Seven-Gate Identity Framework Implementation

Comprehensive Testing Blueprint for Michael Levin’s Algotype Experiment

Complete implementation of seven-gate identity framework with rigorous testing against Michael Levin’s algotype experiment, demonstrating processual identity theory through logical operations in sorting algorithms

Seven-Gate Identity Framework Implementation

This notebook implements a comprehensive seven-gate identity framework that directly interfaces with Michael Levin’s algotype experiment conditions, following the rigorous testing blueprint for integrating our identity-gate framework with empirical clustering phenomena.

Framework Overview

Building on Michael Levin’s groundbreaking discovery of clustering behavior in sorting algorithms, we implement a theoretical framework where:

• Elements are self-implementing logical operators with Gate-Policy Vectors (GPVs)
• Seven identity gates (Be, Sustain, Compose, Belong, Generate, Transition, Maintain) govern element interactions
• Gate-Policy Vectors (GPVs) encode each element’s operational behavior as 7-bit binary strings
• Clustering emerges from logical compatibility and gate interactions
• Identity is processual - maintained through consistent operational patterns

What We’ll Implement

1. Seven-gate identity framework mapped to Levin’s experimental conditions
2. Gate-Policy Vectors encoding element behaviors as 7-bit binary strings
3. Interactive seven-gate visualization with real-time heatmap and gate activation patterns
4. Levin’s exact metrics: Sortedness, Monotonicity Error, Delayed Gratification, Aggregation Value
5. Factorial experimental design spanning 486 conditions with fault models
6. Statistical validation against Levin’s published results

Interactive Seven-Gate Visualization

Before diving into the Python implementation, let’s explore the seven-gate identity framework through an interactive visualization that shows real-time gate activation patterns, clustering dynamics, and GPV interactions during bubble sort:

Animation Controls

Speed: 5x

Array Size: 400 12 elements 16 elements 20 elements 24 elements 400 elements

GPV Distribution: Bubble Heavy Balanced (Equal GPVs) Bubble Heavy (70/30) Selection Heavy (30/70) Diverse (4 GPV types)

Gate Activation Threshold: 0.5

Gate Trail Effect

Seven-Gate Bubble Sort Array

BE Gate (Identity)

SUSTAIN Gate (OR)

COMPOSE Gate (XOR)

BELONG Gate (XOR)

GENERATE Gate (AND)

TRANSITION Gate (NOR)

MAINTAIN Gate (NAND)

Swaps: 0 Comparisons: 0 Gate Activations: 0 Sort Progress: 0%

Gate Activation Heatmap

Real-time visualization of seven-gate activation patterns across array positions

Gate-Policy Vector (GPV) Patterns

Visual representation of GPV distributions and their interactions

Seven-Gate Color Summation

Combined gate activation intensities showing emergent pattern complexity

Real-time Pattern Analytics

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Clustering Coefficient

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Pattern Stability

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Gate Complexity

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Operation Frequency

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Identity Flow

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Levin Sortedness

Seven-Gate Operations Status

Current operational state analysis of identity gates

Let’s explore the theoretical foundations through Python implementation…