README.md

Subversive Serendipity

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🔗Partition function (statistical mechanics) - wikipedia page
🔗Thermodynamic beta - wikipedia page
🔗Two Level Systems and more
📘Einstein model

Second Law of Thermo

🔗The 2nd Law of Thermodynamics -- A Probablistic Law

Quantum stuff

🔗 http://www.thomaswong.net/

🎲 https://www.thegamecrafter.com/games/qubit-touchdown
📖Introduction to Classical and Quantum Computing

Miscellaneous

🔗 https://longnow.org/

Brainstorming (9/2/2024)

import numpy as np

# Define the sefirot
sefirot = ["Keter", "Chokhmah", "Binah", "Chesed", "Gevurah", "Tiferet", "Netzach", "Hod", "Yesod", "Malkuth"]

# Number of sefirot
n = len(sefirot)

# Assign self-energies using a Gaussian distribution
mean = 100
std_dev = 20
self_energies = np.random.normal(mean, std_dev, n)

# Define a hypothetical interaction energy matrix
# For simplicity, we'll use a symmetric matrix with small random values
interaction_energies = np.random.uniform(-10, 10, (n, n))
np.fill_diagonal(interaction_energies, 0)  # No self-interaction
interaction_energies = (interaction_energies + interaction_energies.T) / 2  # Make it symmetric

# Construct the Hamiltonian matrix
H = np.diag(self_energies) + interaction_energies

# Diagonalize the Hamiltonian
eigenvalues, eigenvectors = np.linalg.eigh(H)

# Print the results
print("Sefirot:", sefirot)
print("Self-Energies:", self_energies)
print("Interaction Energies:\n", interaction_energies)
print("Hamiltonian:\n", H)
print("Eigenvalues:", eigenvalues)
print("Eigenvectors:\n", eigenvectors)