# Quickstart Tutorial¶

Here’s an example of how you use HOOMD-TF. To compute a 1 / r pairwise potential:

import hoomd, hoomd.md
import hoomd.htf as htf
import tensorflow as tf

########### Model Building Code ###########
class MyModel(htf.SimModel):
def compute(self, nlist):
rinv = htf.nlist_rinv(nlist)
energy = rinv
forces = htf.compute_nlist_forces(nlist, energy)
return forces

########### Hoomd-Sim Code ################
hoomd.context.initialize()
# 32 is maximum number of neighbors
model = MyModel(32)
tfcompute = htf.tfcompute(model)
# create a square lattice
system = hoomd.init.create_lattice(unitcell=hoomd.lattice.sq(a=4.0),
n=[3,3])
nlist = hoomd.md.nlist.cell()
hoomd.md.integrate.mode_standard(dt=0.005)
hoomd.md.integrate.nve(group=hoomd.group.all())
tfcompute.attach(nlist, r_cut=3.0)
hoomd.run(1e3)


This creates a computation graph whose energy function is 2 / r and also computes forces and virial for the simulation. The 2 is because the neighbor lists in HOOMD-TF are full neighbor lists (double counted). The HOOMD-blue code starts a simulation of a 9 particle square lattice and simulates it for 1000 timesteps under the potential defined in our HOOMD-TF model. The general process of using HOOMD-TF is to build a model by defining a compute function and then use the model in HOOMD-blue. See Building a Model and Using a Model in a Simulation for a more detailed description. Or see a complete set of Jupyter Notebook tutorials.