4 citations · 4 across the 2 of their papers we have counts for
2 papers
astro-ph.CO2023
LyAl-Net: A high-efficiency Lyman- forest simulation with a neural network
Chotipan Boonkongkird, Guilhem Lavaux, Sebastien Peirani +3
The inference of cosmological quantities requires accurate and large hydrodynamical cosmological simulations. Unfortunately, their computational time can take millions of CPU hours…
astro-ph.CO2023★ 4 cited
Higher-order statistics of the large-scale structure from photometric redshifts
Eleni Tsaprazi, Jens Jasche, Guilhem Lavaux +1
The large-scale structure is a major source of cosmological information. However, next-generation photometric galaxy surveys will only provide a distorted view of cosmic structures…