This is code repository for Quantum Adiabatic Optimization article.
Start by running instance.py
that will build list-based definiton of the graph from its set-based definition, this will let you keep consistent indices between all the runs.
The run.py
is the adiabatic optimization code.
Energy spectrum can be examined by running eigenenergies.py
with single command line argument being one of HMVC
, HMVC_
, HMIS
or HMIS_
. I don't suggest running all the diagonalizations in single run, graphs are big and you are likely to get a segmentation fault error. This is why it is good to keep consistent indices and store your graph using lists and not sets.
You can plot figures using plot.py
.