Challenges to the DGP Model from Horizon-Scale Growth and Geometry
Wenjuan Fang, Sheng Wang, Wayne Hu, Zoltan Haiman, Lam Hui, Morgan May

TL;DR
This study tests the DGP braneworld gravity model against cosmological data, finding significant tensions with observations that challenge its viability as an alternative to dark energy.
Contribution
The paper provides a comprehensive MCMC analysis of the DGP model using multiple cosmological datasets, revealing its inability to reconcile growth and distance measures.
Findings
DGP model fits are significantly worse than Lambda CDM.
Growth and distance measure tensions cannot be alleviated simultaneously.
Modifications to initial conditions conflict with polarization data.
Abstract
We conduct a Markov Chain Monte Carlo study of the Dvali-Gabadadze-Porrati (DGP) self-accelerating braneworld scenario given the cosmic microwave background (CMB) anisotropy, supernovae and Hubble constant data by implementing an effective dark energy prescription for modified gravity into a standard Einstein-Boltzmann code. We find no way to alleviate the tension between distance measures and horizon scale growth in this model. Growth alterations due to perturbations propagating into the bulk appear as excess CMB anisotropy at the lowest multipoles. In a flat cosmology, the maximum likelihood DGP model is nominally a 5.3 sigma poorer fit than Lambda CDM. Curvature can reduce the tension between distance measures but only at the expense of exacerbating the problem with growth leading to a 4.8 sigma result that is dominated by the low multipole CMB temperature spectrum. While changing…
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.
