Characterizing the impact of photometric redshift uncertainties on dark energy constraints from LSST using analytic nuisance parameter marginalization

Joseph Santos

Galaxy clustering and weak gravitational lensing data can be used to measure a range of cosmological parameters describing the universe’s contents and evolution. To infer these cosmological parameters using photometric large-scale structure data, observational and astrophysical sources of uncertainty must be taken into account. In practice, this means that many nuisance parameters are included in the analysis, alongside a smaller number of cosmological parameters. Sampling these nuisance parameters with traditional rejection sampling methods is computationally intensive and time consuming. One way to obtain the cosmological parameter constraints more efficiently is to use analytical approximation methods to efficiently marginalize over the nuisance parameters. We use analytic marginalization to study the effects of redshift uncertainties on dark energy constraints from an LSST-like experiment, and compare the results with those obtained by directly sampling the nuisance parameters. 

 

This poster will be displayed on Monday and Tuesday.

 

Career Stage: 
Undergrad Student