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About
Chapters
Schedule (Spring 2025)
Stats
Probability theory
Random variables
Diffusion
Entropy and Information
Thermodynamics
Review of thermodynamics principles
Thermodynamic Potentials
Ensembles
Ensemble equivalence
Ensembles in phase-space
muPT
Gases
Quantum non-interacting systems
Photons and Phonons
Phase transitions
Monte Carlo and “the power of randomness”
Ising models and Metropolis algorithm
Phase transitions through the lense of Ising models
Mean Field Theory
Mean Field theory of interacting fluids
Analytic solutions to 1D Ising model
Fluids
Statistical mechanics of fluids
MC simulations of fluids
Molecular Dynamics
MD simulations of fluids
Kinetics
Langevin equation and Brownian motion
Tutorials
Python
Python3
NumPy
Plotting
Tutorial: Building Python Classes
Numpy lab
Numpy and Probabilities
Numpy Lab: Sinc Function
Numpy Lab: Linear Functions
Tutorial: Numpy simultions of 1D gas
Tutorial: Numpy simultions of 2D gas
Random Walks
Random walk simulations
The Inverse Transform of RVs
Change of variables with automatic differentiation (autodiff)
Conformations of Random Polymer Chains
Langevin Equation for Brownian Motion and Mean Square Displacement (MSD)
Application of ensembles
Free energy and protein folding
Two-state system
Mass action law
Simulating Ising models
Ising-2D simulations using ML libraries
Other Methods for sampling Ising models
Non-boltzman (enhanced) sampling ideas
Simulating Fluids
Double Well potential using OpenMM
Simulating toy polymers using openMM
Simulating Ethane
Simulating solvated protein
Index
