Null tests of the cosmological constant using supernovae

TL;DR

This paper develops null tests based on supernova luminosity distances to verify if dark energy is a cosmological constant, using Gaussian Processes for model-independent derivative extraction, and assesses future survey capabilities.

Contribution

It introduces a novel null test approach for the cosmological constant using supernova data and Gaussian Processes, and evaluates the potential of upcoming surveys to improve this test.

Findings

Current data is consistent with the cosmological constant but has large uncertainties.

Future surveys like DES can significantly tighten null test constraints under flat universe assumptions.

Allowing for curvature reduces the test's effectiveness, highlighting the importance of spatial flatness.

Abstract

The standard concordance model of the Universe is based on the cosmological constant as the driver of accelerating expansion. This concordance model is being subjected to a growing range of inter-locking observations. In addition to using generic observational tests, one can also design tests that target the specific properties of the cosmological constant. These null tests do not rely on parametrisations of observables, but focus on quantities that are constant only if dark energy is a cosmological constant. We use supernova data in null tests that are based on the luminosity distance. In order to extract derivatives of the distance in a model-independent way, we use Gaussian Processes. We find that the concordance model is compatible with the Union 2.1 data, but the error bars are fairly large. Simulated datasets are generated for the DES supernova survey and we show that this survey will allow for a sharper null test of the cosmological constant if we assume the Universe is flat. Allowing for spatial curvature degrades the power of the null test.