Add Massive_Atomic_Diversity_MAD_test files

README.md

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+---
+configs:
+- config_name: default
+  data_files: "co/*.parquet"
+- config_name: info
+  data_files: "ds.parquet"
+license: cc-by-4.0
+tags:
+- molecular dynamics
+- mlip
+- interatomic potential
+pretty_name: Massive Atomic Diversity MAD test
+---
+### <details><summary>Cite this dataset </summary>Mazitov, A., Chorna, S., Fraux, G., Bercx, M., Pizzi, G., De, S., and Ceriotti, M. _Massive Atomic Diversity MAD test_. ColabFit, 2025. https://doi.org/10.60732/e55c4ce1</details>  
+#### This dataset has been curated and formatted for the ColabFit Exchange  
+#### This dataset is also available on the ColabFit Exchange:  
+https://materials.colabfit.org/id/DS_s05lflv67rsn_0  
+#### Visit the ColabFit Exchange to search additional datasets by author, description, element content and more.  
+https://materials.colabfit.org
+<br><hr>  
+# Dataset  Name  
+Massive Atomic Diversity MAD test  
+### Description  
+The test split of the MAD (Massive Atomic Diversity) dataset. From the creators: Starting from relatively small sets of stable structures, the dataset is built to contain “massive atomic diversity” (MAD) by aggressively distorting these configurations, with near-complete disregard for the stability of the resulting configurations. The electronic structure details, on the other hand, are chosen to maximize consistency rather than to obtain the most accurate prediction fora given structure, or to minimize computational effort. The MAD dataset we present here, despite containing fewer than 100k structures, has already been shown to enable training universal interatomic potentials that are competitive with models trained on traditional datasets with two to three orders of magnitude more structures.  
+### Dataset authors  
+Arslan Mazitov, Sofiia Chorna, Guillaume Fraux, Marnik Bercx, Giovanni Pizzi, Sandip De, Michele Ceriotti  
+### Publication  
+https://doi.org/10.48550/arXiv.2506.19674  
+### Original data link  
+https://doi.org/10.24435/materialscloud:vd-e8  
+### License  
+CC-BY-4.0  
+### Number of unique molecular configurations  
+9546  
+### Number of atoms  
+259376  
+### Elements included  
+Ag, Al, Ar, As, Au, B, Ba, Be, Bi, Br, C, Ca, Cd, Ce, Cl, Co, Cr, Cs, Cu, Dy, Er, Eu, F, Fe, Ga, Gd, Ge, H, He, Hf, Hg, Ho, I, In, Ir, K, Kr, La, Li, Lu, Mg, Mn, Mo, N, Na, Nb, Nd, Ne, Ni, O, Os, P, Pb, Pd, Pm, Po, Pr, Pt, Rb, Re, Rh, Rn, Ru, S, Sb, Sc, Se, Si, Sm, Sn, Sr, Ta, Tb, Tc, Te, Ti, Tl, Tm, V, W, Xe, Y, Yb, Zn, Zr  
+### Properties included  
+energy, atomic forces, cauchy stress  
+<br>
+<hr>  
+
+# Usage  
+- `ds.parquet` : Aggregated dataset information.  
+- `co/` directory: Configuration rows each include a structure, calculated properties, and metadata.  
+- `cs/` directory : Configuration sets are subsets of configurations grouped by some common characteristic. If `cs/` does not exist, no configurations sets have been defined for this dataset.  
+- `cs_co_map/` directory : The mapping of configurations to configuration sets (if defined).  
+<br>
+#### ColabFit Exchange documentation includes descriptions of content and example code for parsing parquet files:  
+- [Parquet parsing: example code](https://materials.colabfit.org/docs/how_to_use_parquet)  
+- [Dataset info schema](https://materials.colabfit.org/docs/dataset_schema)  
+- [Configuration schema](https://materials.colabfit.org/docs/configuration_schema)  
+- [Configuration set schema](https://materials.colabfit.org/docs/configuration_set_schema)  
+- [Configuration set to configuration mapping schema](https://materials.colabfit.org/docs/cs_co_mapping_schema)  

co/co_0.parquet

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+version https://git-lfs.github.com/spec/v1
+oid sha256:4a911438592b1d6e80320fbe4e48cf4d0e893aba144041108fca397b74649561
+size 12984138

ds.parquet

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ba92d5cca9d8430ad302e01d6b3cc1b24eeabcf0a9f3335fca508ee9e481d5b5
+size 20648