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Register a new userRevisiting dark energy models using differential ages of galaxies
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In this work, we use a test based on the differential ages of galaxies for distinguishing the dark energy models. As proposed by Jimenez and Loeb, relative ages of galaxies can be used to put constraints on various cosmological parameters. In the same vein, we reconstruct $H_0dt/dz$ and its derivative ($H_0d^2t/dz^2$) using a model independent technique called non-parametric smoothing. Basically, $dt/dz$ is the change in the age of the object as a function of redshift which is directly link with the Hubble parameter. Hence for reconstruction of this quantity, we use the most recent $H(z)$ data. Further, we calculate $H_0dt/dz$ and its derivative for several models like Phantom, Einstein de Sitter (EdS), $Lambda$CDM, Chevallier-Polarski-Linder (CPL) parametrization, Jassal-Bagla-Padmanabhan (JBP) parametrization and Feng-Shen-Li-Li (FSLL) parametrization. We check the consistency of these models with the results of reconstruction obtained in model independent way from the data. It is observed that $H_0dt/dz$ as a tool is not able to distinguish between the $Lambda$CDM, CPL, JBP and FSLL parametrizations but as expected EdS and Phantom models show noticeable deviation from the reconstructed results. Further, the derivative of $H_0dt/dz$ for various dark energy models is more sensitive at low redshift. It is observed that the FSLL model is not consistent with the reconstructed results at redshifts less than $0.5$, however, the $Lambda$CDM model is in concordance with the 3$sigma$ region of the reconstruction.
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This work uses a combination of a variational auto-encoder and generative adversarial network to compare different dark energy models in light of observations, e.g., the distance modulus from type Ia supernovae. The network finds an analytical variational approximation to the true posterior of the latent parameters in the models, yielding consistent model comparison results with those derived by the standard Bayesian method, which suffers from a computationally expensive integral over the parameters in the product of the likelihood and the prior. The parallel computational nature of the network together with the stochastic gradient descent optimization technique leads to an efficient way to compare the physical models given a set of observations. The converged network also provides interpolation for a dataset, which is useful for data reconstruction.
Model independent reconstructions of dark energy have received some attention. The approach that addresses the reconstruction of the dimensionless coordinate distance and its two first derivatives using a polynomial fit in different redshift windows is well developed cite{DalyDjorgovski1,DalyDjorgovski2,DalyDjorgovski3}. In this work we offer new insights into the problem by focusing on two types of observational probes: SNeIa and GRBs. Our results allow to highlight some of the intrinsic weaknesses of the method. One of the directions we follow is to consider updated observational samples. Our results indicate than conclusions on the main dark energy features as drawn from this method are intimately related to the features of the samples themselves (which are not quite ideal). This is particularly true of GRBs, which manifest themselves as poor performers in this context. In contrast to original works, we conclude they cannot be used for cosmological purposes, and the state of the art does not allow to regard them on the same quality basis as SNeIa. The next direction we contribute to is the question of how the adjusting of some parameters (window width, overlap, selection criteria) affect the results. We find again there is a considerable sensitivity to these features. Then, we try to establish what is the current redshift range for which one can make solid predictions on dark energy evolution. Finally, we strengthen the former view that this model is modest in the sense it provides only a picture of the global trend. But, on the other hand, we believe it offers an interesting complement to other approaches given that it works on minimal assumptions.
The distribution of angles subtended between pairs of galaxies and the line of sight,which is uniform in real space, is distorted by their peculiar motions, and has been proposed as a probe of cosmic expansion. We test this idea using N-body simulations of structure formation in a cold dark matter universe with a cosmological constant and in two variant cosmologies with different dark energy models. We find that the distortion of the distribution of angles is sensitive to the nature of dark energy. However, for the first time, our simulations also reveal dependences of the normalization of the distribution on both redshift and cosmology that have been neglected in previous work. This introduces systematics that severely limit the usefulness of the original method. Guided by our simulations, we devise a new, improved test of the nature of dark energy. We demonstrate that this test does not require prior knowledge of the background cosmology and that it can even distinguish between models that have the same baryonic acoustic oscillations and dark matter halo mass functions. Our technique could be applied to the completed BOSS galaxy redshift survey to constrain the expansion history of the Universe to better than 2%. The method will also produce different signals for dark energy and modified gravity cosmologies even when they have identical expansion histories, through the different peculiar velocities induced in these cases.
We consider the capabilities of current and future large facilities operating at 2,mm to 3,mm wavelength to detect and image the [CII] 158,$mu$m line from galaxies into the cosmic dark ages ($z sim 10$ to 20). The [CII] line may prove to be a powerful tool in determining spectroscopic redshifts, and galaxy dynamics, for the first galaxies. We emphasize that the nature, and even existence, of such extreme redshift galaxies, remains at the frontier of open questions in galaxy formation. In 40,hr, ALMA has the sensitivity to detect the integrated [CII] line emission from a moderate metallicity, active star-forming galaxy [$Z_A = 0.2,Z_{odot}$; star formation rate (SFR) = 5,$M_odot$,yr$^{-1}$], at $z = 10$ at a significance of 6$sigma$. The next-generation Very Large Array (ngVLA) will detect the integrated [CII] line emission from a Milky-Way like star formation rate galaxy ($Z_{A} = 0.2,Z_{odot}$, SFR = 1,$M_odot$,yr$^{-1}$), at $z = 15$ at a significance of 6$sigma$. Imaging simulations show that the ngVLA can determine rotation dynamics for active star-forming galaxies at $z sim 15$, if they exist. Based on our very limited knowledge of the extreme redshift Universe, we calculate the count rate in blind, volumetric surveys for [CII] emission at $z sim 10$ to 20. The detection rates in blind surveys will be slow (of order unity per 40,hr pointing). However, the observations are well suited to commensal searches. We compare [CII] with the [OIII] 88$mu$m line, and other ancillary information in high $z$ galaxies that would aid these studies.
The accelerated expansion of the Universe is one of the main discoveries of the past decades, indicating the presence of an unknown component: the dark energy. Evidence of its presence is being gathered by a succession of observational experiments with increasing precision in its measurements. However, the most accepted model for explaining the dynamic of our Universe, the so-called Lambda cold dark matter, face several problems related to the nature of such energy component. This has lead to a growing exploration of alternative models attempting to solve those drawbacks. In this review, we briefly summarize the characteristics of a (non-exhaustive) list of dark energy models as well as some of the most used cosmological samples. Next, we discuss how to constrain each models parameters using observational data. Finally, we summarize the status of dark energy modeling.
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