Datasets:
Tasks:
Graph Machine Learning
Modalities:
Text
Formats:
webdataset
Languages:
English
Size:
1K - 10K
License:
Update README.md
Browse files
README.md
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# QHMat Dataset
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**QHMat** is a large-scale quantum Hamiltonian dataset for materials comprising **105,260 crystal structures** spanning **75** elements.
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### Dataset Description
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QHMat is a graph/tensor dataset for electronic-structure learning on materials systems. Records contain crystal structure features together with Hamiltonian/overlap tensor blocks, serialized as `torch_geometric.data.Data` objects.
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The current release provides a **~50 GiB subset** suitable for model development and integration tests. **The full dataset (~4.1 TB) is planned to be uploaded after peer review.**
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# QHMat Dataset
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**QHMat** is a large-scale quantum Hamiltonian dataset for materials comprising **105,260 crystal structures** spanning **75** elements. It contains crystal structure features together with Hamiltonian/overlap tensor blocks, serialized as `torch_geometric.data.Data` objects.
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The current release provides a **~50 GiB subset** suitable for model development and integration tests. **The full dataset (~4.1 TB) is planned to be uploaded after peer review.**
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