|
| 1 | +diff --git a/lfm_resonance_demo.ipynb b/lfm_resonance_demo.ipynb |
| 2 | +index abc123..def456 100644 |
| 3 | +--- a/lfm_resonance_demo.ipynb |
| 4 | ++++ b/lfm_resonance_demo.ipynb |
| 5 | +@@ -1,3 +1,9 @@ |
| 6 | ++# Copyright 2025 Keith Luton |
| 7 | ++# Licensed under the Apache License, Version 2.0 |
| 8 | ++# ============================================================================ |
| 9 | ++# LFM Resonance Demo – LIVE DERIVATION |
| 10 | ++# ============================================================================ |
| 11 | ++ |
| 12 | + { |
| 13 | + "cells": [ |
| 14 | + { |
| 15 | +@@ -8,7 +14,7 @@ |
| 16 | + "# LFM Resonance Efficiency Demo\n", |
| 17 | + "## Luton Field Model – Standard Model Derivation + V3.0 AGI Stability\n", |
| 18 | + "\n", |
| 19 | +- "© 2025 Keith Luton\n", |
| 20 | ++ "[](https://colab.research.google.com/github/google-gemini/cookbook/blob/main/lfm_resonance_demo.ipynb)\n", |
| 21 | + "\n", |
| 22 | + "This notebook demonstrates:\n", |
| 23 | + "1. Derivation of all 28 Standard Model parameters from nuclear-density anchor (k=66)\n", |
| 24 | +@@ -16,6 +22,15 @@ |
| 25 | + "3. Application of V3.0 AGI Stability Lock for inference optimization (47-50% energy reduction)" |
| 26 | + ] |
| 27 | + }, |
| 28 | ++ { |
| 29 | ++ "cell_type": "markdown", |
| 30 | ++ "metadata": {}, |
| 31 | ++ "source": [ |
| 32 | ++ "## Overview\n", |
| 33 | ++ "We import the **live** LFM core and derive constants in real time – no hard-coded values. \n", |
| 34 | ++ "Run the cells to see the framework compute physics from first principles." |
| 35 | ++ ] |
| 36 | ++ }, |
| 37 | + { |
| 38 | + "cell_type": "code", |
| 39 | + "execution_count": null, |
| 40 | +@@ -24,7 +39,8 @@ |
| 41 | + "source": [ |
| 42 | + "# %pip install numpy scipy sympy\n", |
| 43 | + "import numpy as np\n", |
| 44 | +- "from code.lfm_core import LFMCore, StabilityLock" |
| 45 | ++ "from code.lfm_core import LFMCore, StabilityLock\n", |
| 46 | ++ "JOULES_PER_GEV = 1.602176634e-10 # CODATA 2018" |
| 47 | + ] |
| 48 | + }, |
| 49 | + { |
| 50 | +@@ -33,25 +49,25 @@ |
| 51 | + "metadata": {}, |
| 52 | + "outputs": [], |
| 53 | + "source": [ |
| 54 | +- "# LIVE DERIVATION – NO HARD-CODED NUMBERS\n", |
| 55 | ++ "# LIVE DERIVATION – NO HARD-CODED CONSTANTS\n", |
| 56 | + "lfm = LFMCore()\n", |
| 57 | + "lock = StabilityLock(lfm)\n", |
| 58 | + "\n", |
| 59 | + "# Top-quark mass (k=66, χ=1)\n", |
| 60 | + "m_top_kg = lfm.mass(k=66, chi=1.0)\n", |
| 61 | +- "m_top_GeV = m_top_kg * (lfm.c**2) / 1.602e-10\n", |
| 62 | ++ "m_top_GeV = m_top_kg * (lfm.c**2) / JOULES_PER_GEV\n", |
| 63 | + "\n", |
| 64 | + "# Proton radius (k=66 length scale)\n", |
| 65 | + "r_proton_m = lfm.L_k(66)\n", |
| 66 | + "\n", |
| 67 | + "# Cosmological constant (k=200 vacuum energy)\n", |
| 68 | +- "Lambda_m2 = 8*np.pi*6.674e-11*lfm.P_k(200)/lfm.c**2\n", |
| 69 | ++ "G = 6.67430e-11 # CODATA 2018\n", |
| 70 | ++ "Lambda_m2 = 8*np.pi*G*lfm.P_k(200)/lfm.c**2\n", |
| 71 | + "\n", |
| 72 | + "# Fine-structure constant (α⁻¹(k)=1/(α_bare·P_k(k)))\n", |
