP Threshold Package 26: Neuromorphic SNN Hardware Bridge (Intel Loihi 2)
Package 25 — cellular-genesis: Apoptosis ATP Threshold
Models intracellular ATP dynamics, mitochondrial membrane potential collapse, Bcl-2/Bcl-xL anti-apoptotic network coherence, and ultrasensitive caspase-3 activation for a stochastic cell population. Computes the CREP criticality index Γ ≈ 0.090 for the apoptotic phase transition.
Apoptosis UTAC Model
| Parameter | Value | Meaning |
|---|---|---|
| K | 5.0 mM | Healthy cytoplasmic ATP ceiling |
| H* | 1.0 mM | Cytochrome c release threshold |
| η | 0.20 | H*/K — cellular fragility setpoint |
| Γ | ≈ 0.090 | arctanh(0.20) / 2.2 — CREP criticality index |
CREP Tensor (P25)
| Symbol | Component | Description |
|---|---|---|
| C | Coherence | Bcl-2/Bcl-xL anti-apoptotic network stability |
| R | Resonance | Mitochondrial membrane potential Δψ oscillation |
| E | Emergence | Caspase-3 ultrasensitive switch state |
| P | Population entropy | Cell-to-cell ATP variability (stochastic noise) |
| Γ | Criticality index | arctanh(η) / σ ≈ 0.090 |
Usage
from cellular_genesis.system import CellularGenesis
sim = CellularGenesis(n_cells=1000, bcl_xl=0.5, seed=42)
result = sim.run_cycle(duration_hours=48.0, stress=0.1)
print(f"Survival fraction: {result['survival_final']:.3f}")
crep = sim.get_crep_state()
print(f"Gamma = {crep['Gamma']:.4f} (reference: {crep['Gamma_ref']})")
utac = sim.get_utac_state()
record = sim.to_zenodo_record()
Package 26 — spiking-aeon: Neuromorphic SNN Hardware Bridge
Bridges the GenesisAeon CREP weight system to physical Spiking Neural Network hardware (Intel Loihi 2). CREP tensor components C, R, E, P are translated into LIF neuron parameters (membrane time constants, synaptic weights, noise amplitudes, refractory periods). Software simulation runs without hardware via the Brian2-compatible pure-Python backend.
Calibrated against NeuEdge (arXiv:2602.02439, 2026): 847 GOp/s/W · 2.3 ms latency · 89% core utilisation · 312× energy improvement over GPU.
SNN UTAC Model
| Parameter | Value | Meaning |
|---|---|---|
| K | 1000 Hz | Max sustainable Loihi 2 firing rate |
| H* | 320 Hz | Critical firing rate for task performance |
| η | 0.32 | H*/K — SNN operating setpoint |
| Γ | ≈ 0.150 | arctanh(0.32) / 2.2 — SNN hardware criticality index |
CREP → LIF Parameter Mapping (P26)
| CREP | LIF Parameter | High value effect |
|---|---|---|
| C | τ_m (membrane time constant) | Longer integration window |
| R | I_noise amplitude | Optimal stochastic resonance |
| E | Synaptic weight W | Stronger collective coupling |
| P | τ_ref (refractory period) | Richer temporal coding |
Usage
from spiking_aeon.system import SpikingAeon
sim = SpikingAeon(n_neurons=1000, seed=42)
# Software simulation (no hardware required)
result = sim.run_cycle(duration_ms=1000.0)
print(f"Mean firing rate: {result['mean_rate_hz']:.1f} Hz")
crep = sim.get_crep_state()
print(f"Gamma = {crep['Gamma']:.4f} (reference: {crep['Gamma_ref']})")
utac = sim.get_utac_state()
print(f"H = {utac['H']:.4f}, H* = {utac['H_star']}, below threshold: {utac['below_threshold']}")
# Zenodo record with full Loihi 2 benchmark metadata
record = sim.to_zenodo_record()
# Deploy to Loihi 2 (requires INRC access + pip install lava-nc)
# sim.deploy_to_loihi()
Stochastic Resonance
sr = sim.optimise_stochastic_resonance(n_steps=20)
print(f"Optimal noise D_res = {sr['D_res']:.3f} (min CV = {sr['min_CV']:.3f})")
Install
# Package 25 (apoptosis) — includes numpy/scipy
pip install "cellular-genesis[cellular]"
# Package 26 (SNN) — includes numpy
pip install "cellular-genesis[spiking]"
# Both packages
pip install "cellular-genesis[cellular,spiking]"
# Base (no scientific dependencies)
pip install cellular-genesis
CREP Criticality Spectrum Position
Domain Pkg Γ_domain η_setpoint
─────────────────────────── ──── ───────── ───────────
Qubit decoherence (T2) P24 0.050 ~5%
Apoptosis (ATP threshold) P25 0.090 20% ← cellular-genesis
Amazon Rainforest P19 0.116 12%
SNN firing (Loihi 2) P26 0.150 32% ← spiking-aeon
Seismic b=1.5 (GR law) P23 0.200 ~40%
AMOC / Neural criticality P18/20 0.251 50% ← triple universality
BTW Sandpile (SOC) P22 0.296 58%
Package Structure
src/
├── cellular_genesis/ # Package 25 — Apoptosis
│ ├── __init__.py # version 0.2.0, gamma=0.090, package_number=25
│ ├── constants.py
│ ├── atp_dynamics.py
│ ├── mitochondria.py
│ ├── bcl_network.py
│ ├── caspase_cascade.py
│ ├── population.py
│ ├── crep_cellular.py
│ ├── resource_governor.py
│ ├── system.py # Diamond interface
│ └── benchmark.py
└── spiking_aeon/ # Package 26 — Neuromorphic SNN
├── __init__.py # version 0.2.0, gamma=0.150, package_number=26
├── constants.py
├── lif_neuron.py # LIF neuron (CREP-modulated threshold)
├── stdp_plasticity.py # Spike-Timing Dependent Plasticity
├── stochastic_resonance.py # Optimal noise sweep (Ferreira 2025)
├── crep_to_weights.py # CREP tensor → LIF network parameters
├── crep_snn.py # SNN CREP tensor {C, R, E, P, Γ}
├── brian2_backend.py # Pure-Python LIF network simulation
├── loihi_adapter.py # Loihi 2 / Lava SDK interface stub
├── system.py # Diamond interface
└── benchmark.py
Citation
This repository already has Zenodo–GitHub integration enabled and an
assigned concept DOI (10.5281/zenodo.19645351). New GitHub Releases mint
updated version DOIs automatically.
@software{romer2026genesis_atlas,
author = {Römer, Johann},
title = {GenesisAeon Entropy Atlas — Packages 25 \& 26},
year = {2026},
version = {0.2.0},
publisher = {Zenodo},
doi = {10.5281/zenodo.19645351},
url = {https://doi.org/10.5281/zenodo.19645351},
}
@article{fcell2025,
doi = {10.3389/fcell.2025.1611055},
journal = {Frontiers in Cell and Developmental Biology},
year = {2025},
note = {Package 25 reference},
}
@misc{neuredge2026,
title = {NeuEdge: Energy-Efficient Neuromorphic Edge Computing},
year = {2026},
eprint = {2602.02439},
note = {Package 26 reference — 847 GOp/s/W on Loihi 2},
}
diamond-setup CLI
This repo also hosts the diamond-setup scaffold tool — see README_QUICKSTART.md.
diamond scaffold my-science-package --template genesis
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