# Testing the DGP model with gravitational lensing statistics

Zhu, Z H; Sereno, M (2008). Testing the DGP model with gravitational lensing statistics. Astronomy and Astrophysics, 487(3):831-835.

## Abstract

Aims. The self-accelerating braneworld model (DGP) appears to provide a simple alternative to the standard $\Lambda$CDM cosmology to explain the current cosmic acceleration, which is strongly indicated by measurements of type Ia supernovae, as well as other concordant observations.
Methods. We investigate observational constraints on this scenario provided by gravitational-lensing statistics using the Cosmic Lens All-Sky Survey (CLASS) lensing sample.
Results. We show that a substantial part of the parameter space of the DGP model agrees well with that of radio source gravitational lensing sample.
Conclusions. In the flat case, $\Omega_{\rm K}=0$, the likelihood is maximized, ${\cal L}={\cal L_{\rm max}}$, for $\Omega_{\rm M} = 0.30_^$. If we relax the prior on $\Omega_{\rm K}$, the likelihood peaks at $\{ \Omega_{\rm M},\Omega_{r_{\rm c}} \} \simeq {0.29, 0.12}$, slightly in the region of open models. The confidence contours are, however, elongated such that we are unable to discard any of the close, flat or open models.

## Abstract

Aims. The self-accelerating braneworld model (DGP) appears to provide a simple alternative to the standard $\Lambda$CDM cosmology to explain the current cosmic acceleration, which is strongly indicated by measurements of type Ia supernovae, as well as other concordant observations.
Methods. We investigate observational constraints on this scenario provided by gravitational-lensing statistics using the Cosmic Lens All-Sky Survey (CLASS) lensing sample.
Results. We show that a substantial part of the parameter space of the DGP model agrees well with that of radio source gravitational lensing sample.
Conclusions. In the flat case, $\Omega_{\rm K}=0$, the likelihood is maximized, ${\cal L}={\cal L_{\rm max}}$, for $\Omega_{\rm M} = 0.30_^$. If we relax the prior on $\Omega_{\rm K}$, the likelihood peaks at $\{ \Omega_{\rm M},\Omega_{r_{\rm c}} \} \simeq {0.29, 0.12}$, slightly in the region of open models. The confidence contours are, however, elongated such that we are unable to discard any of the close, flat or open models.

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