summary

paper/paper.md

@@ -13,19 +13,26 @@ authors:
     orcid: 0000-0001-6873-0278
     affiliation: 1
 affiliations:
- - name: Inorganic Chemistry Deparment, University of Oxford
+ - name: Department of Chemistry, Inorganic Chemistry Laboratory, University of Oxford, Oxford OX1 3QR, United Kingdom
    index: 1
 date: 10/01/2025
 bibliography: paper.bib
+
 ---
 
 # Summary
 
-TODO
+`graph-pes` is an open-source toolkit that accelerates the development, training and deployment of machine-learned potential energy surfaces (ML-PESs) that act on graph-based representations of atomic structures. The `graph-pes` toolkit comprises three components:
+
+1. **the `graph_pes` Python package**: a modular Python library containing all the functionality required to build and train graph-based ML-PES models. This includes a mature data pipeline for converting atomic structures into graph representations, a fully featured ML-PES base class with automatic force and stress inferences, and a suite of common data manipulation and model building blocks.
+
+2. **the `graph-pes-train` command-line interface**: a unified tool for training graph-based ML-PES models on datasets of labelled atomic structures. Several popular model architectures are provided out of the box, but the interface is designed so that custom, end-user defined architectures can be used (alongside custom loss functions, optimizers, datasets, etc.)
+
+3. **the `pair style graph_pes` LAMMPS integration**: a pair style for using LAMMPS to perform GPU-accelerated molecular dynamics simulations using any graph-based ML-PES model defined and trained using the `graph_pes` package.
+
 
 # Statement of need
 
-TODO
 
 # Related work
 
@@ -37,6 +44,8 @@ The core functionality of `graph-pes` builds upon
 
 - `ase` [@HjorthLarsen-17-06]
 
+- `LAMMPS` 
+
 `graph-pes` also builds upon the `e3nn` [@Geiger-22-07] package for implementing the `NequIP` [@Batzner-22-05] and `MACE` [@Batatia-23-01] architectures.
 
 Other note-worthy softwares that offer similar functionality to `graph-pes` include:
@@ -45,14 +54,16 @@ Other note-worthy softwares that offer similar functionality to `graph-pes` incl
 
 - `mace-torch`
 
-- `deepmd`
+- `deepmd-kit`
 
 - `schnetpack`
 
 - `torchmd`
 
+
 # Acknowledgements
 
 Krystian Gierczak, Daniel Thomas du Toit and Zoé Faure Beaulieu for early testing and feedback.
 
+
 # References