Speaker
Description
Using data from upcoming (Stage-IV) cosmological surveys, we jointly reconstruct the Universe’s growth and expansion histories using forward modeling and Gaussian Processes. Our approach only relies on a few reasonable assumptions, namely:
- A (flat) Friedmann-Lemaître-Robertson-Walker metric,
- An Einstein De Sitter (matter-dominated) Universe at high redshift.
We forecast the upcoming surveys’ potential to accurately reconstruct the Dark Energy (DE) evolution and thus detect any possible deviation from a cosmological constant. We generate mock data for various alternative DE models and illustrate how our method captures the correct DE behavior in all cases — being capable of distinguishing them from $\Lambda$ at more than 95% C.L.
Finally, we extend our methodology to include possible deviations from General Relativity (GR) at low-$z$, by simultaneously reconstructing the phenomenological function $G_{\rm eff}(z)$ governing the growth of (dust-like) matter density perturbations.
| Secondary category for the parallel session (optional) | Cosmology |
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