David Parkinson

The WiggleZ Dark Energy Survey: mapping the distance–redshift relation with baryon acoustic oscillations

We present measurements of the baryon acoustic peak at redshifts z = 0.44, 0.6 and 0.73 in the galaxy correlation function of the final dataset of the WiggleZ Dark Energy Survey. We combine our correlation function with lower-redshift measurements from the 6-degree Field Galaxy Survey and Sloan Digital Sky Survey, producing a stacked survey correlation function in which the statistical significance of the detection of the baryon acoustic peak is 4.9-σ relative to a zero-baryon model with no peak. We fit cosmological models to this combined baryon acoustic oscillation (BAO) dataset comprising six distance-redshift data points, and compare the results to similar fits to the latest compilation of supernovae (SNe) and Cosmic Microwave Background (CMB) data. The BAO and SNe datasets produce consistent measurements of the equation-ofstate w of dark energy, when separately combined with the CMB, providing a powerful check for systematic errors in either of these distance probes. Combining all datasets we determine w = 1.03 ± 0.08 for a flat Universe, consistent with a cosmological constant model. Assuming dark energy is a cosmological constant and varying the spatial curvature, we find k = 0.004± 0.006.

The WiggleZ Dark Energy Survey: testing the cosmological model with baryon acoustic oscillations at z= 0.6

We measure the imprint of baryon acoustic oscillations (BAOs) in the galaxy clustering pattern at the highest redshift achieved to date, z= 0.6, using the distribution of N= 132 509 emission-line galaxies in the WiggleZ Dark Energy Survey. We quantify BAOs using three statistics: the galaxy correlation function, power spectrum and the band-filtered estimator introduced by Xu et al. The results are mutually consistent, corresponding to a 4.0 per cent measurement of the cosmic distance–redshift relation at z= 0.6 [in terms of the acoustic parameter ‘A(z)’ introduced by Eisenstein et al., we find A(z= 0.6) = 0.452 ± 0.018]. Both BAOs and power spectrum shape information contribute towards these constraints. The statistical significance of the detection of the acoustic peak in the correlation function, relative to a wiggle-free model, is 3.2σ. The ratios of our distance measurements to those obtained using BAOs in the distribution of luminous red galaxies at redshifts z= 0.2 and 0.35 are consistent with a flat Λ cold dark matter model that also provides a good fit to the pattern of observed fluctuations in the cosmic microwave background radiation. The addition of the current WiggleZ data results in a ≈30 per cent improvement in the measurement accuracy of a constant equation of state, w, using BAO data alone. Based solely on geometric BAO distance ratios, accelerating expansion (w < −1/3) is required with a probability of 99.8 per cent, providing a consistency check of conclusions based on supernovae observations. Further improvements in cosmological constraints will result when the WiggleZ survey data set is complete.

A NESTED SAMPLING ALGORITHM FOR COSMOLOGICAL MODEL SELECTION

The abundance of new cosmological data becoming available means that a wider range of cosmological models are testable than ever before. However, an important distinction must be made between parameter fitting and model selection. While parameter fitting simply determines how well a model fits the data, model selection statistics, such as the Bayesian Evidence, are now necessary to choose between these different models, and in particular to assess the need for new parameters. We implement a new evidence algorithm known as nested sampling, which combines accuracy, generality of application and computational feasibility, and apply it to some cosmological datasets and models. We find that a five-parameter model with Harrison–Zel’dovich initial spectrum is currently preferred. Subject headings: cosmology: theory

The WiggleZ Dark Energy Survey: Final data release and cosmological results

This paper presents cosmological results from the final data release of the WiggleZ Dark Energy Survey. We perform full analyses of different cosmological models using the WiggleZ power spectra measured at z=0.22, 0.41, 0.60, and 0.78, combined with other cosmological data sets. The limiting factor in this analysis is the theoretical modeling of the galaxy power spectrum, including nonlinearities, galaxy bias, and redshift-space distortions. In this paper we assess several different methods for modeling the theoretical power spectrum, testing them against the Gigaparsec WiggleZ simulations (GiggleZ). We fit for a base set of six cosmological parameters, {Ω_(b)h^2,Ω_(CDM)h^2,H_0,τ,A_s,n_s}, and five supplementary parameters {n_(run),r,w,Ω_k,∑m_ν}. In combination with the cosmic microwave background, our results are consistent with the ΛCDM concordance cosmology, with a measurement of the matter density of Ωm=0.29±0.016 and amplitude of fluctuations σ_8=0.825±0.017. Using WiggleZ data with cosmic microwave background and other distance and matter power spectra data, we find no evidence for any of the extension parameters being inconsistent with their ΛCDM model values. The power spectra data and theoretical modeling tools are available for use as a module for CosmoMC, which we here make publicly available at http://smp.uq.edu.au/wigglez-data. We also release the data and random catalogs used to construct the baryon acoustic oscillation correlation function.

Foundations of observing dark energy dynamics with the Wilkinson Microwave Anisotropy Probe

Detecting dark energy dynamics is the main quest of current dark energy research. Addressing the issue demands a fully consistent analysis of cosmic microwave background, large-scale structure and SN-Ia data with multiparameter freedom valid for all redshifts. Here we undertake a ten parameter analysis of general dark energy confronted with the first year Wilkinson Microwave Anisotropy Probe, 2dF galaxy survey and latest SN-Ia data. Despite the huge freedom in dark energy dynamics there are no new degeneracies with standard cosmic parameters apart from a mild degeneracy between reionization and the redshift of acceleration, both of which effectively suppress small scale power. Breaking this degeneracy will help significantly in detecting dynamics, if it exists. Our best-fit model to the data has significant late-time evolution at z<1.5. Phantom models are also considered and we find that the best-fit crosses w =-1 which, if confirmed, would be a clear signal for radically new physics. Treatment of such rapidly varying models requires careful integration of the dark energy density usually not implemented in standard codes, leading to crucial errors of up to 5%. Nevertheless cosmic variance means that standard Lambda cold dark matter models are still a very good fit to the data and evidence for dynamics is currently very weak. Independent tests of reionization or the epoch of acceleration (e.g., integrated Sachs-Wolfelarge scale structure correlations) or reduction of cosmic variance at large scales (e.g., cluster polarization at high redshift) may prove key in the hunt for dynamics.

