Joint Light-curve Analysis Research Articles

Reconstruction of energy conditions from observations and implications for extended theories of gravity

The attempt to describe the recent accelerated expansion of the Universe includes different propositions for dark energy models and modified gravity theories. Establish their features in order to discriminate and even rule out part of these models using observational data is a fundamental issue of cosmology. In the present work we consider a class of extended theories of gravity (ETG) that are minimally coupled to the ordinary matter fields. In this context, and assuming a homogeneous and isotropic spacetime, we derive the energy conditions for this ETG class. We then put constraints on these conditions using a model-independent approach to reconstruct the deceleration function along with the Joint Light-curve Analysis (JLA) supernova sample, 11 baryon acoustic oscillation and 22 cosmic-chronometer measurements. We also consider an additional condition imposing the strong energy condition only on the ordinary matter. This is to guarantee the presence of only attractive matter in the energy–momentum tensor, at least in the redshift range of the observations, i.e., the recent accelerated expansion of the Universe is due solely to the modifications in the gravity theory. The main result of this work is a general reconstruction of the energy conditions valid for every considered ETG.

SN Ia Standardization on the Rise: Evidence for the Cosmological Importance of Pre-maximum Measurements

We present SALT2X, an extension of the SALT2 model for SN Ia supernova light curves. SALT2X separates the light-curve-shape parameter x1 into an x1r and x1f for the rise and fall portions of the light curve. Using the Joint Lightcurve Analysis (JLA) SN sample, we assess the importance of the rising and falling portions of the light curve for cosmological standardization using a modified version of the Unified Nonlinear Inference for Type Ia cosmologY (UNITY) framework. We find strong evidence that x1r has a stronger correlation with peak magnitude than x1f. We see evidence that standardizing on the rise affects the color standardization relation, and reduces the size of the host-galaxy standardization and the unexplained ("intrinsic") luminosity dispersion. Since SNe Ia generally rise more quickly than they decline, a faster observing cadence in future surveys will be necessary to maximize the gain from this work, and to continue to explore the impacts of decoupling the rising and falling portions of SN Ia light curves.

Anisotropy Effects and Observational Data on the Constraints of Evolution Dark Energy Models

We investigate cosmological dark energy models where the accelerated expansion of the universe is driven by a field with an anisotropic universe. The constraints on the parameters are obtained by maximum likelihood analysis using observational of 194 Type Ia supernovae (SNIa) and the most recent joint light-curve analysis (JLA) sample. In particular we reconstruct the dark energy equation of state parameter w(z) and the deceleration parameter q(z). We find that the best fit dynamical w(z) obtained from the 194 SNIa dataset does not cross the phantom divide line w(z)=−1 and remains above and close to line for the whole redshift range showing no evidence for phantom behavior. By applying the anisotropy effect on the ΛCDM model, the joint analysis indicates that , with 194 SNIa, with 238 the SiFTO sample of JLA and with 1048 the SALT2 sample of Pantheon at confidence interval. The analysis shows that by considering the anisotropy, it leads to more best fit parameters in all models with JLA SNe datasets. Furthermore, we use two statistical tests such as the usual and p-test to compare two dark energy models with ΛCDM model. Finally we show that the presence of anisotropy is confirmed in mentioned models via SNIa dataset.

Hořava–Lifshitz cosmology in light of new data

We present new observational constraints on Lorentz violating Ho\v{r}ava-Lifshitz cosmological scenarios using an updated cosmological data set from Cosmic Microwave Background (Planck CMB), expansion rates of elliptical and lenticular galaxies, JLA compilation (Joint Light-Curve Analysis) data for Type Ia supernovae (SneIa), Baryon Acoustic Oscillations (BAO) and priors on the Hubble parameter with an alternative parametrisation of the equations. Unlike in other approaches we consider the curvature parameter $\Omega_k$ as a free parameter in the analysis we considered the parameters $\Omega_k$ and $\Delta N_\nu$ as completely free, which helped to place new, updated bounds on several of the theory parameters. Remarkably, the detailed balance scenario exhibits positive spatial curvature to more than 3$\sigma$, whereas for further theory generalizations we found evidence for positive spatial curvature at 1$\sigma$. This could create circumstantial evidence from observations and could be used to single out distinct formulations and scenarios.

