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--- howto:allegro [2023/04/24 13:48] – gtocci
+++ howto:allegro [2024/01/03 13:15] (current) – oschuett
@@ Line 1: / Line 1: @@
-====== How to Train a neural network interatomic potential using Allegro and Perform Molecular Dynamics with CP2K ======
+This page has been moved to: https://manual.cp2k.org/trunk/methods/machine_learning/nequip.html
-This [[https://github.com/gabriele16/cp2k/blob/nequip-cp2k-colab/colab/allegro-cp2k-tutorial.ipynb|Colab tutorial]] illustrates how to train an equivariant neural network interatomic potential for bulk water using the Allegro framework. You will learn how to train a model, deploy it in production, and run molecular dynamics simulations in ''CP2K''. The training and inference will be carried out on the GPU provided by the Colab environment.
-Allegro is designed for constructing highly accurate and scalable interatomic potentials for molecular dynamics simulations. The methodology is described in detail in this paper ([[doi>10.1038/s41467-023-36329-y]]). An open-source package (https://github.com/mir-group/allegro) that implements Allegro, built on the nequip framework was developed by the Allegro and NequIP (https://github.com/mir-group/nequip) authors.
-Inference in CP2K is performed through the ''MM'' package of ''CP2K'', ''Fist''. As an example, the relevant section for Allegro (or similarly for NequIP) is:
-<code - Allegro_si_MD.inp >
-      &ALLEGRO
-        ATOMS Si
-        PARM_FILE_NAME Allegro/si-deployed.pth
-        UNIT_COORDS angstrom
-        UNIT_ENERGY eV
-        UNIT_FORCES eV*angstrom^-1
-      &END ALLEGRO
- </code>
-where the ''si-deployed.pth'' refers to the PyTorch model that was deployed using the Allegro framework, and the ''UNIT'' tags refer to the units of the coordinates, energy and forces of the model itself.
-For additional references on NequIP, Allegro and equivariant neural networks (e3nn) see:
-  - Allegro paper [[doi>10.1038/s41467-023-36329-y]] and code [[https://github.com/mir-group/allegro|https://github.com/mir-group/allegro]]
-  - NequIP paper [[doi>10.1038/s41467-022-29939-5]] and code [[https://github.com/mir-group/nequip|https://github.com/mir-group/nequip]]
-  - NequIP/Allegro Tutorial on LAMMPS by the authors of the above papers, see Colab notebook [[https://colab.research.google.com/drive/1yq2UwnET4loJYg_Fptt9kpklVaZvoHnq|here]]
-  - For an introduction to e3nn see [[https://blondegeek.github.io/e3nn_tutorial|here]], [[doi>10.5281/zenodo.7430260]]