docs: document external neighbor list

Signed-off-by: Jinzhe Zeng <[email protected]>

doc/inference/python.md

@@ -27,3 +27,20 @@ model_devi = calc_model_devi(coord, cell, atype, graphs)
 ```
 
 Note that if the model inference or model deviation is performed cyclically, one should avoid calling the same model multiple times. Otherwise, tensorFlow will never release the memory and this may lead to an out-of-memory (OOM) error.
+
+## External neighbor list algorithm
+
+The native neighbor list algorithm of the DeePMD-kit is in $O(N^2)$ complexity ($N$ is the number of atoms).
+While this is not a problem for small systems that quantum methods can afford, the large systems for molecular dynamics have slow performance.
+In this case, one may pass an external neighbor list that has lower complexity to {class}`DeepPot <deepmd.infer.DeepPot>`, once it is compatible with {class}`ase.neighborlist.NewPrimitiveNeighborList`.
+
+```py
+import ase.neighborlist
+
+neighbor_list = ase.neighborlist.NewPrimitiveNeighborList(
+    cutoffs=6, bothways=True, self_interaction=False
+)
+dp = DeepPot("graph.pb", neighbor_list = neighbor_list)
+```
+
+The `update` and `build` methods will be called by {class}`DeepPot <deepmd.infer.DeepPot>`, and `first_neigh`, `pair_second`, and `offset_vec` properties will be used.