💓 ENTRO-PULSE (E-LAB-09)
Periodic Entropy Pulsing and Informational Wave Management in High-Velocity AI Systems
Overview
ENTRO-PULSE introduces Periodic Entropy Pulsing (PEP) — a control paradigm that transforms entropy flow management from continuous suppression into a rhythmically-managed oscillatory regime.
Rather than fighting entropy accumulation reactively, PEP orchestrates it: drawing on the cardiac pulsing model, PWM principles from power electronics, and the Kuramoto model of coupled oscillator synchronization to turn system stress into a structured, predictable wave.
Core Contributions
| Component | Full Name | Role |
|---|---|---|
| EPWM | Entropy Pulse Width Modulation | Adaptive duty-cycle control of entropy flow |
| RRL | Rhythmic Resonance Law | Anti-phase Kuramoto synchronization across agents |
| PGC | Pulse-Ghost Controller | Integration bridge with ENTRO-GHOST (E-LAB-08) |
Validated Results
| Metric | ENTRO-PULSE | Baseline |
|---|---|---|
| Throughput gain | +38.7% | — |
| Collapse events under burst overload | 0% | 23.4% |
| Peak network load reduction | 86.1% | — |
| Burst survival rate | 100% | — |
Installation
pip install entro-pulse
Quick Start
EPWM Controller
from entro_pulse import EntropyPulseController
# Initialize with angular frequency and max duty cycle
epwm = EntropyPulseController(omega=0.8, delta_max=0.7)
# Execute a control step
result = epwm.step(psi=0.85, u_base=0.1)
print(f"Duty cycle : {result.duty_cycle:.3f}")
print(f"Output : {result.u_output:.3f}")
Pulse-Ghost Controller
Integrates entropic memory traces from ENTRO-GHOST (E-LAB-08).
from entro_pulse import PulseGhostController
pgc = PulseGhostController(omega=0.8, delta_max=0.7, zeta=0.65, rho=0.4)
result = pgc.step(psi=0.85, u_base=0.1)
print(f"Ghost trace : {result.ghost_trace:.3f}")
print(f"Ghost pull : {result.ghost_pull:.3f}")
Rhythmic Resonance Law — Distributed Systems
from entro_pulse import RhythmicResonanceController
rrl = RhythmicResonanceController(n_agents=8, K=0.5)
phases = rrl.step(100)
r = rrl.order_parameter() # r → 0 confirms anti-phase synchronization
print(f"Order parameter: {r:.4f}")
Documentation
| Resource | Link |
|---|---|
| Website | https://entro-pulse.netlify.app |
| Research Paper | https://doi.org/10.5281/zenodo.19547863 |
| API Reference | https://entro-pulse.readthedocs.io |
Project Structure
ENTRO-PULSE/
│
├── entro_pulse/
│ ├── __init__.py
│ ├── epwm.py # EPWM Controller — Eq 3.1, 3.2, 4.1, 4.2
│ ├── rrl.py # RRL Controller — Eq 5.1, 5.2, 5.3
│ ├── pgc.py # Pulse-Ghost Controller — Eq 6.1, 6.2, 6.3
│ └── utils.py # Simulation utilities
│
├── tests/
│ ├── test_epwm.py # 8 tests
│ ├── test_rrl.py # 5 tests
│ ├── test_pgc.py # 8 tests
│ └── test_utils.py # 4 tests
│
├── examples/
│ ├── example_epwm.py
│ ├── example_rrl.py
│ └── example_pgc.py
│
├── results/
│ ├── daily_report_2026-04-14.txt
│ ├── weekly_report_week15_2026.txt
│ ├── monthly_report_april_2026.txt
│ ├── alerts.log
│ └── coverage_report_2026-04-14.txt
│
├── docs/
│ ├── conf.py
│ ├── index.rst
│ └── api.rst
│
├── Netlify/
│ ├── index.html
│ ├── dashboard.html
│ ├── reports.html
│ └── documentation.html
│
├── bin/
│ └── run_simulation.py
│
├── scripts/
├── data/
├── dist/
│ └── entro-pulse-1.0.0.tar.gz
│
├── pyproject.toml
├── requirements.txt
├── requirements-dev.txt
├── Dockerfile
├── Makefile
├── VERSION
├── CITATION.cff
├── AUTHORS.md
├── CHANGELOG.md
├── CONTRIBUTING.md
├── SECURITY.md
├── DEPLOY.md
├── INSTALL.md
└── COMPLETION.md
Codebase Statistics
| Metric | Value |
|---|---|
| Python modules | 5 |
| Test files | 4 |
| Test cases | 25 / 25 passed |
| Coverage | 89% |
| Governing equations | 12+ |
EntropyLab Research Program
ENTRO-PULSE is the ninth project in the EntropyLab series — a unified research program bridging thermodynamic entropy, Shannon information theory, and AI systems control.
| E-LAB | Project | Focus |
|---|---|---|
| 01 | ENTROPIA | Theoretical foundations |
| 02 | ENTRO-AI | AI inference stability |
| 03 | ENTRO-CORE | Core entropy measurement |
| 04 | ENTRO-ENGINE | System coupling |
| 05 | ENTRO-EVO | Adaptive weighting |
| 06 | ENTRO-NET | Distributed synchronization |
| 07 | ENTRO-QUANTUM | Probabilistic states |
| 08 | ENTRO-GHOST | Entropic memory |
| 09 | ENTRO-PULSE | Periodic pulsing |
| 10 | ENTRO-MANIFESTO | Unified manifesto |
→ Program home: entropia-lab.netlify.app
Citation
@software{baladi2026entropulse,
author = {Samir Baladi},
title = {ENTRO-PULSE: Periodic Entropy Pulsing and Informational Wave Management
in High-Velocity AI Systems},
year = {2026},
publisher = {Zenodo},
doi = {10.5281/zenodo.19547863},
note = {EntropyLab E-LAB-09},
url = {https://doi.org/10.5281/zenodo.19547863}
}
License
MIT License © 2026 Samir Baladi Ronin Institute / Rite of Renaissance · ORCID 0009-0003-8903-0029
"A system that pulses does not merely survive its entropy dynamics — it dances with them."
— EntropyLab Research Program
Metadata
Release files for entro-pulse 1.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| entro_pulse-1.0.0.tar.gz | 20.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| entro_pulse-1.0.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 33.9 kB
Release files / entro_pulse-1.0.0.tar.gz
| Download URL | entro_pulse-1.0.0.tar.gz |
|---|---|
| Size | 20.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
b6dea64f72eb264826431208c8c0ae21b2b7290e66667b7aeeb918eadca667e0
|
|
BLAKE2b-256 checksum How to use checksums |
4277cb6f44fd0ca7a6c0979a2bad274d7bbab070857fe63d21de5e00540449c2
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
ENTRO-PULSE-Uploader/1.0
|
Release files / entro_pulse-1.0.0-py3-none-any.whl
| Download URL | entro_pulse-1.0.0-py3-none-any.whl |
|---|---|
| Size | 13.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
34f5924d33edf8564706c6b22f198bfe90a187aab73089e6b8f39b6868d19034
|
|
BLAKE2b-256 checksum How to use checksums |
bd8044382625266766b399d5099b85aae58a533f946b4f8bfba9288e461a555c
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
ENTRO-PULSE-Uploader/1.0
|