Type Ia supernova Hubble diagram with near-infrared and optical observations

We main goal of this paper is to test whether the NIR peak magnitudes of SNe Ia could be accurately estimated with only a single observation obtained close to maximum light, provided the time of B band maximum and the optical stretch parameter are known. We obtained multi-epoch UBVRI and single-epoch J and H photometric observations of 16 SNe Ia in the redshift range z=0.037-0.183, doubling the leverage of the current SN Ia NIR Hubble diagram and the number of SNe beyond redshift 0.04. This sample was analyzed together with 102 NIR and 458 optical light curves (LCs) of normal SNe Ia from the literature. The analysis of 45 well-sampled NIR LCs shows that a single template accurately describes them if its time axis is stretched with the optical stretch parameter. This allows us to estimate the NIR peak magnitudes even with one observation obtained within 10 days from B-band maximum. We find that the NIR Hubble residuals show weak correlation with DM_15 and E(B-V), and for the first time we report a possible dependence on the J_max-H_max color. The intrinsic NIR luminosity scatter of SNe Ia is estimated to be around 0.10 mag, which is smaller than what can be derived for a similarly heterogeneous sample at optical wavelengths. In conclusion, we find that SNe Ia are at least as good standard candles in the NIR as in the optical. We showed that it is feasible to extended the NIR SN Ia Hubble diagram to z=0.2 with very modest sampling of the NIR LCs, if complemented by well-sampled optical LCs. Our results suggest that the most efficient way to extend the NIR Hubble diagram to high redshift would be to obtain a single observation close to the NIR maximum. (abridged)Comment: 39 pages, 15 figures, accepted by A&

Parameter estimation with Bayesian estimation applied to multiple species in the presence of biases and correlations

The original formulation of Bayesian estimation applied to multiple species (BEAMS) showed how to use a data set contaminated by points of multiple underlying types to perform unbiased parameter estimation. An example is cosmological parameter estimation from a photometric supernova sample contaminated by unknown Type Ibc and II supernovae. Where other methods require data cuts to increase purity, BEAMS uses all of the data points in conjunction with their probabilities of being each type. Here we extend the BEAMS formalism to allow for correlations between the data and the type probabilities of the objects as can occur in realistic cases. We show with simple simulations that this extension can be crucial, providing a 50 per cent reduction in parameter estimation variance when such correlations do exist. We then go on to perform tests to quantify the importance of the type probabilities, one of which illustrates the effect of biasing the probabilities in various ways. Finally, a general presentation of the selection bias problem is given, and discussed in the context of future photometric supernova surveys and BEAMS, which lead to specific recommendations for future supernova survey

Model selection applied to reconstruction of the Primordial Power Spectrum

The preferred shape for the primordial spectrum of curvature perturbations is determined by performing a Bayesian model selection analysis of cosmological observations. We first reconstruct the spectrum modelled as piecewise linear in \log k between nodes in k-space whose amplitudes and positions are allowed to vary. The number of nodes together with their positions are chosen by the Bayesian evidence, so that we can both determine the complexity supported by the data and locate any features present in the spectrum. In addition to the node-based reconstruction, we consider a set of parameterised models for the primordial spectrum: the standard power-law parameterisation, the spectrum produced from the Lasenby & Doran (LD) model and a simple variant parameterisation. By comparing the Bayesian evidence for different classes of spectra, we find the power-law parameterisation is significantly disfavoured by current cosmological observations, which show a preference for the LD model.Comment: Minor changes to match version accepted by JCA

Statistical classification techniques for photometric supernova typing

Future photometric supernova surveys will produce vastly more candidates than can be followed up spectroscopically, highlighting the need for effective classification methods based on light curves alone. Here we introduce boosting and kernel density estimation techniques which have minimal astrophysical input, and compare their performance on 20 000 simulated Dark Energy Survey light curves. We demonstrate that these methods perform very well provided a representative sample of the full population is used for training. Interestingly, we find that they do not require the redshift of the host galaxy or candidate supernova. However, training on the types of spectroscopic subsamples currently produced by supernova surveys leads to poor performance due to the resulting bias in training, and we recommend that special attention be given to the creation of representative training samples. We show that given a typical non-representative training sample, S, one can expect to pull out a representative subsample of about 10 per cent of the size of S, which is large enough to outperform the methods trained on all of

