This is a modern introduction to the topic of statistical mechanics, that is, the way in which the interactions between sufficiently large sets of molecules give rise to experimentally observable properties of a system. Click here for the syllabus.
Assignments
- Week 1 - Intro to Python: Complete the interactive tutorial at this link.
- Week 1 - Results (same as at previous link)
- Week 2 - Homework 1 (Statistics, etc.)
- >>>Homework 1 Solutions
- >>>Computational Homework 1 Solutions
- Week 3 - Homework 2 (Microcanonical Ensemble)
- >>>Homework 2 Solutions
- Week 4 - Homework 3 (Canonical Ensemble and RDF)
- >>>Homework 3 Solutions
- >>>Radial Distribution Function Computational Homework Solutions
- Week 5 - Homework 4 (Density and density fluctuations)
- >>>Homework 4 Solutions
- Week 8 - Homework 5 (MD, NPT, and Grand Canonical Ensembles)
Lecture Notes
- Lecture 1 - Intro to Stat Mech and 1-d Diffusion
- Lecture 2 - Statistics
- Lecture 3 - Central limit and intro to classical mechanics
- Lecture 4 - Phase space
- Lecture 5 - Microcanonical ensemble
- Lecture 6 - Canonical Ensemble, Pt. 1
- Lecture 7 - Canonical Ensemble, Pt. 2
- Lecture 8 - Interacting liquids and gasses
- Lecture 9 - Connection of scattering and work to the radial distribution function
- Lecture 10 - Energy and pressure from the radial distribution function
- Lecture 11 - Virial expansion and perturbation paper
- Lecture 12 - Introduction to Simulations and Monte Carlo
- Lecture 13 - Molecular Dynamics Simulations
- Lecture 14 - Enhanced Sampling Simulations and Replica Exchange
- Lecture 15 - Umbrella Sampling
- Lecture 16 - Canonical Sampling
- Lecture 17 - Other Ensembles
- Lecture 18 - Phase Transitions, Part 1
- Lecture 19 - Phase Transitions, Part 2
- Lecture 20 - Phase Transitions, Part 3
- Lecture 21 - Phase Transitions, Part 4
- Lecture 22 - Non-equilibrium, Part 1
- Lecture 23 - Non-equilibrium, Part 2
- Lecture 24 - Non-equilibrium, Part 3