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Adds link to glassy dynamics dataset in google cloud storage.

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Thomas Keck
2020-04-16 10:52:52 +01:00
committed by Diego de Las Casas
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commit 6b11d21e5a
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@@ -6,6 +6,9 @@ network model described in our
The model can be trained using the training binary included in this repository, The model can be trained using the training binary included in this repository,
and the dataset published with our paper. and the dataset published with our paper.
Pretrained model checkpoints and the dataset are available via the
[google cloud platform](https://console.cloud.google.com/storage/browser/deepmind-research-glassy-dynamics).
## Abstract ## Abstract
@@ -26,14 +29,20 @@ other physical systems that map to a graph of local interaction.
## Dataset ## Dataset
### System description
The dataset was generated with the LAMMPS molecular dynamics package. The dataset was generated with the LAMMPS molecular dynamics package.
The simulated system has periodic boundaries and is a binary mixture of 4096 The simulated system has periodic boundaries and is a binary mixture of 4096
large (A) and small (B) particles that interact via a 6-12 Lennard-Jones large (A) and small (B) particles that interact via a 6-12 Lennard-Jones
potential. potential.
The interaction coefficients are set for a typical Kob-Andersen configuration. The interaction coefficients are set for a typical Kob-Andersen configuration.
### Download
The dataset (and model checkpoints) can be downloaded using [gsutil](https://cloud.google.com/storage/docs/downloading-objects).
To download the entire GCP bucket (~100GB) use:
> gsutil -m cp -R gs://deepmind-research-glassy-dynamics .
### Data format ### Data format
The data is stored in Python's pickle format protocol version 3. The data is stored in Python's pickle format protocol version 3.