CCAPP Seminar: Georgios Valogiannis (UChicago)

Valogiannis
January 23, 2024
12:00PM - 2:00PM
PRB 4138 & Zoom

Date Range
2024-01-23 12:00:00 2024-01-23 14:00:00 CCAPP Seminar: Georgios Valogiannis (UChicago) Speaker: Georgios ValogiannisPrecise Cosmological Constraints from BOSS Galaxy Clustering using the Wavelet Scattering TransformOptimal extraction of the non-Gaussian information encoded in the Large-Scale Structure (LSS) of the universe lies at the forefront of modern precision cosmology. In this talk, I will discuss recent efforts to achieve this task using the Wavelet Scattering Transform (WST), which subjects an input field to a layer of non-linear transformations that are sensitive to non-Gaussianity through a generated set of WST coefficients. In order to assess its applicability in the context of LSS surveys, I will present the first WST application to actual galaxy observations, through a WST re-analysis of the BOSS DR12 CMASS dataset. After laying out the procedure on how to capture all necessary layers of realism for an application to data obtained from a spectroscopic survey, I will show results for the marginalized posterior probability distributions of multiple cosmological parameters obtained from a likelihood analysis of the CMASS data. A joint WST+ 2-point correlation function (2pcf) analysis is found to deliver a substantial improvement in the values of the predicted 1σ errors compared to the regular 2pcf-only analysis, highlighting the exciting prospect of employing higher-order statistics in order to fully exploit the potential of upcoming Stage-IV spectroscopic observations.  PRB 4138 & Zoom America/New_York public

Speaker: Georgios Valogiannis

Precise Cosmological Constraints from BOSS Galaxy Clustering using the Wavelet Scattering Transform

Optimal extraction of the non-Gaussian information encoded in the Large-Scale Structure (LSS) of the universe lies at the forefront of modern precision cosmology. In this talk, I will discuss recent efforts to achieve this task using the Wavelet Scattering Transform (WST), which subjects an input field to a layer of non-linear transformations that are sensitive to non-Gaussianity through a generated set of WST coefficients. In order to assess its applicability in the context of LSS surveys, I will present the first WST application to actual galaxy observations, through a WST re-analysis of the BOSS DR12 CMASS dataset. After laying out the procedure on how to capture all necessary layers of realism for an application to data obtained from a spectroscopic survey, I will show results for the marginalized posterior probability distributions of multiple cosmological parameters obtained from a likelihood analysis of the CMASS data. A joint WST+ 2-point correlation function (2pcf) analysis is found to deliver a substantial improvement in the values of the predicted 1σ errors compared to the regular 2pcf-only analysis, highlighting the exciting prospect of employing higher-order statistics in order to fully exploit the potential of upcoming Stage-IV spectroscopic observations. 

Events Filters: