Quantum Wave Field Function (ChatGPT)

A little chat with ChatGPT 4o returned the following Python code, which I then ran in Google Colab:

import numpy as np
from PIL import Image
import colorsys

# Image size
WIDTH = HEIGHT = 4096
TOTAL_COLORS = WIDTH * HEIGHT

# Step 1: Generate all RGB colors — exactly once
colors = np.zeros((TOTAL_COLORS, 3), dtype=np.uint8)
index = 0
for r in range(256):
    for g in range(256):
        for b in range(256):
            colors[index] = (r, g, b)
            index += 1

assert index == TOTAL_COLORS, "Color generation failed"

# Step 2: Generate quantum-inspired coordinate map
# Convert coordinates to "wave-interference energy" for sorting
coords = []
for y in range(HEIGHT):
    for x in range(WIDTH):
        # Normalize to [-1, 1]
        nx = (x - WIDTH / 2) / (WIDTH / 2)
        ny = (y - HEIGHT / 2) / (HEIGHT / 2)
        # Simulate quantum field interference (wave-like energy)
        wave = (
            np.sin(10 * nx) * np.cos(10 * ny)
            + np.sin(20 * nx * ny)
            + np.cos(15 * (nx**2 + ny**2))
        )
        coords.append((wave, x, y))

# Step 3: Sort pixels by wave function output
coords.sort()

# Step 4: Sort colors for aesthetic match (e.g., brightness)
brightness = np.dot(colors, [0.299, 0.587, 0.114])
sorted_color_indices = np.argsort(brightness)
colors_sorted = colors[sorted_color_indices]

# Step 5: Create image and assign each color to its sorted coordinate
img = Image.new("RGB", (WIDTH, HEIGHT))
pixels = img.load()

for (i, (_, x, y)) in enumerate(coords):
    pixels[x, y] = tuple(colors_sorted[i])

# Step 6: Save image losslessly
img.save("quantum_field_color_space.png", format="PNG")