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About
Getting Started
Python
Python3
NumPy
Plotting
Stats
Probability theory
Random walk
Diffusion
Entropy
Thermodynamics
Review of thermodynamics principles
Legendre transform
Chapters
Ensembles
Overview of ensembles
Phase Space
NVE
NVT
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
Labs
Numpy lab
Numpy Lab: Sinc Function
Numpy Lab: Linear Functions
Random variable lab
Conformations of Random Polymer Chains
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
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Application of ensembles
Application of ensembles
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