Dataset Open Access

Scripts and models for "Machine learning the electronic structure of matter across temperatures"

Fiedler, Lenz; Modine, Normand A.; Miller, Kyle D.; Cangi, Attila

# Data and Scripts for "Machine learning the electronic structure of matter across temperatures"

This dataset contains data and calculation scripts for the publication "Machine learning the electronic structure of matter across temperatures".
Its goal is to enable interested parties to reproduce the experiments we have carried out.

## Prerequesites

The following software versions are needed for the python scripts:

- `python`: 3.8.x
- `mala`: 1.2.0 
- `numpy`: 1.23.0 (lower version may work)

Further, make sure you have downloaded additional data such as local pseudopotentials and training data.

## Contents

- `data_analysis/`: Contains scripts contain useful functions to reproduce the analysis carried out on the provided 
                    data.
- `model_training/`: Contains scripts that allow the training and testing of the models discussed in the accompanying
                     publication.
- `trained_models`: Contains the models discussed in the accompanying publication. Per data set, five models with 
                    different random initializations were trained. 

Files (5.1 GB)
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ml_electronic_temperature_data.zip
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Data volume 112.2 GB112.2 GB
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Cite as

Fiedler, Lenz, Modine, Normand A., Miller, Kyle D., & Cangi, Attila. (2023). Scripts and models for "Machine learning the electronic structure of matter across temperatures" (Version v1.0.0) [Data set]. Rodare. http://doi.org/10.14278/rodare.2266

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