Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: ForceNet: A Graph Neural Network for Large-Scale Quantum Calculations   With massive amounts of atomic simulation data available, there is a huge
opportunity to develop fast and accurate machine learning models to approximate
expensive physics-based calculations. The key quantity to estimate is atomic
forces, where the state-of-the-art Graph Neural Networks (GNNs) explicitly
enforce basic physical constraints such as rotation-covariance. However, to
strictly satisfy the physical constraints, existing models have to make
tradeoffs between computational efficiency and model expressiveness. Here we
explore an alternative approach. By not imposing explicit physical constraints,
we can flexibly design expressive models while maintaining their computational
efficiency. Physical constraints are implicitly imposed by training the models
using physics-based data augmentation. To evaluate the approach, we carefully
design a scalable and expressive GNN model, ForceNet, and apply it to OC20
(Chanussot et al., 2020), an unprecedentedly-large dataset of quantum physics
calculations. Our proposed ForceNet is able to predict atomic forces more
accurately than state-of-the-art physics-based GNNs while being faster both in
training and inference. Overall, our promising and counter-intuitive results
open up an exciting avenue for future research.

20
The categories of this paper are: acc-phys
32
The categories of this paper are: atom-ph
10
The categories of this paper are: q-bio
7
The categories of this paper are: hep-th
26
The categories of this paper are: bayes-an
17
The categories of this paper are: q-fin
0
The categories of this paper are: hep-ph
9
The categories of this paper are: nlin
16
The categories of this paper are: stat
4
The categories of this paper are: cond-mat
27
The categories of this paper are: comp-gas
6
The categories of this paper are: astro-ph
11
The categories of this paper are: hep-lat
22
The categories of this paper are: chao-dyn
29
The categories of this paper are: funct-an
18
The categories of this paper are: econ