Implementation of neural coherent states, a type of neural-network quantum states introduced in the following preprint:
Artificial neural network states for non-additive systems
Wojciech Rzadkowski, Mikhail Lemeshko, Johan H. Mentink
arXiv:2105.15193
This code needs Jax and Flax. Python 3.9 is recommended.
Running python main.py
will perform learning procedure for a small system
with two bosonic modes. Energies at each optimization step will be written to output.txt
. For
simplicity, adjusting both the physics and algorithm parameters is done directly
in the main file by editing
physics_pars
and arg_pars
variables.
The code runs on GPU without change. Consult this material for running on TPU.
The tests can be run with python tests.py
. No errors indicate tests passing,
while AssertionError
s appearing correspond to their failure.