CFHTLenS: testing the laws of gravity with tomographic weak lensing and redshift-space distortions

Dark energy may be the first sign of new fundamental physics in the Universe, taking either a physical form or revealing a correction to Einsteinian gravity. Weak gravitational lensing and galaxy peculiar velocities provide complementary probes of general relativity, and in combination allow us to test modified theories of gravity in a unique way. We perform such an analysis by combining measurements of cosmic shear tomography from the Canada–France–Hawaii Telescope Lensing Survey (CFHTLenS) with the growth of structure from the WiggleZ Dark Energy Survey and the Six-degree-Field Galaxy Survey, producing the strongest existing joint constraints on the metric potentials that describe general theories of gravity. For scale-independent modifications to the metric potentials which evolve linearly with the effective dark energy density, we find present-day cosmological deviations in the Newtonian potential and curvature potential from the prediction of general relativity to be ΔΨ/Ψ = 0.05 ± 0.25 and ΔΦ/Φ = −0.05 ± 0.3, respectively (68 per cent confidence limits).

Measuring the effective complexity of cosmological models

We introduce a statistical measure of the effective model complexity, called the Bayesian complexity. We demonstrate that the Bayesian complexity can be used to assess how many effective parameters a set of data can support and that it is a useful complement to the model likelihood (the evidence) in model selection questions. We apply this approach to recent measurements of cosmic microwave background anisotropies combined with the Hubble Space Telescope measurement of the Hubble parameter. Using mildly non-informative priors, we show how the 3-year WMAP data improves on the first-year data by being able to measure both the spectral index and the reionization epoch at the same time. We also find that a non-zero curvature is strongly disfavored. We conclude that although current data could constrain at least seven effective parameters, only six of them are required in a scheme based on the Lambda-CDM concordance cosmology.

Bayesian methods in cosmology

In recent years cosmologists have advanced from largely qualitative models of the Universe to precision modelling using Bayesian methods, in order to determine the properties of the Universe to high accuracy. This timely book is the only comprehensive introduction to the use of Bayesian methods in cosmological studies, and is an essential reference for graduate students and researchers in cosmology, astrophysics and applied statistics. The first part of the book focuses on methodology, setting the basic foundations and giving a detailed description of techniques. It covers topics including the estimation of parameters, Bayesian model comparison, and separation of signals. The second part explores a diverse range of applications, from the detection of astronomical sources (including through gravitational waves), to cosmic microwave background

Results from the Supernova Photometric Classification Challenge

We report results from the Supernova Photometric Classification Challenge (SNPhotCC), a publicly released mix of simulated supernovae (SNe), with types (Ia, Ibc, and II) selected in proportion to their expected rates. The simulation was realized in the griz filters of the Dark Energy Survey (DES) with realistic observing conditions (sky noise, point-spread function, and atmospheric transparency) based on years of recorded conditions at the DES site. Simulations of non-Ia-type SNe are based on spectroscopically confirmed light curves that include unpublished non-Ia samples donated from the Carnegie Supernova Project (CSP), the Supernova Legacy Survey (SNLS), and the Sloan Digital Sky Survey-II (SDSS-II). A spectroscopically confirmed subset was provided for training. We challenged scientists to run their classification algorithms and report a type and photo-z for each SN. Participants from 10 groups contributed 13 entries for the sample that included a host-galaxy photo-z for each SN and nine entries for the sample that had no redshift information. Several different classification strategies resulted in similar performance, and for all entries the performance was significantly better for the training subset than for the unconfirmed sample. For the spectroscopically unconfirmed subset, the entry with the highest average figure of merit for classifying SNe Ia has an efficiency of 0.96 and an SN Ia purity of 0.79. As a public resource for the future development of photometric SN classification and photo-z estimators, we have released updated simulations with improvements based on our experience from the SNPhotCC, added samples corresponding to the Large Synoptic Survey Telescope (LSST) and the SDSS-II, and provided the answer keys so that developers can evaluate their own analysis.

Bayesian model selection analysis of WMAP3

We present a Bayesian model selection analysis of WMAP3 data using our code CosmoNest. We focus on the density perturbation spectral index nS and the tensor-to-scalar ratio r, which define the plane of slow-roll inflationary models. We find that while the Bayesian evidence supports the conclusion that nS 6= 1, the data are not yet powerful enough to do so at a strong or decisive level. If tensors are assumed absent, the current odds are approximately 8 to 1 in favour of nS 6= 1 under our assumptions, when WMAP3 data is used together with external data sets. WMAP3 data on its own is unable to distinguish between the two models. Further, inclusion of r as a parameter weakens the conclusion against the Harrison–Zel’dovich case (nS = 1, r = 0), albeit in a prior-dependent way. In appendices we describe the CosmoNest code in detail, noting its ability to supply posterior samples as well as to accurately compute the Bayesian evidence. We make a first public release of CosmoNest, now available at www.cosmonest.org.