Beecroft Institute for Particle Astrophysics and Cosmology

Abstract:

We present a new method to marginalize over uncertainties in redshift distributions, N(z), within tomographic cosmological analyses applicable to current and upcoming photometric galaxy surveys. We allow for arbitrary deviations from the best-guess N(z) governed by a general covariance matrix describing the uncertainty in our knowledge of redshift distributions. In principle, this is marginalization over hundreds or thousands of new parameters describing potential deviations as a function of redshift and tomographic bin. However, by linearly expanding the theory predictions around a fiducial model, this marginalization can be performed analytically, resulting in a modified data covariance matrix that effectively downweights the modes of the data vector that are more sensitive to redshift distribution variations. We showcase this method by applying it to the galaxy clustering measurements from the Hyper Suprime-Cam first data release. We illustrate how to marginalize over sample-variance of the calibration sample and a large general systematic uncertainty in photometric estimation methods, and explore the impact of priors imposing smoothness in the redshift distributions.

Abstract:

The interplay of star formation (SF) and supernova (SN) feedback in galaxy formation is a key element for understanding galaxy evolution. Since these processes occur at small scales, it is necessary to have sub-grid models that recover their evolution and environmental effects at the scales reached by cosmological simulations. In this work, we present the results of the Mochima simulation, where we simulate the same spiral galaxy inhabiting a Milky Way (MW) size halo in a cosmological environment changing the sub-grid models for SN feedback and SF. We test combinations of the Schmidt law and a multifreefall based SF with delayed cooling feedback or mechanical feedback. We reach a resolution of 35 pc in a zoom-in box of 36 Mpc. For this, we use the code RAMSES with the implementation of gas turbulence in time and trace the local hydrodynamical features of the star-forming gas. Finally, we compare the galaxies at redshift 0 with global and interstellar medium observations in the MW and local spiral galaxies. The simulations show successful comparisons with observations. Nevertheless, diverse galactic morphologies are obtained from different numerical implementations. We highlight the importance of detailed modelling of the SF and feedback processes, especially for simulations with a resolution that start to reach scales relevant for molecular cloud physics. Future improvements could alleviate the degeneracies exhibited in our simulated galaxies under different sub-grid models.