SN Ia Data Sets Research Articles

NewHubble Space TelescopeDiscoveries of Type Ia Supernovae atz≥ 1: Narrowing Constraints on the Early Behavior of Dark Energy

We have discovered 21 new Type Ia supernovae (SNe Ia) with the Hubble Space Telescope (HST) and have used them to trace the history of cosmic expansion over the last 10 billion yr. These objects, which include 13 spectroscopically confirmed SNe Ia at z ≥ 1, were discovered during 14 epochs of reimaging of the GOODS fields North and South over 2 yr with the Advanced Camera for Surveys on HST. Together with a recalibration of our previous HST-discovered SNe Ia, the full sample of 23 SNe Ia at z ≥ 1 provides the highest redshift sample known. Combining these data with previous SN Ia data sets, we measured H(z) at discrete, uncorrelated epochs, reducing the uncertainty of H(z > 1) from 50% to under 20%, strengthening the evidence for a cosmic jerk—the transition from deceleration in the past to acceleration in the present. The unique leverage of the HST high-redshift SNe Ia provides the first meaningful constraint on the dark energy equation-of-state parameter at z ≥ 1. The result remains consistent with a cosmological constant [w(z) = −1] and rules out rapidly evolving dark energy (dw/dz ≫ 1). The defining property of dark energy, its negative pressure, appears to be present at z > 1, in the epoch preceding acceleration, with ~98% confidence in our primary fit. Moreover, the z > 1 sample-averaged spectral energy distribution is consistent with that of the typical SN Ia over the last 10 Gyr, indicating that any spectral evolution of the properties of SNe Ia with redshift is still below our detection threshold.

Tension and systematics in the Gold06 SnIa data set

The Gold06 SnIa data set recently released in astro-ph/0611572 consists of five distinctsubsets defined by the group or instrument that discovered and analysed the correspondingdata. These subsets are: the SNLS subset (47 SnIa), the HST subset (30 SnIa), the HZSSTsubset (41 SnIa), the SCP subset (26 SnIa) and the low redshift (LR) subset (38SnIa). These subsets sum up to the 182 SnIa of the Gold06 data set. We useMonte Carlo simulations to study the statistical consistency of each one of theabove subsets with the full Gold06 data set. In particular, we compare the best fitw(z) parameters (w0, w1) obtained by subtracting each one of the above subsets from the Gold06data set (subset truncation), with the corresponding best fit parameters(w0r, w1r) obtained by subtracting the same number of randomly selected SnIa from the same redshiftrange of the Gold06 data set (random truncation). We find that the probability for(w0r, w1r) = (w0, w1) is large for the Gold06 minus SCP (Gold06-SCP) truncation but is less than5% for the Gold06-SNLS, Gold06-HZSST and Gold06-HST truncations. This result implies thatthe Gold06 data set is not statistically homogeneous. By comparing the values of the best fit(w0, w1) for each subset truncation we find that the tension among subsets is such that the SNLSand HST subsets are statistically consistent with each other and ‘pull’ towardsΛCDM (w0 = −1, w1 = 0) while the HZSST subset is statistically distinct and strongly ‘pulls’ towards a varyingw(z) crossingthe line w = −1 from below (w0 < −1, w1 > 0). We also isolate six SnIa that are mostly responsible for this behaviour of the HZSSTsubset.

Evolving Newton’s constant, extended gravity theories, and SnIa data analysis

If Newton's constant $G$ evolves on cosmological timescales as predicted by extended gravity theories then Type Ia supernovae (SnIa) cannot be treated as standard candles. The magnitude-redshift datasets however can still be useful. They can be used to simultaneously fit for both $H(z)$ and $G(z)$ (so that local $G(z)$ constraints are also satisfied) in the context of appropriate parametrizations. Here we demonstrate how this analysis can be done by applying it to the Gold SnIa dataset. We compare the derived effective equation of state parameter $w(z)$ at best fit with the corresponding result obtained by neglecting the evolution $G(z)$. We show that even though the results clearly differ from each other, in both cases the best fit $w(z)$ crosses the phantom divide $w=\ensuremath{-}1$. We then attempt to reconstruct a scalar-tensor theory that predicts the derived best fit forms of $H(z)$ and $G(z)$. Since the best fit $G(z)$ fixes the scalar-tensor potential evolution $F(z)$, there is no ambiguity in the reconstruction and the potential $U(z)$ can be derived uniquely. The particular reconstructed scalar-tensor theory, however, involves a change of sign of the kinetic term ${\ensuremath{\Phi}}^{\ensuremath{'}}(z{)}^{2}$ as in the minimally coupled case.

