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Register a new userPeculiar-velocity cosmology with Types Ia and II supernovae
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We present the Democratic Samples of Supernovae (DSS), a compilation of 775 low-redshift Type Ia and II supernovae (SNe Ia & II), of which 137 SN Ia distances are derived via the newly developed snapshot distance method. Using the objects in the DSS as tracers of the peculiar-velocity field, we compare against the corresponding reconstruction from the 2M++ galaxy redshift survey. Our analysis -- which takes special care to properly weight each DSS subcatalogue and cross-calibrate the relative distance scales between them -- results in a measurement of the cosmological parameter combination $fsigma_8 = 0.390_{-0.022}^{+0.022}$ as well as an external bulk flow velocity of $195_{-23}^{+22}$ km s$^{-1}$ in the direction $(ell, b) = (292_{-7}^{+7}, -6_{-4}^{+5})$ deg, which originates from beyond the 2M++ reconstruction. Similarly, we find a bulk flow of $245_{-31}^{+32}$ km s$^{-1}$ toward $(ell, b) = (294_{-7}^{+7}, 3_{-5}^{+6})$ deg on a scale of $sim 30 h^{-1}$ Mpc if we ignore the reconstructed peculiar-velocity field altogether. Our constraint on $fsigma_8$ -- the tightest derived from SNe to date (considering only statistical error bars), and the only one to utilise SNe II -- is broadly consistent with other results from the literature. We intend for our data accumulation and treatment techniques to become the prototype for future studies that will exploit the unprecedented data volume from upcoming wide-field surveys.
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Type Ia Supernovae have yet again the opportunity to revolutionize the field of cosmology as the new generation of surveys are acquiring thousands of nearby SNeIa opening a new era in cosmology: the direct measurement of the growth of structure parametrized by $fD$. This method is based on the SNeIa peculiar velocities derived from the residual to the Hubble law as direct tracers of the full gravitational potential caused by large scale structure. With this technique, we could probe not only the properties of dark energy, but also the laws of gravity. In this paper we present the analytical framework and forecasts. We show that ZTF and LSST will be able to reach 5% precision on $fD$ by 2027. Our analysis is not significantly sensitive to photo-typing, but known selection functions and spectroscopic redshifts are mandatory. We finally introduce an idea of a dedicated spectrograph that would get all the required information in addition to boost the efficiency to each SNeIa so that we could reach the 5% precision within the first two years of LSST operation and the few percent level by the end of the survey.
We present the cosmological analysis of 752 photometrically-classified Type Ia Supernovae (SNe Ia) obtained from the full Sloan Digital Sky Survey II (SDSS-II) Supernova (SN) Survey, supplemented with host-galaxy spectroscopy from the SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS). Our photometric-classification method is based on the SN typing technique of Sako et al. (2011), aided by host galaxy redshifts (0.05<z<0.55). SNANA simulations of our methodology estimate that we have a SN Ia typing efficiency of 70.8%, with only 3.9% contamination from core-collapse (non-Ia) SNe. We demonstrate that this level of contamination has no effect on our cosmological constraints. We quantify and correct for our selection effects (e.g., Malmquist bias) using simulations. When fitting to a flat LambdaCDM cosmological model, we find that our photometric sample alone gives omega_m=0.24+0.07-0.05 (statistical errors only). If we relax the constraint on flatness, then our sample provides competitive joint statistical constraints on omega_m and omega_lambda, comparable to those derived from the spectroscopically-confirmed three-year Supernova Legacy Survey (SNLS3). Using only our data, the statistics-only result favors an accelerating universe at 99.96% confidence. Assuming a constant wCDM cosmological model, and combining with H0, CMB and LRG data, we obtain w=-0.96+0.10-0.10, omega_m=0.29+0.02-0.02 and omega_k=0.00+0.03-0.02 (statistical errors only), which is competitive with similar spectroscopically confirmed SNe Ia analyses. Overall this comparison is re-assuring, considering the lower redshift leverage of the SDSS-II SN sample (z<0.55) and the lack of spectroscopic confirmation used herein. These results demonstrate the potential of photometrically-classified SNe Ia samples in improving cosmological constraints.
An important problem in precision cosmology is the determination of the effects of averaging and backreaction on observational predictions, particularly in view of the wealth of new observational data and improved statistical techniques. In this paper, we discuss the observational viability of a class of averaged cosmologies which consist of a simple parametrized phenomenological two-scale backreaction model with decoupled spatial curvature parameters. We perform a Bayesian model selection analysis and find that this class of averaged phenomenological cosmological models is favored with respect to the standard $Lambda$CDM cosmological scenario when a joint analysis of current SNe Ia and BAO data is performed. In particular, the analysis provides observational evidence for non-trivial spatial curvature.
The existence of multiple subclasses of type Ia supernovae (SNeIa) has been the subject of great debate in the last decade. One major challenge inevitably met when trying to infer the existence of one or more subclasses is the time consuming, and subjective, process of subclass definition. In this work, we show how machine learning tools facilitate identification of subtypes of SNeIa through the establishment of a hierarchical group structure in the continuous space of spectral diversity formed by these objects. Using Deep Learning, we were capable of performing such identification in a 4 dimensional feature space (+1 for time evolution), while the standard Principal Component Analysis barely achieves similar results using 15 principal components. This is evidence that the progenitor system and the explosion mechanism can be described by a small number of initial physical parameters. As a proof of concept, we show that our results are in close agreement with a previously suggested classification scheme and that our proposed method can grasp the main spectral features behind the definition of such subtypes. This allows the confirmation of the velocity of lines as a first order effect in the determination of SNIa subtypes, followed by 91bg-like events. Given the expected data deluge in the forthcoming years, our proposed approach is essential to allow a quick and statistically coherent identification of SNeIa subtypes (and outliers). All tools used in this work were made publicly available in the Python package Dimensionality Reduction And Clustering for Unsupervised Learning in Astronomy (DRACULA) and can be found within COINtoolbox (https://github.com/COINtoolbox/DRACULA).
The vast majority of Type II supernovae (SNe) are produced by red supergiants (RSGs), but SN 1987A revealed that blue supergiants (BSGs) can produce members of this class as well, albeit with some peculiar properties. This best studied event revolutionized our understanding of SNe, and linking it to the bulk of Type II events is essential. We present here optical photometry and spectroscopy gathered for SN 2000cb, which is clearly not a standard Type II SN and yet is not a SN 1987A analog. The light curve of SN 2000cb is reminiscent of that of SN 1987A in shape, with a slow rise to a late optical peak, but on substantially different time scales. Spectroscopically, SN 2000cb resembles a normal SN II but with ejecta velocities that far exceed those measured for SN 1987A or normal SNe II, above 18000 km/s for H-alpha at early times. The red colours, high velocities, late photometric peak, and our modeling of this object all point toward a scenario involving the high-energy explosion of a small-radius star, most likely a BSG, producing 0.1 solar masses of Ni-56. Adding a similar object to the sample, SN 2005ci, we derive a rate of about 2% of the core-collapse rate for this loosely defined class of BSG explosions.
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