Tutorials

The tutorials below demonstrate how to set up and run Monte Carlo calculations in HANDE. The input files in the test suite also demonstrate how calculations can be performed. The aim here is to provide an introduction to setting up, running and analysing calculations and only basic input options are considered; for advanced options please consult the appropriate section of the manual.

The tutorials assume that HANDE has been successfully compiled and the test suite has been sucessfully run. Any reference to hande.x should be replaced with the full path to the HANDE executable and similarly for the reblock_hande.py, finite_temperature_analysis.py and analyse_canonical.py scripts.

Note

The exact command to launch HANDE with MPI depends upon the exact configuration of MPI. The command may be different (e.g. mpirun instead of mpiexec) and might require the number of processors to be passed as an argument. The tutorials show the exact command we used, which varies depending upon the machine used to run the tutorials. We regularly use the OpenMPI implementation (mpiexec -np <# processors> or mpirun -np <# processors>), Intel MPI (mpiexec) and Cray-MPICH (aprun).

The input and output files from the calculations performed in the tutorials can be found under the documentation/manual/tutorials/calcs/ directory. The example calculations are deliberately not trivial and may require up to a few hundred core hours to run as shown. Smaller calculations can be performed by reducing the system size (e.g. using fewer electrons or orbitals) or running for fewer iterations.

Note

None of the tutorials fix a random number seed (as this is the best approach for running multiple production calculations on the same system) so results will not be exactly identical (but should agree statistically) from those in the above dataset unless the same seeds (which can be found in the output files) are used.

We recommend working through the FCIQMC tutorial before the iFCIQMC, CCMC or DMQMC tutorials.

• Full Configuration Interaction Quantum Monte Carlo
• Initiator Approximation to FCIQMC
• Semi-Stochastic FCIQMC
• Coupled Cluster Monte Carlo
• Density Matrix Quantum Monte Carlo
• Interaction Picture Density Matrix Quantum Monte Carlo
• Canonical Estimates
• Shoulder Plots
• Solid state calculations

All calculations were analysed using pyhande and all graphs were plotted using matplotlib. Parts of the plot generation code were adapted from the matplotlib tutorials.