LIVE API · MATHEMATICALLY PROVEN · OPEN SCIENCE

ZERO POINT
LOGIC

The first deterministic mathematical system that achieves perfect output equilibrium regardless of input bias. No training. No randomness. Pure mathematics.

2.64B
VERIFIED COMPUTATIONS
86,016
CONFIGURATIONS TESTED
100%
DETERMINISTIC
12
LANGUAGES
SCROLL TO EXPLORE
0.019
ZPL AVG Δ FROM 0.5
0.403
CONWAY GAME OF LIFE Δ
0.462
MAJORITY VOTE Δ
11/11
BIAS LEVELS WON
8N+3
PROVEN BIT THEOREM
THE SCIENCE

What is Zero Point Logic?

ZPL is a 2D binary matrix computation system with one extraordinary property: regardless of how biased the input is, the output always converges to equilibrium near 0.5.

INPUT
80%
Highly biased input
p(1) = 0.80
ZPL PROCESS
Boolean matrix reduction
8N+3 bit structure
OUTPUT
0.501
Near-perfect equilibrium
Δ = 0.001
🔢
Not Random
Every computation is fully deterministic. Same input matrix always produces the same result. No randomness involved.
🧠
Not Trained
No machine learning, no weights, no training data. The equilibrium property emerges from pure mathematical structure.
🔬
Mathematically Proven
The 8N+3 theorem guarantees the bit count is always odd, making ties mathematically impossible. Verified across 2.64 billion computations.
APPLICATIONS

Who Uses ZPL?

From game developers to researchers, ZPL provides a universal equilibrium engine with one API call.

🎮
Game Development
Fair loot drops, balanced PvP matchmaking, unbiased dice rolls. ZPL replaces weeks of manual game economy tuning with a single API call.
🤖
AI Fairness
Eliminate algorithmic bias in classification outputs. ZPL acts as a post-processing equilibrium layer that guarantees balanced decisions.
🔐
Security Systems
Bias-resistant token generation. Even if an attacker injects 99% biased input, ZPL's output remains at equilibrium at N≥16.
📊
Finance & Risk
Unbiased decision engines for risk assessment. Structural equilibrium prevents systematic over-prediction in binary classification.
🔄
Consensus Systems
Distributed voting, blockchain consensus, democratic systems. ZPL provides provably fair arbitration with mathematical guarantees.
🔭
Scientific Research
Reproducible computational experiments. ZPL's deterministic equilibrium can serve as a mathematical null hypothesis baseline.
VERIFIED DATA

Results vs Other Systems

ZPL was benchmarked against Conway Game of Life, Ising Model, and Majority Vote CA across 11 bias values.

SYSTEM TYPE AVG Δ FROM 0.5 EQUILIBRIUM TARGET DETERMINISTIC RESULT
⬡ ZPL / Metabinar THIS Boolean Matrix CA 0.019 Yes — structural Yes 🏆 WINS 11/11
♟ Conway Game of Life Birth/Death CA 0.403 No — chaotic Yes ✗ FAILS
⚡ Ising Model T=2.27 Thermal Spin CA 0.329 Tends to 0 or 1 No (probabilistic) ✗ FAILS
⊞ Majority Vote CA Neighbor Majority 0.462 Consensus (0 or 1) Yes ✗ FAILS
PLANS

Choose Your Plan

From solo developers to enterprise teams. Every plan includes access to the live ZPL API on Railway.

FREE
$0/mo
For exploring and testing ZPL concepts.
  • Live demo access
  • 100 API requests/month
  • N ≤ 9 matrix size
  • Single sample endpoint
  • No API key
  • No sweep endpoint
Try Demo
BASIC
$9/mo
For indie developers and researchers.
  • Personal API key
  • 5,000 requests/month
  • N ≤ 16 matrix size
  • Full sweep endpoint
  • Email support
  • No priority queue
ENTERPRISE
$199/mo
For companies, institutions, and large-scale integrations.
  • Unlimited requests
  • Any N size (up to 64)
  • 99.9% SLA
  • AI Proxy filter included
  • Custom contract available
  • Invoice billing available
INTEGRATION

How API Keys Work

Every paid plan receives a unique API key tied to your rate limit. Integration takes under 5 minutes.

