Paper detail

Testing the dark energy with gravitational lensing statistics

We study the redshift distribution of two samples of early-type gravitational lenses, extracted from a larger collection of 122 systems, to constrain the cosmological constant in the LCDM model and the parameters of a set of alternative dark energy models (XCDM, Dvali-Gabadadze-Porrati and Ricci dark energy models), under a spatially flat universe. The likelihood is maximized for $Ω_Λ= 0.70 \pm 0.09$ when considering the sample excluding the SLACS systems (known to be biased towards large image-separation lenses) and no-evolution, and $Ω_Λ= 0.81\pm 0.05$ when limiting to gravitational lenses with image separation larger than 2" and no-evolution. In both cases, results accounting for galaxy evolution are consistent within 1$σ$. The present test supports the accelerated expansion, by excluding the null-hypothesis (i.e., $Ω_Λ= 0 $) at more than 4$σ$, regardless of the chosen sample and assumptions on the galaxy evolution. A comparison between competitive world models is performed by means of the Bayesian information criterion. This shows that the simplest cosmological constant model - that has only one free parameter - is still preferred by the available data on the redshift distribution of gravitational lenses. We perform an analysis of the possible systematic effects, finding that the systematic errors due to sample incompleteness, galaxy evolution and model uncertainties approximately equal the statistical errors, with present-day data. We find that the largest sources of systemic errors are the dynamical normalization and the high-velocity cut-off factor, followed by the faint-end slope of the velocity dispersion function.

preprint2012arXivOpen access

Signal facts

What is known right now

Open access3 authors1 topic

Next steps

Decide what to do with this paper

Use like or dislike for the fast social read. The more specific scholarly feedback stays available below when needed.

Log in to curate

Reading frame

Keep the important context close to the paper

Keep the important signals around this paper in one place: votes, save state, collection context, reviews and the metadata you need before deciding what to do next.

Institutions

Add specific reaction

Move through the context

Research map

Open full explorer

Move through nearby people, institutions, topics and adjacent work without leaving the paper page.

Building this map preview

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Structured reviews

0 review(s)

ContributeLeave structured feedbackUse the review template when you have a concrete strength, concern or method question.Open review form

No structured reviews yet. High-signal critique starts here.

Work discussion

0 comment(s)

DiscussAdd a high-signal commentKeep quick notes, caveats and replication pointers separate from formal reviews.Open comment form

No discussion yet. The first strong comment sets the tone.