entro-pulse 1.0.0

ENTRO-PULSE: Periodic Entropy Pulsing and Informational Wave Management in High-Velocity AI Systems

💓 ENTRO-PULSE (E-LAB-09)

Periodic Entropy Pulsing and Informational Wave Management in High-Velocity AI Systems

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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%	—

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Installation

pip install entro-pulse

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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}")

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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

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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+

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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

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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}
}

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License

MIT License © 2026 Samir Baladi Ronin Institute / Rite of Renaissance · ORCID 0009-0003-8903-0029

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"A system that pulses does not merely survive its entropy dynamics — it dances with them."

— EntropyLab Research Program