Dark energy presents us with a challenging puzzle: understanding the new physics seen in the acceleration of the expansion of the Universe. Measurements using type-Ia supernovae (SNe) first detected this acceleration, and this approach remains the most direct route to studying the details of the Universe's expansion history that can teach us more about the nature of the dark energy. Such measurements are, however, extremely demanding in both precision and accuracy, since the different dark-energy models predict very small differences in the expansion history. While several cosmological probes may reach the required statistical uncertainties, the key measurement limit will be the systematic uncertainty. The supernova-measurement approach has the advantage of well-studied systematic uncertainties, allowing a next-generation experiment to be pursued. We briefly review the progress to date and examine the promise of future surveys with large numbers of SNe and well-bounded systematics.
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BigBOSS is a Stage IV ground-based dark energy experiment to study baryon acoustic oscillations (BAO) and the growth of structure with a wide-area galaxy and quasar redshift survey over 14,000 square degrees. It has been conditionally accepted by NOAO in response to a call for major new instrumentation and a high-impact science program for the 4-m Mayall telescope at Kitt Peak. The BigBOSS instrument is a robotically-actuated, fiber-fed spectrograph capable of taking 5000 simultaneous spectra over a wavelength range from 340 nm to 1060 nm, with a resolution R = 3000-4800.
Using data from imaging surveys that are already underway, spectroscopic targets are selected that trace the underlying dark matter distribution. In particular, targets include luminous red galaxies (LRGs) up to z = 1.0, extending the BOSS LRG survey in both redshift and survey area. To probe the universe out to even higher redshift, BigBOSS will target bright [OII] emission line galaxies (ELGs) up to z = 1.7. In total, 20 million galaxy redshifts are obtained to measure the BAO feature, trace the matter power spectrum at smaller scales, and detect redshift space distortions. BigBOSS will provide additional constraints on early dark energy and on the curvature of the universe by measuring the Ly-alpha forest in the spectra of over 600,000 2.2 < z < 3.5 quasars.
BigBOSS galaxy BAO measurements combined with an analysis of the broadband power, including the Ly-alpha forest in BigBOSS quasar spectra, achieves a FOM of 395 with Planck plus Stage III priors. This FOM is based on conservative assumptions for the analysis of broad band power (kmax = 0.15), and could grow to over 600 if current work allows us to push the analysis to higher wave numbers (kmax = 0.3). BigBOSS will also place constraints on theories of modified gravity and inflation, and will measure the sum of neutrino masses to 0.024 eV accuracy.
We develop a new framework for use in exploring Type Ia Supernova (SN Ia) spectra. Combining Principal Component Analysis (PCA) and Partial Least Square analysis (PLS) we are able to establish correlations between the Principal Components (PCs) and spectroscopic/photometric SNe Ia features. The technique was applied to ~120 supernova and ~800 spectra from the Nearby Supernova Factory. The ability of PCA to group together SNe Ia with similar spectral features, already explored in previous studies, is greatly enhanced by two important modifications: (1) the initial data matrix is built using derivatives of spectra over the wavelength, which increases the weight of weak lines and discards extinction, and (2) we extract time evolution information through the use of entire spectral sequences concatenated in each line of the input data matrix. These allow us to define a stable PC parameter space which can be used to characterize synthetic SN Ia spectra by means of real SN features. Using PLS, we demonstrate that the information from important previously known spectral indicators (namely the pseudo-equivalent width (pEW) of Si II 5972 / Si II 6355 and the line velocity of S II 5640 / Si II 6355) at a given epoch, is contained within the PC space and can be determined through a linear combination of the most important PCs. We also show that the PC space encompasses photometric features like B or V magnitudes, B-V color and SALT2 parameters c and x1. The observed colors and magnitudes, that are heavily affected by extinction, cannot be reconstructed using this technique alone. All the above mentioned applications allowed us to construct a metric space for comparing synthetic SN Ia spectra with observations.
Using three magnified Type Ia supernovae (SNe Ia) detected behind CLASH (Cluster Lensing and Supernovae with Hubble) clusters, we perform a first pilot study to see whether standardizable candles can be used to calibrate cluster mass maps created from strong lensing observations. Such calibrations will be crucial when next-generation Hubble Space Telescope cluster surveys (e.g. Frontier) provide magnification maps that will, in turn, form the basis for the exploration of the high-redshift Universe. We classify SNe using combined photometric and spectroscopic observations, finding two of the three to be clearly of Type Ia and the third probable. The SNe exhibit significant amplification, up to a factor of 1.7 at ∼5σ significance (SN-L2). We conducted this as a blind study to avoid fine-tuning of parameters, finding a mean amplification difference between SNe and the cluster lensing models of 0.09 ± 0.09stat ± 0.05sys舁mag. This impressive agreement suggests no tension between cluster mass models and high-redshift-standardized SNe Ia. However, the measured statistical dispersion of σμ = 0.21舁mag appeared large compared to the dispersion expected based on statistical uncertainties (0.14). Further work with the SN and cluster lensing models, post-unblinding, reduced the measured dispersion to σμ = 0.12. An explicit choice should thus be made as to whether SNe are used unblinded to improve the model, or blinded to test the model. As the lensed SN samples grow larger, this technique will allow improved constraints on assumptions regarding e.g. the structure of the dark matter halo.
