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Part 1: Document Description
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Citation |
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Title: |
SimCATS_GaAs_v1_random_variations_v2 |
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Identification Number: |
doi:10.26165/JUELICH-DATA/5PB3GT |
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Distributor: |
Jülich DATA |
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Date of Distribution: |
2024-10-09 |
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Version: |
1 |
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Bibliographic Citation: |
Hader, Fabian; Fuchs, Fabian; Fleitmann, Sarah, 2024, "SimCATS_GaAs_v1_random_variations_v2", https://doi.org/10.26165/JUELICH-DATA/5PB3GT, Jülich DATA, V1 |
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Citation |
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Title: |
SimCATS_GaAs_v1_random_variations_v2 |
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Identification Number: |
doi:10.26165/JUELICH-DATA/5PB3GT |
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Authoring Entity: |
Hader, Fabian (ZEA-2) |
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Fuchs, Fabian (ZEA-2) |
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Fleitmann, Sarah (ZEA-2) |
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Distributor: |
Jülich DATA |
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Access Authority: |
Hader, Fabian |
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Depositor: |
Hader, Fabian |
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Date of Deposit: |
2024-10-09 |
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Study Scope |
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Keywords: |
Computer and Information Science, Engineering, Simulation, Quantum Dots, Charge-Stability-Diagram, CSD |
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Abstract: |
<h1>Dataset: SimCATS_GaAs_v1_random_variations_v2</h1> <p>Simulated data from the geometric SimCATS model (<a title="SimCATS GitHub Repository" href="https://github.com/f-hader/SimCATS" target="_blank" rel="noopener">GitHub Repository</a>, <a title="SimCATS Paper" href="https://ieeexplore.ieee.org/document/10640289" target="_blank" rel="noopener">Paper</a>) for benchmarking of semiconductor quantum dot tuning algorithms.</p> <p>Generated using <a title="Jupyter Notebook: Dataset Generation" href="https://github.com/f-hader/SimCATS-Datasets/blob/v2.4.0/notebooks/dataset_gen%5Brandom_variations%5D.ipynb" target="_blank" rel="noopener">this Jupyter Notebook</a> and used for the final evaluation in <a title="Automated Charge Transition Detection in Quantum Dot Charge Stability Diagrams" href="https://doi.org/10.36227/techrxiv.172963185.53119182/v1" target="_blank" rel="noopener">Automated Charge Transition Detection in Quantum Dot Charge Stability Diagrams</a>.</p> <h2>Key Facts</h2> <ul> <li>Contains pink, white & random telegraph noise, transition blurring, and dot jumps</li> <li>Random variations of charge transitions, sensor, and distortions</li> <li>1.000 randomly sampled configurations with 100 CSDs each (in total: 100.000 CSDs) </li> </ul> <h2>Usage</h2> <p>To load the data, e.g. for calculating metrics, please have a look at SimCATS-Datasets (<a title="SimCATS-Datasets GitHub Repository" href="https://github.com/f-hader/SimCATS-Datasets" target="_blank" rel="noopener">GitHub Repository</a>, <a title="ReadTheDocs" href="https://simcats-datasets.readthedocs.io/" target="_blank" rel="noopener">ReadTheDocs</a>). The dataset can be loaded as numpy arrays using the function <a title="load_dataset documentation" href="https://simcats-datasets.readthedocs.io/en/latest/autoapi/simcats_datasets/loading/index.html#simcats_datasets.loading.load_dataset" target="_blank" rel="noopener">load_dataset</a> or as PyTorch Dataset class (for machine learning purposes) using the class <a title="SimcatsDataset documentation" href="https://simcats-datasets.readthedocs.io/en/latest/autoapi/simcats_datasets/loading/pytorch/index.html#simcats_datasets.loading.pytorch.SimcatsDataset" target="_blank" rel="noopener">SimcatsDataset</a>.</p> |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Notes: |
CC0 Waiver |
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Other Study Description Materials |
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Related Publications |
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Citation |
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Identification Number: |
10.5281/zenodo.13903285 |
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Bibliographic Citation: |
Hader, F. (2024). SimCATS_GaAs_v1_random_variations_v2 [Data set]. Zenodo (Genève: CERN). |