This is a collection of materials that are used in a school on stochastic methods. Contributions from (in alphabetical order):
- George Booth
- Bryan Clark
- Ken Jordan
- Brenda Rubenstein
- James Shepherd
- Luke Shulenberger
- Cyrus Umrigar
- Lucas Wagner
The next school will be held the week of July 29 in Pittsburg. Logistical information is available here: https://molssi.org/event/school-on-stochastic-approaches-to-electronic-structure-calculations/
- python (3.6 or above recommended)
- pandas - for data analysis
- numpy - for fast numerical calculations
- matplotlib - for plotting
- Szabo and Ostlund
- Anaconda - an easy way to install Python
- Software Carpentry lessons: Git/Basic Python/Plotting in Python
- AFQMC: Motta review/Constrained path AFQMC
- FCI-QMC: Booth
- VMC and DMC: Foulkes review/Umrigar/Wagner