Comparison of the legacy and gold type Ia supernovae dataset constraints on dark energy models

We have performed a comparative analysis of three recent and reliable SnIa datasets available in the literature: the Full Gold (FG) dataset (157 data points $0&lt;z&lt;1.75$), a Truncated Gold (TG) dataset (140 data points $0&lt;z&lt;1$) and the most recent Supernova Legacy Survey (SNLS) dataset (115 data points $0&lt;z&lt;1$). We have analyzed and compared the likelihood of cosmological constant and dynamical dark energy parametrizations allowing for crossing of the phantom divide line (PDL). We find that, even though the constraints obtained using the three datasets are consistent with each other at the 95% confidence level, the latest (SNLS) dataset shows distinct trends which are not shared by the Gold datasets. We find that the best fit dynamical $w(z)$ obtained from the SNLS dataset does not cross the PDL $w=\ensuremath{-}1$ and remains above and close to the $w=\ensuremath{-}1$ line for the whole redshift range $0&lt;z&lt;1$ showing no evidence for phantom behavior. The $\ensuremath{\Lambda}+\mathrm{\text{Cold}}\text{ }\mathrm{\text{Dark}}\text{ }\mathrm{\text{Matter}}$ (LCDM) parameter values (${w}_{0}=\ensuremath{-}1$, ${w}_{1}=0$) almost coincide with the best fit parameters of the dynamical $w(z)$ parametrizations. In contrast, the best fit dynamical $w(z)$ obtained from the Gold datasets (FG and TG) clearly crosses the PDL and departs significantly from the PDL $w=\ensuremath{-}1$ line while the LCDM parameter values are about $2\ensuremath{\sigma}$ away from the best fit $w(z)$. In addition, the $({\ensuremath{\Omega}}_{0m},{\ensuremath{\Omega}}_{\ensuremath{\Lambda}})$ parameters in a LCDM parametrization without a flat prior, fit by the SNLS dataset, favor the minimal flat LCDM concordance model. The corresponding fit with the Gold datasets mildly favors a closed universe and the flat LCDM parameter values are $1\ensuremath{\sigma}--2\ensuremath{\sigma}$ away from the best fit $({\ensuremath{\Omega}}_{0m},{\ensuremath{\Omega}}_{\ensuremath{\Lambda}})$.

Fitting non-minimally coupled scalar models to Gold SnIa dataset

Non-minimally coupled theories of special potentials are analyzed numerically. Such theories yield equations of state ω<−1 and oscillations of the cosmological expansion, which are favored by the recent analysis of observations. Fitting these theories to the Gold SnIa dataset, we obtain results comparable with other models. A potential of the form V(ϕ)=V0ea1ϕ2 yields χmin2=170.127. Similar results are obtained for potentials of the form V(ϕ)=V0+a1ϕn.

Testing non-standard cosmological models with supernovae

In this work, we study the magnitude–redshift relation of a non-standard cosmological model. The model under consideration was first investigated within a special case of metric-affine gravity (MAG) and was recently recovered via different approaches by two other groups. Apart from the usual cosmological parameters for pressureless matter Ωm, cosmological constant/dark energy Ωλ and radiation Ωr a new density parameter Ωψ emerges. The field equations of the model reduce to a system which is effectively given by the usual Friedmann equations of general relativity, supplied by a correction to the energy density and pressure in the form of Ωψ, which is related to the non-Riemannian structure of the underlying spacetime. We search for the best-fit parameters using recent SN Ia data sets and constrain the possible contribution of a new dark-energy-like component at low redshifts, thereby putting an upper limit on the presence of non-Riemannian quantities in the late stages of the universe. In addition, the impact of placing the data in redshift bins of variable size is studied. The numerical results of this work also apply to several anisotropic cosmological models which, on the level of the field equations, exhibit a similar scaling behaviour of the density parameters like our non-Riemannian model.