Measuring primordial gravitational waves from CMB B-modes in cosmologies with generalized expansion histories

We evaluate our capability to constrain the abundance of primordial tensor perturbations in cosmologies with generalized expansion histories in the epoch of cosmic acceleration. Forthcoming satellite and sub-orbital experiments probing polarization in the CMB are expected to measure the B-mode power in CMB polarization, coming from PGWs on the degree scale, as well as gravitational lensing on arcmin scales; the latter is the main competitor for the measurement of PGWs, and is directly affected by the underlying expansion history, determined by the presence of a DE component. In particular, we consider early DE possible scenarios, in which the expansion history is substantially modified at the epoch in which the CMB lensing is most relevant. We show that the introduction of a parametrized DE may induce a variation as large as 30% in the ratio of the power of lensing and PGWs on the degree scale. We find that adopting the nominal specifications of upcoming satellite measurements the constraining power on PGWs is weakened by the inclusion of the extra degrees of freedom, resulting in a reduction of about 10% of the upper limits on r in fiducial models with no GWs, as well as a comparable increase in the error bars in models with non-zero r. Moreover, we find that the inclusion of sub-orbital CMB experiments, capable of mapping the B-mode power up to the angular scales affected by lensing, can restore the forecasted performances with a cosmological constant. Finally, we show how the combination of CMB data with Type Ia SNe, BAO and Hubble constant allows to constrain simultaneously r and the DE quantities in the parametrization we consider, consisting of present abundance and first redshift derivative of the energy density. We compare this study with results obtained using the forecasted lensing potential measurement precision from CMB satellite observations, finding consistent results.Comment: 17 pages, 9 figures, accepted for publication by JCAP. Modified version after the referee's comment

Sterile neutrinos with eV masses in cosmology -- how disfavoured exactly?

We study cosmological models that contain sterile neutrinos with eV-range masses as suggested by reactor and short-baseline oscillation data. We confront these models with both precision cosmological data (probing the CMB decoupling epoch) and light-element abundances (probing the BBN epoch). In the minimal LambdaCDM model, such sterile neutrinos are strongly disfavoured by current data because they contribute too much hot dark matter. However, if the cosmological framework is extended to include also additional relativistic degrees of freedom -- beyond the three standard neutrinos and the putative sterile neutrinos, then the hot dark matter constraint on the sterile states is considerably relaxed. A further improvement is achieved by allowing a dark energy equation of state parameter w<-1. While BBN strongly disfavours extra radiation beyond the assumed eV-mass sterile neutrino, this constraint can be circumvented by a small nu_e degeneracy. Any model containing eV-mass sterile neutrinos implies also strong modifications of other cosmological parameters. Notably, the inferred cold dark matter density can shift up by 20 to 75% relative to the standard LambdaCDM value.Comment: 14 pages, 6 figures, v2: minor changes, matches version accepted for publication in JCA

Statistical Classification Techniques for Photometric Supernova Typing

Future photometric supernova surveys will produce vastly more candidates than can be followed up spectroscopically, highlighting the need for effective classification methods based on lightcurves alone. Here we introduce boosting and kernel density estimation techniques which have minimal astrophysical input, and compare their performance on 20,000 simulated Dark Energy Survey lightcurves. We demonstrate that these methods are comparable to the best template fitting methods currently used, and in particular do not require the redshift of the host galaxy or candidate. However both methods require a training sample that is representative of the full population, so typical spectroscopic supernova subsamples will lead to poor performance. To enable the full potential of such blind methods, we recommend that representative training samples should be used and so specific attention should be given to their creation in the design phase of future photometric surveys.Comment: 19 pages, 41 figures. No changes. Additional material and summary video available at http://cosmoaims.wordpress.com/2010/09/30/boosting-for-supernova-classification