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1 to 10 of 276 Results
Oct 9, 2024
Hader, Fabian; Fuchs, Fabian; Fleitmann, Sarah, 2024, "SimCATS_GaAs_v1_random_variations_v2", https://doi.org/10.26165/JUELICH-DATA/5PB3GT, Jülich DATA, V1
Dataset: SimCATS_GaAs_v1_random_variations_v2 Simulated data from the geometric SimCATS model (GitHub Repository, Paper) for benchmarking of semiconductor quantum dot tuning algorithms. Generated using this Jupyter Notebook and used for the final evaluation in Automated Charge Tr...
Oct 2, 2024
Robens, Markus, 2024, "Data supporting manuscript "NoC Simulation steered by NEST: McAERsim and a Noxim Patch"", https://doi.org/10.26165/JUELICH-DATA/JJ31IX, Jülich DATA, V1
This is a wrapper for »Data supporting manuscript "NoC Simulation steered by NEST: McAERsim and a Noxim Patch"« submitted to Zenodo (Robens, 2024) due to its file size. This dataset contains data underlying the results presented in the article Robens M, Kleijnen R, Schiek M, and...
Oct 2, 2024
Hader, Fabian; Fuchs, Fabian; Havemann, Karin; Fleitmann, Sarah; Vogelbruch, Jan, 2024, "SimCATS-Datasets", https://doi.org/10.26165/JUELICH-DATA/SB7L3L, Jülich DATA, V1
SimCATS-Datasets is a Python package that simplifies the creation and loading of SimCATS datasets. For License, CLA, and Copyright have a look at GitHub. GitHub (source code): https://github.com/f-hader/SimCATS-Datasets PyPi (package): https://pypi.org/project/simcats-datasets Re...
Feb 23, 2023 - Campus Collection
Hader, Fabian; Vogelbruch, Jan; Humpohl, Simon; Hangleiter, Tobias; Eguzo, Chimezie; Heinen, Stefan; Meyer, Stefanie; van Waasen, Stefan, 2023, "Replication Data for: On Noise-Sensitive Automatic Tuning of Gate-Defined Sensor Dots", https://doi.org/10.26165/JUELICH-DATA/QIIBZV, Jülich DATA, V1
Sensor dot measurement data (Matlab format) and format description used in the evaluation of IEEE TQE paper: On Noise-Sensitive Automatic Tuning of Gate-Defined Sensor Dots, 2023
Plain Text - 2.5 KB - SHA-256: 718d06bf5a4fc9829c8201ce771e83e68d509ede66d9ef3b432102e2d1cd6937
Markdown Text - 10.3 KB - SHA-256: 97a19bf811dca5225496bb6fabb7e839329bf71ab54ac38017f5ec1705a37517
Markdown Text - 4.3 KB - SHA-256: 64d905a97d94ef39ee7da46212793b86271b0727f910fbfaecaa95499f9f008a
MATLAB Data - 161.7 KB - SHA-256: 321a0eb7fbfbaf69e64f6f26a0e001dc18a1d2da8376dc4b66b5e18cca2e5216
MATLAB Data - 82.1 KB - SHA-256: 4c638e47638c673f6a2a1ba5a8c2f1e880e532fc63d6ef66c9ae421bd90869ba
MATLAB Data - 162.3 KB - SHA-256: 54a2638e1cdb14c639394c8b74ba16169aeb3310bebb793fdfde798aa089adec
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