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Register a new userStress testing the dark energy equation of state imprint on supernova data
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This work determines the degree to which a standard Lambda-CDM analysis based on type Ia supernovae can identify deviations from a cosmological constant in the form of a redshift-dependent dark energy equation of state w(z). We introduce and apply a novel random curve generator to simulate instances of w(z) from constraint families with increasing distinction from a cosmological constant. After producing a series of mock catalogs of binned type Ia supernovae corresponding to each w(z) curve, we perform a standard Lambda-CDM analysis to estimate the corresponding posterior densities of the absolute magnitude of type Ia supernovae, the present-day matter density, and the equation of state parameter. Using the Kullback-Leibler divergence between posterior densities as a difference measure, we demonstrate that a standard type Ia supernova cosmology analysis has limited sensitivity to extensive redshift dependencies of the dark energy equation of state. In addition, we report that larger redshift-dependent departures from a cosmological constant do not necessarily manifest easier-detectable incompatibilities with the Lambda-CDM model. Our results suggest that physics beyond the standard model may simply be hidden in plain sight.
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We combine recent measurements of Cosmic Microwave Background Anisotropies, Supernovae luminosity distances and Baryonic Acoustic Oscillations to derive constraints on the dark energy equation of state w in the redshift range 0<z<2, using a principal components approach. We find no significant deviations from the expectations of a cosmological constant. However, combining the datasets we find slight indication for w<-1 at low redshift, thus highlighting how these datasets prefer a non-constant w. Nevertheless the cosmological constant is still in agreement with these observations, while we find that some classes of alternative models may be in tension with the inferred w(z) behaviour.
Data-driven model-independent reconstructions of the dark energy equation of state $w(z)$ are presented using Planck 2015 era CMB, BAO, SNIa and Lyman-$alpha$ data. These reconstructions identify the $w(z)$ behaviour supported by the data and show a bifurcation of the equation of state posterior in the range $1.5{<}z{<}3$. Although the concordance $Lambda$CDM model is consistent with the data at all redshifts in one of the bifurcated spaces, in the other a supernegative equation of state (also known as `phantom dark energy) is identified within the $1.5 sigma$ confidence intervals of the posterior distribution. To identify the power of different datasets in constraining the dark energy equation of state, we use a novel formulation of the Kullback--Leibler divergence. This formalism quantifies the information the data add when moving from priors to posteriors for each possible dataset combination. The SNIa and BAO datasets are shown to provide much more constraining power in comparison to the Lyman-$alpha$ datasets. Further, SNIa and BAO constrain most strongly around redshift range $0.1-0.5$, whilst the Lyman-$alpha$ data constrains weakly over a broader range. We do not attribute the supernegative favouring to any particular dataset, and note that the $Lambda$CDM model was favoured at more than $2$ log-units in Bayes factors over all the models tested despite the weakly preferred $w(z)$ structure in the data.
Cosmic voids and their corresponding redshift-aggregated projections of mass densities, known as troughs, play an important role in our attempt to model the large-scale structure of the Universe. Understanding these structures leads to tests comparing the standard model with alternative cosmologies, constraints on the dark energy equation of state, and provides evidence to differentiate among gravitational theories. In this paper, we extend the subspace-constrained mean shift algorithm, a recently introduced method to estimate density ridges, and apply it to 2D weak-lensing mass density maps from the Dark Energy Survey Y1 data release to identify curvilinear filamentary structures. We compare the obtained ridges with previous approaches to extract trough structure in the same data, and apply curvelets as an alternative wavelet-based method to constrain densities. We then invoke the Wasserstein distance between noisy and noiseless simulations to validate the denoising capabilities of our method. Our results demonstrate the viability of ridge estimation as a precursor for denoising weak lensing quantities to recover the large-scale structure, paving the way for a more versatile and effective search for troughs.
The observed galaxy power spectrum acquires relativistic corrections from lightcone effects, and these corrections grow on very large scales. Future galaxy surveys in optical, infrared and radio bands will probe increasingly large wavelength modes and reach higher redshifts. In order to exploit the new data on large scales, an accurate analysis requires inclusion of the relativistic effects. This is especially the case for primordial non-Gaussianity and for extending tests of dark energy models to horizon scales. Here we investigate the latter, focusing on models where the dark energy interacts non-gravitationally with dark matter. Interaction in the dark sector can also lead to large-scale deviations in the power spectrum. If the relativistic effects are ignored, the imprint of interacting dark energy will be incorrectly identified and thus lead to a bias in constraints on interacting dark energy on very large scales.
The standard model of cosmology, the LCDM model, robustly predicts the existence of a multitude of dark matter subhaloes around galaxies like the Milky Way. A wide variety of observations have been proposed to look for the gravitational effects such subhaloes would induce in observable matter. Most of these approaches pertain to the stellar or cool gaseous phases of matter. Here we propose a new approach, which is to search for the perturbations that such dark subhaloes would source in the warm/hot circumgalactic medium (CGM) around normal galaxies. With a combination of analytic theory, carefully-controlled high-resolution idealised simulations, and full cosmological hydrodynamical simulations (the ARTEMIS simulations), we calculate the expected signal and how it depends on important physical parameters (subhalo mass, CGM temperature, and relative velocity). We find that dark subhaloes enhance both the local CGM temperature and density and, therefore, also the pressure. For the pressure and density, the fluctuations can vary in magnitude from tens of percent (for subhaloes with M_sub=10^10 Msun) to a few percent (for subhaloes with M_sub=10^8 Msun), although this depends strongly on the CGM temperature. The subhaloes also induce fluctuations in the velocity field ranging in magnitude from a few km/s up to 25 km/s. We propose that X-ray, Sunyaev-Zeldovich effect, radio dispersion measure, and quasar absorption line observations can be used to measure these fluctuations and place constraints on the abundance and distribution of dark subhaloes, thereby placing constraints on the nature of dark matter.
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