ChangHoon Hahn

[ChangHoon Hahn @ChanghoonHahn]

Excited to announce that our latest #SimBIG collaboration research has just been published in @NatureAstronomy 🔭✨!
#Astronomy #Cosmology #NatureAstronomy

[Nature Astronomy @NatureAstronomy]

By extracting non-Gaussian cosmological information on galaxy clustering at non-linear scales, a framework for cosmic inference (SimBIG) provides precise constraints for testing cosmological models. @ChanghoonHahn @cosmo_shirley @DavidSpergel et al.: https://t.co/lXiOSKc8T8

[ChangHoon Hahn @ChanghoonHahn]

Check out also the #SimBIG team's latest @PhysRevD! We use #SimBIG to analyze:
- the bispectrum https://t.co/Ive3x1oyFQ
- wavelet scattering transform https://t.co/8nUHplICTj
- convolutional neural networks https://t.co/wUI1qWAeKl
- skew spectra https://t.co/lBm4jckHsv

[ChangHoon Hahn @ChanghoonHahn]

Excited to announce that our latest #SimBIG collaboration research has just been published in @NatureAstronomy 🔭✨!
#Astronomy #Cosmology #NatureAstronomy

[Nature Astronomy @NatureAstronomy]

By extracting non-Gaussian cosmological information on galaxy clustering at non-linear scales, a framework for cosmic inference (SimBIG) provides precise constraints for testing cosmological models. @ChanghoonHahn @cosmo_shirley @DavidSpergel et al.: https://t.co/lXiOSKc8T8

[ChangHoon Hahn @ChanghoonHahn]

Huge thanks to the incredible #SimBIG team for making this happen! @PabloLemosP, @liamhparker, @BrunoRegaldo, @meickenberg, @cosmo_shirley, @jiamin_hou, @ElenaMassara, @chmod_i, @DavidSpergel

https://t.co/r5G0dua6c5