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Abstract: We apply the technique of parameter-splitting to existing cosmological datasets, to check for a generic failure of dark energy models. Given a dark energyparameter, such as the energy density Omega Lambda or equation of state w, wesplit it into two meta-parameters with one controlling geometrical distances,and the other controlling the growth of structure. Observational data spanningType Ia Supernovae, the cosmic microwave background (CMB), galaxy clustering,and weak gravitational lensing statistics are fit without requiring the twometa-parameters to be equal. This technique checks for inconsistency betweendifferent data sets, as well as for internal inconsistency within any one dataset (e.g., CMB or lensing statistics) that is sensitive to both geometry andgrowth. We find that the cosmological constant model is consistent with currentdata. Theories of modified gravity generally predict a relation between growthand geometry that is different from that of general relativity.Parameter-splitting can be viewed as a crude way to parametrize the space ofsuch theories. Our analysis of current data already appears to put sharp limitson these theories: assuming a flat universe, current data constrain thedifference Omega Lambda(geom) - Omega Lambda(grow) to be -0.0044 +- 0.0058(68% C.L.); allowing the equation of state w to vary, the difference w(geom) -w(grow) is constrained to be 0.37 +- 0.37 (68% C.L.). Interestingly, theregion w(grow) > w(geom), which should be generically favored by theories thatslow structure formation relative to general relativity, is quite restricted bydata already. We find w(grow) < -0.80 at 2 sigma. As an example, the best-fitflat Dvali-Gabadadze-Porrati (DGP) model approximated by our parametrizationlies beyond the 3 sigma contour for constraints from all the data sets.

Autor: Sheng Wang (Brookhaven; Columbia), Lam Hui (Columbia; ISCAP), Morgan May (Brookhaven), Zoltan Haiman (Columbia)


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