Bayesian optimization for likelihood-free cosmological inference

Many cosmological models have only a finite number of parameters of interest, but a very expensive data-generating process and an intractable likelihood function. We address the problem of performing likelihood-free Bayesian inference from such black-box simulation-based models, under the constraint of a very limited simulation budget (typically a few thousand). To do so, we adopt an approach based on the likelihood of an alternative parametric model. Conventional approaches to approximate Bayesian computation such as likelihood-free rejection sampling are impractical for the considered problem, due to the lack of knowledge about how the parameters affect the discrepancy between observed and simulated data. As a response, we make use of a strategy previously developed in the machine learning literature (Bayesian optimization for likelihood-free inference, bolfi), which combines Gaussian process regression of the discrepancy to build a surrogate surface with Bayesian optimization to actively acquire training data. We extend the method by deriving an acquisition function tailored for the purpose of minimizing the expected uncertainty in the approximate posterior density, in the parametric approach. The resulting algorithm is applied to the problems of summarizing Gaussian signals and inferring cosmological parameters from the joint lightcurve analysis supernovae data. We show that the number of required simulations is reduced by several orders of magnitude, and that the proposed acquisition function produces more accurate posterior approximations, as compared to common strategies.

Observational constraints on oscillating dark-energy parametrizations

We perform a detailed confrontation of various oscillating dark-energy parame-trizations with the latest sets of observational data. In particular, we use data from Joint Light Curve analysis (JLA) sample from Supernoave Type Ia, Baryon Acoustic Oscillations (BAO) distance measurements, Cosmic Microwave Background (CMB) observations, redshift space distortion, weak gravitational lensing, Hubble parameter measurements from cosmic chronometers, and we impose constraints on four oscillating models. From the analyses we find that the best-fit characters of almost all models are bent towards the phantom region, nevertheless in all of them the quintessential regime is also allowed within 1$\sigma$ confidence-level. Furthermore, the deviations from $\Lambda$CDM cosmology are not significant, however for two of the models they could be visible at large scales, through the impact on the temperature anisotropy of the CMB spectra and on the matter power spectra. Finally, we peform the Bayesian analysis, which shows that the current observational data support the $\Lambda$CDM paradigm over this set of oscillating dark-energy parametrizations.

Cosmological tests with the joint lightcurve analysis

We examine whether a comparison between wCDM and using merged Type-Ia SN catalogs produces results consistent with those based on a single homogeneous sample. Using the Betoule et al. (Astron. Astrophys., 568 (2014) 22). Joint Lightcurve Analysis (JLA) of a combined sample of 613 events from SNLS and SDSS-II, we estimate the parameters of the two models and compare them. We find that the improved statistics can alter the model selection in some cases, but not others. In addition, based on the model fits, we find that there appears to be a lingering systematic offset of ∼0.04–0.08 mag between the SNLS and SDSS-II sources, in spite of the cross-calibration in the JLA. Treating wCDM, ΛCDM and as separate models, we find in an unbiased pairwise statistical comparison that the Bayes Information Criterion (BIC) favors the Universe with a likelihood of vs. for wCDM, but the ratio of likelihoods is reversed ( vs. ) when (i.e., ΛCDM) and strongly reversed ( vs. ) if in addition k = 0 (i.e., flat ΛCDM). We point out, however, that the value of k is a measure of the net energy (kinetic plus gravitational) in the Universe and is not constrained theoretically, though some models of inflation would drive due to an expansion-enforced dilution. Since we here consider only the basic ΛCDM model, the value of k needs to be measured and, therefore, the pre-assumption of flatness introduces a significant bias into the BIC.

Testing the cosmic anisotropy with supernovae data: Hemisphere comparison and dipole fitting

The cosmological principle is one of the cornerstones in modern cosmology. It assumes that the universe is homogeneous and isotropic on cosmic scales. Both the homogeneity and the isotropy of the universe should be tested carefully. In the present work, we are interested in probing the possible preferred direction in the distribution of type Ia supernovae (SNIa). To our best knowledge, two main methods have been used in almost all of the relevant works in the literature, namely the hemisphere comparison (HC) method and the dipole fitting (DF) method. However, the results from these two methods are not always approximately coincident with each other. In this work, we test the cosmic anisotropy by using these two methods with the Joint Light-Curve Analysis (JLA) and simulated SNIa datasets. In many cases, both methods work well, and their results are consistent with each other. However, in the cases with two (or even more) preferred directions, the DF method fails while the HC method still works well. This might shed new light on our understanding of these two methods.