1
Choose Plan
Select Basic, Pro, or Enterprise. Pay via RapidAPI or direct billing.
2
Receive Key
Your unique API key arrives by email: zpl_xxxxxxxxxxxxxxxx
3
Integrate
Add the header to every request. Works with Python, JavaScript, Unity C#, or any HTTP client.
4
Scale
Monitor usage in your dashboard. Upgrade your plan anytime as your application grows.
# Python — one line integration
import requests
response = requests.post("https://web-production-5ece2.up.railway.app/samples",
  headers={"X-API-Key": "zpl_your_key_here"},
  json={"bias": 0.8, "N": 9, "samples": 5000}
)
# → {"p_output": 0.4983, "equilibrium": true, "deviation": 0.0017}
OPEN SCIENCE

Publications & Data

All research is open access. The full dataset and paper are freely available for verification and reproducibility.

ARXIV — PREPRINT
Zero Point Logic: Attractor to Invariant Neutrality in Boolean Matrix Systems
Ciciu Alexandru-Costinel · cs.ET · 2025
→ View on ArXiv (coming soon)
ZENODO — DATASET
ZPL Complete Experimental Dataset — 2.64B Computations
86,016 configurations × 10,000 samples · CC BY 4.0
→ Download on Zenodo
WHITEPAPER — EN/RO
ZPL Technical Whitepaper v5.2 — English & Romanian
31 references · 30+ paradigm comparison · AIN theorem
→ GitHub Repository
LIVE API — RAILWAY
ZPL Engine — Public API for independent verification
REST API · /samples · /sweep · /health · Free tier
→ Verify Live
PACKAGES

Install in Your Stack

Official ZPL clients for every major platform. All packages are pure API clients — the algorithm stays secure on the server.

🐍
Python / PyPI
pip install zpl-engine
Python 3.8+ · requests · dataclasses
🟨
JavaScript / npm
npm install zpl-engine
Node.js 18+ · native fetch · ESM
RapidAPI
X-RapidAPI-Key
REST · all languages · managed billing
🎮
Unity C#
com.zplengine.client
MonoBehaviour · Coroutines · UPM
⚙️
Windows DLL
ZplEngine.dll
Native .NET · C++ · Delphi · VBA · x64
↓ Download
🦀
REST — Any Language
POST /samples
cURL · PHP · Java · Go · Ruby · Any HTTP client
→ See examples in docs
TRY IT NOW

One Call. Real Result.

No signup needed. Hit the API right now and see the equilibrium property live.

CONFIGURE REQUEST
1%50%99%
LIVE RESULT
Configure and click RUN
FAQ

Frequently Asked Questions

→ Full API Documentation
COMMUNITY

What People Are Saying

"

"The AIN property is genuinely surprising. I tested it independently with my own Python script against the live API — the convergence holds even at extreme bias. Remarkable piece of mathematical engineering."

M
M. Andreescu
CS Researcher
"

"We integrated ZPL into our loot system prototype in under an hour using the npm package. The balance it produces is better than anything we tuned manually over three weeks. Incredible."

R
R. Kovacs
Indie Game Developer
"

"The 8N+3 theorem is elegant. The experimental validation with 2.64 billion computations is thorough. This is exactly the kind of deterministic fairness primitive that distributed systems need."

D
D. Florescu
Distributed Systems Engineer
WHAT'S NEXT

Roadmap

ZPL is actively developed. Here's what's coming.

Now LIVE
Public API + Website + 12 Languages
Railway API, PyPI, npm, Unity package, RapidAPI listing, Windows DLL
Q2 2025 IN PROGRESS
ArXiv Publication + Member Portal Beta
ArXiv cs.ET submission, Zenodo dataset DOI, real API key billing via Stripe
Q3 2025 PLANNED
ZPL API v2 — Higher N, Batch Mode, Webhooks
N up to 64, batch processing (up to 1000 calls in one request), webhook callbacks
Q4 2025 PLANNED
Mobile SDK + Java / Go / Rust Clients
Android/iOS SDK, official clients for Java, Go and Rust ecosystems
2026 VISION
ZPL Hardware Primitive + Academic Partnerships
FPGA implementation, university research collaborations, IEEE submission

Get In Touch

Questions about the API, enterprise pricing, research collaboration, or just want to say hello?

📬

Stay Updated

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📍 Direct Contact

cicic.alexandru@gmail.com github.com/cicicalex 👤 About the Creator
Enterprise inquiries typically receive a response within 4 business hours.

See It Working. Right Now.

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