Categorizing models using Self-Organizing Maps: an application to modified gravity theories probed by cosmic shear
Abstract
We propose to use Self-Organizing Maps (SOM) to map the impact of physical models onto observables. Using this approach, we are able to determine how theories relate to each other given their signatures. In cosmology this will be particularly useful to determine cosmological models (such as dark energy, modified gravity or inflationary models) that should be tested by the new generation of experiments. As a first example, we apply this approach to the representation of a subset of the space of modified gravity theories probed by cosmic shear. We therefore train a SOM on shear correlation functions in the f(R), dilaton and symmetron models. The results indicate these three theories have similar signatures on shear for small values of their parameters but the dilaton has different signature for higher values. We also show that modified gravity (especially the dilaton model) has a different impact on cosmic shear compared to a dynamical dark energy so both need to be tested by galaxy surveys.
Additional Information
Attribution 4.0 International (CC BY 4.0) The research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004). In particular, this work was initiated with a JPL Data Science Pilot grant under a program run by Daniel Crichton and Richard Doyle who provided early support and advice. PLT acknowledges support for this work from a NASA Postdoctoral Program Fellowship. BM was supported by the JPL/Caltech Summer Undergraduate Research Fellowship Program. AF would like to thank Benjamin Giblin for indicating an issue in the implementation of MGCAMB in CosmoSIS to compute f(R) gravity cosmic shear predictions and Joe Zuntz for his help to fix this issue; Xiao Fang for help with CosmoCov; members of the JPL Dark Sector group and of the cosmology group at Caltech for their support and inputs; and early audiences of this work for useful discussions.Attached Files
Submitted - 2110.13171.pdf
Files
Name | Size | Download all |
---|---|---|
md5:24fd689c3b5b5b04c612a55a337a9999
|
834.8 kB | Preview Download |
Additional details
- Eprint ID
- 113724
- Resolver ID
- CaltechAUTHORS:20220304-171244005
- NASA/JPL/Caltech
- 80NM0018D0004
- NASA Postdoctoral Program
- Caltech Summer Undergraduate Research Fellowship (SURF)
- Created
-
2022-03-07Created from EPrint's datestamp field
- Updated
-
2022-03-07Created from EPrint's last_modified field
- Caltech groups
- Infrared Processing and Analysis Center (IPAC)