Super-Eddington accreting massive black holes explore high- z cosmology: Monte-Carlo simulations

In this paper, we simulate Super-Eddington accreting massive black holes (SEAMBHs) as the candles to probe cosmology for the first time. SEAMBHs have been demonstrated to be able to provide a new tool for estimating cosmological distance. Thus, we create a series of mock data sets of SEAMBHs, especially in the high redshift region, to check their abilities to probe the cosmology. To fulfill the potential of the SEAMBHs on the cosmology, we apply the simulated data to three projects. The first is the exploration of their abilities to constrain the cosmological parameters, in which we combine different data sets of current observations such as the cosmic microwave background from {\it Planck} and type Ia supernovae from Joint Light-curve Analysis (JLA). We find that the high redshift SEAMBHs can help to break the degeneracies of the background cosmological parameters constrained by {\it Planck} and JLA, thus giving much tighter constraints of the cosmological parameters. The second uses the high redshift SEAMBHs as the complements of the low redshift JLA to constrain the early expansion rate and the dark energy density evolution in the cold dark matter frame. Our results show that these high redshift SEAMBHs are very powerful on constraining the early Hubble rate and the evolution of the dark energy density; thus they can give us more information about the expansion history of our Universe, which is also crucial for testing the $\Lambda$CDM model in the high redshift region. Finally, we check the SEAMBH candles' abilities to reconstruct the equation of state of dark energy at high redshift. In summary, our results show that the SEAMBHs, as the rare candles in the high redshift region, can provide us a new and independent observation to probe cosmology in the future.

Model independent inference of the expansion history and implications for the growth of structure

We model the expansion history of the Universe as a Gaussian Process and find constraints on the dark energy density and its low-redshift evolution using distances inferred from the Luminous Red Galaxy (LRG) and Lyman-alpha (Ly$\alpha$) datasets of the Baryon Oscillation Spectroscopic Survey, supernova data from the Joint Light-curve Analysis (JLA) sample, Cosmic Microwave Background (CMB) data from the Planck satellite, and local measurement of the Hubble parameter from the Hubble Space Telescope ($\mathsf H0$). Our analysis shows that the CMB, LRG, Ly$\alpha$, and JLA data are consistent with each other and with a $\Lambda$CDM cosmology, but the ${\mathsf H0}$ data is inconsistent at moderate significance. Including the presence of dark radiation does not alleviate the ${\mathsf H0}$ tension in our analysis. While some of these results have been noted previously, the strength here lies in that we do not assume a particular cosmological model. We calculate the growth of the gravitational potential in General Relativity corresponding to these general expansion histories and show that they are well-approximated by $\Omega_{\rm m}^{0.55}$ given the current precision. We assess the prospects for upcoming surveys to measure deviations from $\Lambda$CDM using this model-independent approach.

What do parameterized Om(z) diagnostics tell us in light of recent observations?

In this paper, we propose a new parametrization for Om(z) diagnostics and show how the most recent and significantly improved observations concerning the H(z) and SN Ia measurements can be used to probe the consistency or tension between the ΛCDM model and observations. Our results demonstrate that H0 plays a very important role in the consistency test of ΛCDM with H(z) data. Adopting the Hubble constant priors from Planck 2013 and Riess, one finds considerable tension between the current H(z) data and ΛCDM model and confirms the conclusions obtained previously by others. However, with the Hubble constant prior taken from WMAP9, the discrepancy between H(z) data and ΛCDM disappears, i.e., the current H(z) observations still support the cosmological constant scenario. This conclusion is also supported by the results derived from the Joint Light-curve Analysis (JLA) SN Ia sample. The best-fit Hubble constant from the combination of H(z)+JLA ( km s−1 Mpc−1) is very consistent with results derived both by Planck 2013 and WMAP9, but is significantly different from the recent local measurement by Riess.

Observational constraints on Gauss–Bonnet cosmology

We analyze a fully geometric approach to dark energy in the framework of [Formula: see text] theories of gravity, where [Formula: see text] is the Ricci curvature scalar and [Formula: see text] is the Gauss–Bonnet topological invariant. The latter invariant naturally exhausts, together with [Formula: see text], the whole curvature content related to curvature invariants coming from the Riemann tensor. In particular, we study a class of [Formula: see text] models with power law solutions and find that, depending on the value of the geometrical parameter, a shift in the anisotropy peaks position of the temperature power spectrum is produced, as well as an increasing in the matter power spectrum amplitude. This fact could be extremely relevant to fix the form of the [Formula: see text] model. We also perform an MCMC analysis using both Cosmic Microwave Background data by the Planck (2015) release and the Joint Light-Curve Analysis of the SNLS–SDSS collaborative effort, combined with the current local measurements of the Hubble value, [Formula: see text], and galaxy data from the Sloan Digital Sky Survey (BOSS CMASS DR11). We show that such a model can describe the CMB data with slightly high [Formula: see text] values, and the prediction on the amplitude matter spectrum value is proved to be in accordance with the observed matter distribution of the universe. At the same time, the value constrained for the geometric parameter implies a density evolution of such a component that is growing with time.