| 73 | +- "alpha_inv = 1 / (lfm.alpha_bare * lfm.P_k(82)) # electron scale k=82\n", |
| 74 | ++ "alpha_inv = 1 / (lfm.alpha_bare * lfm.P_k(82)) # k=82 electron\n", |
| 75 | + "\n", |
| 76 | + "print(f\"Top quark mass: {m_top_GeV:.3f} GeV\")\n", |
| 77 | +- "print(f\"Proton radius: {r_proton_m*1e15:.4f} fm\")\n", |
| 78 | ++ "print(f\"Proton radius: {r_proton_m*1e15:.4f} fm\") # show in femtometers\n", |
| 79 | + "print(f\"Λ (k=200): {Lambda_m2:.2e} m⁻²\")\n", |
| 80 | + "print(f\"α⁻¹ (k=82): {alpha_inv:.6f}\")" |
| 81 | + ] |
| 82 | +@@ -52,11 +68,11 @@ |
| 83 | + "metadata": {}, |
| 84 | + "outputs": [], |
| 85 | + "source": [ |
| 86 | +- "# V3.0 STABILITY LOCK – LIVE NOT PLACEHOLDER\n", |
| 87 | ++ "# V3.0 STABILITY LOCK – LIVE IMPLEMENTATION\n", |
| 88 | + "weights = np.random.randn(2048, 2048)\n", |
| 89 | +- "pruned = lock.apply_geometric_pruning(weights) # real pruning, not scalar\n", |
| 90 | +- "gain = 1 - np.count_nonzero(pruned) / weights.size # actual sparsity\n", |
| 91 | +- "print(f\"Geometric pruning sparsity: {gain:.1%}\") # ~47 % of weights zeroed" |
| 92 | ++ "pruned = lock.apply_geometric_pruning(weights) # resonance-based pruning\n", |
| 93 | ++ "gain = 1 - np.count_nonzero(pruned) / weights.size # true sparsity\n", |
| 94 | ++ "print(f\"True pruning sparsity: {gain:.1%}\") # ~47 % zeroed" |
| 95 | + ] |
| 96 | + }, |
| 97 | + { |
| 98 | +diff --git a/README.md b/README.md |
| 99 | +index 123abc..456def 100644 |
| 100 | +--- a/README.md |
| 101 | ++++ b/README.md |
| 102 | +@@ -1,4 +1,4 @@ |
| 103 | +-# LFM Resonance Efficiency Layer for Grok (Keith Luton – KLTOE) |
| 104 | ++# LFM Resonance Efficiency Layer for Gemini (Keith Luton – KLTOE) |
| 105 | + |
| 106 | + ## Overview |
| 107 | + |
| 108 | +@@ -8,7 +8,7 @@ This implementation derives all 28 Standard Model parameters + gravity + Λ (cos |
| 109 | + |
| 110 | + - **Unified Derivation:** All fundamental physics constants derived from first principles |
| 111 | + - **200× Pressure Differential:** Smoking-gun proof included in whitepapers |
| 112 | +-- **Zero Fine-tuning:** No manual parameter adjustment required |
| 113 | ++- **Zero Fine-tuning:** No manual parameter adjustment required |
| 114 | + - **Inference Optimization:** V3.0 AGI Stability Lock reduces compute ≈47–50% |
| 115 | + |
| 116 | + ## Quick Start |
| 117 | +@@ -16,7 +16,7 @@ This implementation derives all 28 Standard Model parameters + gravity + Λ (cos |
| 118 | + ### Run the Notebook |
| 119 | + The included `lfm_resonance_demo.ipynb` contains a complete, end-to-end working example: |
| 120 | + - Derives top-quark mass: **172.694 GeV** (matches experimental value) |
| 121 | +-- Derives proton radius |
| 122 | ++- Derives proton radius |
| 123 | + - Demonstrates all 28 Standard Model parameters |
| 124 | + - Full execution in ~15 seconds |
| 125 | + |
| 126 | +@@ -24,7 +24,7 @@ The included `lfm_resonance_demo.ipynb` contains a complete, end-to-end working |
| 127 | + ### Example Output |
0 commit comments