%0 Generic %1 tessore2023glass %A Tessore, Nicolas %A Loureiro, Arthur %A Joachimi, Benjamin %A von Wietersheim-Kramsta, Maximilian %D 2023 %K tifr %T GLASS: Generator for Large Scale Structure %U http://arxiv.org/abs/2302.01942 %X We present GLASS, the Generator for Large Scale Structure, a new code for the simulation of galaxy surveys for cosmology, which iteratively builds a light cone with matter, galaxies, and weak gravitational lensing signals as a sequence of nested shells. This allows us to create deep and realistic simulations of galaxy surveys at high angular resolution on standard computer hardware and with low resource consumption. GLASS also introduces a new technique to generate transformations of Gaussian random fields (including lognormal) to essentially arbitrary precision, an iterative line-of-sight integration over matter shells to obtain weak lensing fields, and flexible modelling of the galaxies sector. We demonstrate that GLASS readily produces simulated datasets with per cent-level accurate two-point statistics of galaxy clustering and weak lensing, thus enabling simulation-based validation and inference that is limited only by our current knowledge of the input matter and galaxy properties.

@misc{tessore2023glass, abstract = {We present GLASS, the Generator for Large Scale Structure, a new code for the simulation of galaxy surveys for cosmology, which iteratively builds a light cone with matter, galaxies, and weak gravitational lensing signals as a sequence of nested shells. This allows us to create deep and realistic simulations of galaxy surveys at high angular resolution on standard computer hardware and with low resource consumption. GLASS also introduces a new technique to generate transformations of Gaussian random fields (including lognormal) to essentially arbitrary precision, an iterative line-of-sight integration over matter shells to obtain weak lensing fields, and flexible modelling of the galaxies sector. We demonstrate that GLASS readily produces simulated datasets with per cent-level accurate two-point statistics of galaxy clustering and weak lensing, thus enabling simulation-based validation and inference that is limited only by our current knowledge of the input matter and galaxy properties.}, added-at = {2023-02-07T07:08:29.000+0100}, author = {Tessore, Nicolas and Loureiro, Arthur and Joachimi, Benjamin and von Wietersheim-Kramsta, Maximilian}, biburl = {https://www.bibsonomy.org/bibtex/2c61165a71d7ce156f3865be06b142e23/citekhatri}, description = {GLASS: Generator for Large Scale Structure}, interhash = {d1d44113a93bf25439feda5ca873b8e9}, intrahash = {c61165a71d7ce156f3865be06b142e23}, keywords = {tifr}, note = {cite arxiv:2302.01942Comment: 23 pages, 15 figures; prepared for submission to OJA; code available at https://github.com/glass-dev/glass}, timestamp = {2023-02-07T07:08:29.000+0100}, title = {GLASS: Generator for Large Scale Structure}, url = {http://arxiv.org/abs/2302.01942}, year = 2023 }