A tomographic test of cosmological principle using the JLA compilation of type Ia supernovae

We test the cosmological principle by fitting a dipolar modulation of distance modulus and searching for an evolution of this modulation with respect to cosmological redshift. Based on a redshift tomographic method, we divide the Joint Light-curve Analysis compilation of supernovae of type Ia into different redshift bins, and employ a Markov-Chain Monte-Carlo method to infer the anisotropic amplitude and direction in each redshift bin. However, we do not find any significant deviations from the cosmological principle, and the anisotropic amplitude is stringently constrained to be less than a few thousandths at $95\%$ confidence level.

Testing the distance–duality relation in the Rh = ct universe

In this paper, we test the cosmic distance duality (CDD) relation using the luminosity distances from joint light-curve analysis (JLA) type Ia supernovae (SNe Ia) sample and angular diameter distance sample from galaxy clusters. The $R_h=ct$ and $\Lambda$CDM models are considered. In order to compare the two models, we constrain the CCD relation and the SNe Ia light-curve parameters simultaneously. Considering the effects of Hubble constant, we find that $\eta\equiv D_A(1+z)^2/D_L=1$ is valid at the 2$\sigma$ confidence level in both models with $H_0 = 67.8\pm0.9$ km/s/Mpc. However, the CDD relation is valid at 3$\sigma$ confidence level with $H_0 = 73.45\pm1.66$ km/s/Mpc. Using the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC), we find that the $\Lambda$CDM model is very strongly preferred over the $R_h=ct$ model with these data sets for the CDD relation test.

Measuring Dark Energy Properties with Photometrically Classified Pan-STARRS Supernovae. II. Cosmological Parameters

Abstract We use 1169 Pan-STARRS supernovae (SNe) and 195 low-z (z < 0.1) SNe Ia to measure cosmological parameters. Though most Pan-STARRS SNe lack spectroscopic classifications, in a previous paper we demonstrated that photometrically classified SNe can be used to infer unbiased cosmological parameters by using a Bayesian methodology that marginalizes over core-collapse (CC) SN contamination. Our sample contains nearly twice as many SNe as the largest previous SN Ia compilation. Combining SNe with cosmic microwave background (CMB) constraints from Planck, we measure the dark energy equation-of-state parameter w to be −0.989 ± 0.057 (stat+sys). If w evolves with redshift as w(a) = w 0 + w a (1 − a), we find w 0 = −0.912 ± 0.149 and w a = −0.513 ± 0.826. These results are consistent with cosmological parameters from the Joint Light-curve Analysis and the Pantheon sample. We try four different photometric classification priors for Pan-STARRS SNe and two alternate ways of modeling CC SN contamination, finding that no variant gives a w differing by more than 2% from the baseline measurement. The systematic uncertainty on w due to marginalizing over CC SN contamination, , is the third-smallest source of systematic uncertainty in this work. We find limited (1.6σ) evidence for evolution of the SN color-luminosity relation with redshift, a possible systematic that could constitute a significant uncertainty in future high-z analyses. Our data provide one of the best current constraints on w, demonstrating that samples with ∼5% CC SN contamination can give competitive cosmological constraints when the contaminating distribution is marginalized over in a Bayesian framework.

Massive optimal data compression and density estimation for scalable, likelihood-free inference in cosmology

Many statistical models in cosmology can be simulated forwards but have intractable likelihood functions. Likelihood-free inference methods allow us to perform Bayesian inference from these models using only forward simulations, free from any likelihood assumptions or approximations. Likelihood-free inference generically involves simulating mock data and comparing to the observed data; this comparison in data-space suffers from the curse of dimensionality and requires compression of the data to a small number of summary statistics to be tractable. In this paper we use massive asymptotically-optimal data compression to reduce the dimensionality of the data-space to just one number per parameter, providing a natural and optimal framework for summary statistic choice for likelihood-free inference. Secondly, we present the first cosmological application of Density Estimation Likelihood-Free Inference (\textsc{delfi}), which learns a parameterized model for joint distribution of data and parameters, yielding both the parameter posterior and the model evidence. This approach is conceptually simple, requires less tuning than traditional Approximate Bayesian Computation approaches to likelihood-free inference and can give high-fidelity posteriors from orders of magnitude fewer forward simulations. As an additional bonus, it enables parameter inference and Bayesian model comparison simultaneously. We demonstrate Density Estimation Likelihood-Free Inference with massive data compression on an analysis of the joint light-curve analysis supernova data, as a simple validation case study. We show that high-fidelity posterior inference is possible for full-scale cosmological data analyses with as few as $\sim 10^4$ simulations, with substantial scope for further improvement, demonstrating the scalability of likelihood-free inference to large and complex cosmological datasets.

