Beecroft Institute for Particle Astrophysics and Cosmology

Abstract:

The Complete Calibration of the Color-Redshift Relation survey (C3R2) is a spectroscopic programme designed to empirically calibrate the galaxy color-redshift relation to the Euclid depth (I_E=24.5), a key ingredient for the success of Stage IV dark energy projects based on weak lensing cosmology. A spectroscopic calibration sample as representative as possible of the galaxies in the Euclid weak lensing sample is being collected, selecting galaxies from a self-organizing map (SOM) representation of the galaxy color space. Here, we present the results of a near-infrared H- and K-bands spectroscopic campaign carried out using the LUCI instruments at the LBT. For a total of 251 galaxies, we present new highly-reliable redshifts in the 1.3<= z <=1.7 and 2<= z<=2.7 ranges. The newly-determined redshifts populate 49 SOM cells which previously contained no spectroscopic measurements and almost double the occupation numbers of an additional 153 SOM cells. A final optical ground-based observational effort is needed to calibrate the missing cells in particular in the redshift range 1.7<= z<=2.7 that lack spectroscopic calibration. In the end, Euclid itself will deliver telluric-free NIR spectra that can complete the calibration...

Abstract:

We apply machine learning (ML), a powerful method for uncovering complex correlations in high-dimensional data, to the galaxy-halo connection of cosmological hydrodynamical simulations. The mapping between galaxy and halo variables is stochastic in the absence of perfect information, but conventional ML models are deterministic and hence cannot capture its intrinsic scatter. To overcome this limitation, we design an ensemble of neural networks with a Gaussian loss function that predict probability distributions, allowing us to model statistical uncertainties in the galaxy-halo connection as well as its best-fitting trends. We extract a number of galaxy and halo variables from the Horizon-AGN and IllustrisTNG100-1 simulations and quantify the extent to which knowledge of some subset of one enables prediction of the other. This allows us to identify the key features of the galaxy-halo connection and investigate the origin of its scatter in various projections. We find that while halo properties beyond mass account for up to 50 per cent of the scatter in the halo-To-stellar mass relation, the prediction of stellar half-mass radius or total gas mass is not substantially improved by adding further halo properties. We also use these results to investigate semi-Analytic models for galaxy size in the two simulations, finding that assumptions relating galaxy size to halo size or spin are not successful.