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1 to 4 of 4 Results

SimCATS_GaAs_v1_random_variations_v2 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 [Upcoming Paper]. K...
Data supporting manuscript "NoC Simulation steered by NEST: McAERsim and a Noxim Patch" 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...
SimCATS-Datasets 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...
Replication Data for: On Noise-Sensitive Automatic Tuning of Gate-Defined Sensor Dots 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

SimCATS_GaAs_v1_random_variations_v2

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 [Upcoming Paper]. K...

Data supporting manuscript "NoC Simulation steered by NEST: McAERsim and a Noxim Patch"

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...

SimCATS-Datasets

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...

Replication Data for: On Noise-Sensitive Automatic Tuning of Gate-Defined Sensor Dots

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

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