Regional attention transformer for Open-Quantum-Dynamics Dataset (v1.0)

# EIT Open-Quantum-Dynamics Dataset (v1.0) This dataset contains synthetic datasets and evlauation results in: “Learning spatially structured open quantum dynamics with regional-attention transformers”. ## Contents ``` - quantum_memory/: datasets and eval results in the EIT quantum memory learning. - eval/ - evaluation_smooth_learning_2_150epoches/ evaluation of Quformer 4.4M in decoherence free datasets(ID&OOD) - evaluation_smooth_learning_2_150epoches_deco/ evaluation of Quformer 4.4M in decoherence datasets(ID&OOD) - evaluation_smooth_learning_2_150epoches_6layers/ evaluation of Quformer Var1 6.3M in decoherence free datasets(ID&OOD) - evaluation_smooth_learning_2_150epoches_6layers_deco/ evaluation of Quformer Var1 6.3M in decoherence datasets(ID&OOD) - evaluation_var1_150epoches/ evaluation of Quformer Var2 6.1M in decoherence free datasets(ID&OOD) - evaluation_var1_150epoches_deco/ evaluation of Quformer Var2 6.1M in decoherence datasets(ID&OOD) - syntheticQuantumMemoryData/ - data/ - decoherence_data/ datasets with decoherence. Naming: *_in_distribution: used for train/eval in model training; *_id_extra, *_OOD*: used for evaluation ID and OOD sets. - decoherenceFree_data/ decoherence free datasets. Naming: in_distribution: used for train/eval in model training; in_distribution_extra, OOD*: used for evaluation ID and OOD sets. - single_qubit/: datasets and eval results in the single qubit learning. - data/ synthetic datasets. - evaluation/ evlaution of ID(*_0sigma) and OODs(*_1sigma to *_3sigma) ``` ## Use with Github code Download corresponding code from https://github.com/Dounan662/RegionalAttentionOpenQuantum ## License Data: CC BY 4.0. Please cite the DOI below. ## Citation Du, D. et al., Regional attention transformer for Open-Quantum-Dynamics Dataset, Zenodo, v1.0, DOI: <to be filled after publish>. Additional support was provided by the Stony Brook Foundation through the Quantum Network Research Center (SBF 248090)