Impact of stellar population synthesis choices on forward modelling-based redshift distribution estimates
Luca Tortorelli, Jamie McCullough, Daniel Gruen

TL;DR
This study investigates how different choices in stellar population synthesis models affect the accuracy of galaxy redshift distribution estimates in forward modelling, revealing significant biases that challenge upcoming survey precision requirements.
Contribution
It provides a sensitivity analysis of SPS model choices on redshift distribution estimates, highlighting key biases from specific model components.
Findings
IMF, AGN, gas physics, and attenuation law choices bias redshift distributions
Biases exceed Stage IV survey precision requirements
Variations impact mean and scatter of redshift estimates
Abstract
The forward modelling of galaxy surveys has recently gathered interest as one of the primary methods to achieve the required precision on the estimate of the redshift distributions for stage IV surveys. One of the key aspects of forward modelling a galaxy survey is the connection between the physical properties drawn from a galaxy population model and the intrinsic SEDs, achieved through SPS codes (e.g. FSPS). However, SPS requires a large number of detailed assumptions on the constituents of galaxies, for which the model choice or parameter values are currently uncertain. In this work, we perform a sensitivity study of the impact that the variations of the SED modelling choices have on the mean and scatter of the tomographic galaxy redshift distributions. We assumed the Prospector beta model as the fiducial input galaxy population model and used its SPS parameters to build 9 bands…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsStellar, planetary, and galactic studies · Astronomy and Astrophysical Research · Scientific Research and Discoveries
