Modeling Neutrino-Induced Scale-Dependent Galaxy Clustering for Photometric Galaxy Surveys

The increasing statistical precision of photometric redshift surveys requires improved accuracy of theoretical predictions for large-scale structure observables to obtain unbiased cosmological constraints. In $\Lambda$CDM cosmologies, massive neutrinos stream freely at small cosmological scales, suppressing the small-scale power spectrum. In massive neutrino cosmologies, galaxy bias modeling needs to accurately relate the scale-dependent growth of the underlying matter field to observed galaxy clustering statistics. In this work, we implement a computationally efficient approximation of the neutrino-induced scale-dependent bias (NISDB). Through simulated likelihood analyses of Dark Energy Survey Year 3 (DESY3) and Legacy Survey of Space and Time Year 1 (LSSTY1) synthetic data that contain an appreciable NISDB, we examine the impact of linear galaxy bias and neutrino mass modeling choices on cosmological parameter inference. We find model misspecification of the NISDB approximation and neutrino mass models to decrease the constraining power of photometric galaxy surveys and cause parameter biases in the cosmological interpretation of future surveys. We quantify these biases and devise mitigation strategies.Comment: 23 pages, 5 figure

Constraining Neutrino Properties through Photometric Large-Scale Structure Surveys

The standard model of cosmology, ΛCDM, has shown great flexibility in accurately modeling observations across cosmic time. The increased statistical precision of cosmological surveys in the early 21st century, however, has uncovered potential tensions in cosmological constraints between early- and late-time observables. These tensions can either indicate the breakdown of ΛCDM and require new physics to reconcile observations, or can be induced by insufficient modeling of systematic uncertainties. In this thesis, we primarily focus on the role neutrino-like particles play in cosmological constraints of large-scale structure (LSS) observations. We first summarize the standard model of cosmology, the modeling of neutrinos within ΛCDM, and how LSS surveys (i.e. the Dark Energy Survey and the Legacy Survey of Space and Time) relate observables to the underlying cosmological model. We then take a closer look at the analysis choices of LSS surveys and consider a range of factors that impact consistency checks of the standard model, including: the robustness of Bayesian methods in quantifying tensions, the role of neutrinos in suppressing the small-scale growth of structure, and the impact of additional sterile neutrinos on cosmological constraints. Through these analyses, we address sources of modeling concern and offer new techniques to accurately and precisely account for the impact of both standard-model and sterile neutrinos in LSS observations. We find that current LSS surveys can be more precise with improved models and that current modeling choices can lead to systematic biases of future LSS cosmological constraints