ENTRO-PULSE introduces Periodic Entropy Pulsing (PEP) β 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.
| 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) |
| Metric | ENTRO-PULSE | Baseline |
|---|---|---|
| Throughput gain | +38.7% | β |
| Collapse events under burst overload | 0% | 23.4% |
| Peak network load reduction | 86.1% | β |
| Burst survival rate | 100% | β |
pip install entro-pulsefrom 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}")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}")from entro_pulse import RhythmicResonanceController
rrl = RhythmicResonanceController(n_agents=8, K=0.5)
phases = rrl.step(100)
r = rrl.order_parameter() # r β 0 confirms anti-phase synchronization
print(f"Order parameter: {r:.4f}")| Resource | Link |
|---|---|
| Website | https://entro-pulse.netlify.app |
| Research Paper | https://doi.org/10.5281/zenodo.19547863 |
| API Reference | https://entro-pulse.readthedocs.io |
ENTRO-PULSE/
β
βββ entro_pulse/
β βββ __init__.py
β βββ epwm.py # EPWM Controller β Eq 3.1, 3.2, 4.1, 4.2
β βββ rrl.py # RRL Controller β Eq 5.1, 5.2, 5.3
β βββ pgc.py # Pulse-Ghost Controller β Eq 6.1, 6.2, 6.3
β βββ utils.py # Simulation utilities
β
βββ tests/
β βββ test_epwm.py # 8 tests
β βββ test_rrl.py # 5 tests
β βββ test_pgc.py # 8 tests
β βββ test_utils.py # 4 tests
β
βββ examples/
β βββ example_epwm.py
β βββ example_rrl.py
β βββ example_pgc.py
β
βββ results/
β βββ daily_report_2026-04-14.txt
β βββ weekly_report_week15_2026.txt
β βββ monthly_report_april_2026.txt
β βββ alerts.log
β βββ coverage_report_2026-04-14.txt
β
βββ docs/
β βββ conf.py
β βββ index.rst
β βββ api.rst
β
βββ Netlify/
β βββ index.html
β βββ dashboard.html
β βββ reports.html
β βββ documentation.html
β
βββ bin/
β βββ run_simulation.py
β
βββ scripts/
βββ data/
βββ dist/
β βββ entro-pulse-1.0.0.tar.gz
β
βββ pyproject.toml
βββ requirements.txt
βββ requirements-dev.txt
βββ Dockerfile
βββ Makefile
βββ VERSION
βββ CITATION.cff
βββ AUTHORS.md
βββ CHANGELOG.md
βββ CONTRIBUTING.md
βββ SECURITY.md
βββ DEPLOY.md
βββ INSTALL.md
βββ COMPLETION.md
| Metric | Value |
|---|---|
| Python modules | 5 |
| Test files | 4 |
| Test cases | 25 / 25 passed |
| Coverage | 89% |
| Governing equations | 12+ |
ENTRO-PULSE is the ninth project in the EntropyLab series β 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 |
β Program home: entropia-lab.netlify.app
@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}
}MIT License Β© 2026 Samir Baladi Ronin Institute / Rite of Renaissance Β· ORCID 0009-0003-8903-0029
"A system that pulses does not merely survive its entropy dynamics β it dances with them."
β EntropyLab Research Program