Beyond dark energy Fisher forecasts: how DESI will constrain LCDM and quintessence models
Samuel Goldstein, Minsu Park, Marco Raveri, Bhuvnesh Jain, Lado, Samushia

TL;DR
This paper forecasts how DESI will enhance constraints on the standard cosmological model and quintessence dark energy models, using formalism and non-parametric reconstruction methods, showing significant improvements over current data.
Contribution
It introduces a formalism for extracting key parameter combinations and applies non-parametric reconstruction to forecast DESI's impact on dark energy models.
Findings
DESI will double the precision of key cosmological parameters.
DESI significantly improves constraints on quintessence properties.
Angular diameter distance measurements are especially constraining.
Abstract
We baseline with current cosmological observations to forecast the power of the Dark Energy Spectroscopic Instrument (DESI) in two ways: 1. the gain in constraining power of parameter combinations in the standard CDM model, and 2. the reconstruction of quintessence models of dark energy. For the former task we use a recently developed formalism to extract the leading parameter combinations constrained by different combinations of cosmological survey data. For the latter, we perform a non-parametric reconstruction of quintessence using the Effective Field Theory of Dark Energy. Using mock DESI observations of the Hubble parameter, angular diameter distance, and growth rate, we find that DESI will provide significant improvements over current datasets on CDM and quintessence constraints. Including DESI mocks in our CDM analysis improves constraints on…
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Taxonomy
TopicsComplex Systems and Time Series Analysis
