J-PAS: Forecasts for dark matter - dark energy elastic couplings
David Figueruelo, Miguel Aparicio Resco, Florencia A. Teppa Pannia,, Jose Beltr\'an Jim\'enez, Dario Bettoni, Antonio L. Maroto, L. Raul Abramo,, Jailson Alcaniz, Narciso Benitez, Silvia Bonoli, Saulo Carneiro, Javier, Cenarro, David Crist\'obal-Hornillos, Renato A. Dupke

TL;DR
This paper investigates a cosmological model with dark matter-dark energy coupling affecting momentum transfer, confirming previous evidence of such coupling and forecasting future survey capabilities to detect it with high significance.
Contribution
The study provides the first forecast for J-PAS data on dark matter-dark energy coupling, demonstrating its potential to detect or constrain the interaction with high confidence.
Findings
Current data favor a non-zero coupling at over 3σ, mainly driven by Sunyaev-Zeldovich observations.
Future J-PAS clustering measurements can detect the coupling at more than 10σ significance.
Weak lensing measurements do not significantly improve constraints on the coupling parameter.
Abstract
We consider a cosmological model where dark matter and dark energy feature a coupling that only affects their momentum transfer in the corresponding Euler equations. We perform a fit to cosmological observables and confirm previous findings within these scenarios that favour the presence of a coupling at more than . This improvement is driven by the Sunyaev-Zeldovich data. We subsequently perform a forecast for future J-PAS data and find that clustering measurements will permit to clearly discern the presence of an interaction within a few percent level with the uncoupled case at more than when the complete survey, covering sq. deg., is considered. We found that the inclusion of weak lensing measurements will not help to further constrain the coupling parameter. For completeness, we compare to forecasts for DESI and Euclid, which provide similar discriminating…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