Astronomical bounds on a cosmological model allowing a general interaction in the dark sector

Non-gravitational interaction between two barotropic dark fluids, namely the pressureless dust and the dark energy in a spatially flat Friedmann-Lema\^{i}tre-Robertson-Walker model has been discussed. It is shown that for the interactions which are linear in terms the energy densities of the dark components and their first order derivatives, the net energy density is governed by a second order differential equation with constant coefficients. Taking a generalized interaction, which includes a number of already known interactions as special cases, the dynamics of the universe is described for three types of the dark energy equation of state, namely that of interacting quintessence, interacting vacuum energy density and interacting phantom. The models have been constrained using the standard cosmological probes, Supernovae type Ia data from joint light curve analysis and the observational Hubble parameter data. Two geometric tests, the cosmographic studies and the $Om$ diagnostic have been invoked so as to ascertain the behaviour of the present model vis-a-vis the $\Lambda$-cold dark matter model. We further discussed the interacting scenarios taking into account the thermodynamic considerations.

Do current cosmological observations rule out all covariant Galileons?

We revisit the cosmology of Covariant Galileon gravity in view of the most recent cosmological data sets, including weak lensing. As a higher derivative theory, Covariant Galileon models do not have a $\Lambda$CDM limit and predict a very different structure formation pattern compared with the standard $\Lambda$CDM scenario. Previous cosmological analyses suggest that this model is marginally disfavoured, yet can not be completely ruled out. In this work we use a more recent and extended combination of data, and we allow for more freedom in the cosmology, by including a massive neutrino sector with three different mass hierarchies. We use the Planck measurements of Cosmic Microwave Background temperature and polarization; Baryonic Acoustic Oscillations measurements by BOSS DR12; local measurements of $H_0$; the joint light-curve analysis supernovae sample; and, for the first time, weak gravitational lensing from the KiDS collaboration. We find, that in order to provide a reasonable fit, a non-zero neutrino mass is indeed necessary, but we do not report any sizable difference among the three neutrino hierarchies. Finally, the comparison of the Bayesian Evidence to the $\Lambda$CDM one shows that in all the cases considered, Covariant Galileon models are statistically ruled out by cosmological data.

Testing Viable f(T) Models with Current Observations

Abstract We perform observational tests on the f(T) gravity with the BAO data (including the BOSS DR 12 galaxy sample, the DR12 Lyα-Forests measurement, the new eBOSS DR14 quasar sample, the 6dFGS, and the SDSS), the CMB distance priors from the Planck 2015, the SNIa data from the joint light-curve analysis, the latest H(z) data, and the local value of the Hubble constant. Six different f(T) models are investigated. Furthermore, the ΛCDM is also considered. All models are compared by using the Akaike information criteria (AIC) and the Bayesian information criteria (BIC). Our results show that the ΛCDM remains to be the most favored model by current observations. However, there are also the Hubble constant tension between the Planck measurements and the local Universe observations and the tension between the CMB data and the H(z) data in the ΛCDM. For f(T) models considered in this paper, half, which can reduce to the ΛCDM, have values of smaller than that of the ΛCDM and can relieve the tensions existing in the ΛCDM. However, they are punished slightly by the BIC due to one extra parameter. Two of six f(T) models, in which the crossing of the phantom divide line can be realized for the equation of state of the effective dark energy and this crossing is shown in this paper to be favored by current observations, are punished by the information criteria. In addition, we find that the logarithmic f(T) model is excluded by cosmological observations.

Updated observational constraints on quintessence dark energy models

The recent GW170817 measurement favors the simplest dark energy models, such as a single scalar field. Quintessence models can be classified in two classes, freezing and thawing, depending on whether the equation of state decreases towards $-1$ or departs from it. In this paper we put observational constraints on the parameters governing the equations of state of tracking freezing, scaling freezing and thawing models using updated data, from the Planck 2015 release, joint light-curve analysis and baryonic acoustic oscillations. Because of the current tensions on the value of the Hubble parameter $H_0$, unlike previous authors, we let this parameter vary, which modifies significantly the results. Finally, we also derive constraints on neutrino masses in each of these scenarios.