Citing, credits, and licence
Before using the CosmoGridV1 data, please read this page carefully.
Citing CosmoGridV1
If you use this dataset for any publication, please cite the following papers: Kacprzak and Fluri et al. 2022 and Fluri et al. 2022:
@ARTICLE{2209.04662,
author = { {Kacprzak}, Tomasz and {Fluri}, Janis and {Schneider}, Aurel and {Refregier}, Alexandre and {Stadel}, Joachim},
title = "{CosmoGridV1: a simulated wCDM theory prediction for map-level cosmological inference}",
journal = {arXiv e-prints},
year = 2022,
month = sep,
eid = {arXiv:2209.04662},
pages = {arXiv:2209.04662},
archivePrefix = {arXiv},
eprint = {2209.04662},
primaryClass = {astro-ph.CO},
year = 2022}
@article{PhysRevD.105.083518,
title = {Full $w\mathrm{CDM}$ analysis of KiDS-1000 weak lensing maps using deep learning},
author = { Fluri, Janis and Kacprzak, Tomasz and Lucchi, Aurelien and Schneider, Aurel and Refregier, Alexandre and Hofmann, Thomas},
journal = {Phys. Rev. D},
volume = {105},
issue = {8},
pages = {083518},
numpages = {22},
year = {2022},
month = {Apr},
publisher = {American Physical Society},
doi = {10.1103/PhysRevD.105.083518},
url = {https://link.aps.org/doi/10.1103/PhysRevD.105.083518}}
Credits
CosmoGridV1 was created by Janis Fluri, Tomasz Kacprzak, Aurel Schneider, Alexandre Refregier, and Joachim Stadel at the ETH Zurich and the University of Zurich. The simulations were run at the Swiss Supercomputing Center (CSCS) as a part of the large production project “Measuring Dark Energy with Deep Learning”.
Licence
This work is licensed under a Creative Commons Attribution 4.0 International License.
Summary of the licence:
You are free to:
Share — copy and redistribute the material in any medium or format
Adapt — remix, transform, and build upon the material for any purpose, even commercially.
Under the following terms:
Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.