Grad Talk- Detecting Internal Tension within the Dark Energy Survey Year 1 (DES-Y1) Analysis

Paul Rogozenski, University of Arizona

When

2 – 3 p.m., Feb. 21, 2020

Where

Abstract: The Bayesian evidence ratio has been used as a tool to check the statistical consistency between different experiments, of which the most common quantifier is the Jeffreys scale. However, the evidence ratio is prior-biased; priors can regularly be arranged to support agreement between datasets and may require further calibration to denote the degree of tension observed. In this talk, we examine evidence ratios in a DES-Y1 simulated analysis, focusing on the internal consistency between simulated weak lensing and galaxy clustering measurements. We first calibrate the expected evidence ratio distribution given noise realizations around the best fit DES-Y1 ΛCDM cosmology. We then show the behavior of the evidence ratio for noiseless fiducial data vectors simulated using modified gravity models studied in the DES-Y1 extension project. We show that prior boundaries could conceal the discrepancies between weak lensing and galaxy clustering induced by such models.    
 
** Refreshments served from 2:45pm – 3:00pm in PAS 218. Please join us for the colloquium in PAS 224. Thank you. **