Supernova host galaxies in the Dark Energy Survey: I. Deep coadds, photometry, and stellar masses

The 5-yr Dark Energy Survey Supernova Programme (DES-SN) is one of the largest and deepest transient surveys to date in terms of volume and number of supernovae. Identifying and characterizing the host galaxies of transients plays a key role in their classification, the study of their formation mechanisms, and the cosmological analyses. To derive accurate host galaxy properties, we create depth-optimized coadds using single-epoch DES-SN images that are selected based on sky and atmospheric conditions. For each of the five DES-SN seasons, a separate coadd is made from the other four seasons such that each SN has a corresponding deep coadd with no contaminating SN emission. The coadds reach limiting magnitudes of order ∼27 in g band, and have a much smaller magnitude uncertainty than the previous DES-SN host templates, particularly for faint objects. We present the resulting multiband photometry of host galaxies for samples of spectroscopically confirmed type Ia (SNe Ia), core-collapse (CCSNe), and superluminous (SLSNe) as well as rapidly evolving transients (RETs) discovered by DES-SN. We derive host galaxy stellar masses and probabilistically compare stellar-mass distributions to samples from other surveys. We find that the DES spectroscopically confirmed sample of SNe Ia selects preferentially fewer high-mass hosts at high-redshift compared to other surveys, while at low redshift the distributions are consistent. DES CCSNe and SLSNe hosts are similar to other samples, while RET hosts are unlike the hosts of any other transients, although these differences have not been disentangled from selection effects

Dark energy survey year 1 results: Redshift distributions of the weak-lensing source galaxies

We describe the derivation and validation of redshift distribution estimates and their uncertainties for the populations of galaxies used as weak-lensing sources in the Dark Energy Survey (DES) Year 1 cosmological analyses. The Bayesian Photometric Redshift (BPZ) code is used to assign galaxies to four redshift bins between z ≈ 0.2 and ≈1.3, and to produce initial estimates of the lensing-weighted redshift distributions nPZi(z) ∝ dni/dz for members of bin i. Accurate determination of cosmological parameters depends critically on knowledge of ni, but is insensitive to bin assignments or redshift errors for individual galaxies. The cosmological analyses allow for shifts ni (z) = nPZi(z - Δzi) to correct themean redshift of ni(z) for biases in nPZi. The Δzi are constrained by comparison of independently estimated 30-band photometric redshifts of galaxies in the Cosmic Evolution Survey (COSMOS) field to BPZ estimates made from the DES griz fluxes, for a sample matched in fluxes, pre-seeing size, and lensing weight to the DES weak-lensing sources. In companion papers, the Δzi of the three lowest redshift bins are further constrained by the angular clustering of the source galaxies around red galaxies with secure photometric redshifts at 0.15 < z < 0.9. This paper details the BPZ and COSMOS procedures, and demonstrates that the cosmological inference is insensitive to details of the ni(z) beyond the choice of Δzi. The clustering and COSMOS validation methods produce consistent estimates of Δzi in the bins where both can be applied, with combined uncertainties of σΔzi = 0.015, 0.013, 0.011, and 0.022 in the four bins. Repeating the photo-z procedure instead using the Directional Neighbourhood Fitting algorithm, or using the ni(z) estimated from the matched sample in COSMOS, yields no discernible difference in cosmological inferences

First cosmology results using Type Ia supernova from the Dark Energy Survey: simulations to correct supernova distance biases

We describe catalog-level simulations of Type Ia supernova (SN~Ia) light curves in the Dark Energy Survey Supernova Program (DES-SN), and in low-redshift samples from the Center for Astrophysics (CfA) and the Carnegie Supernova Project (CSP). These simulations are used to model biases from selection effects and light curve analysis, and to determine bias corrections for SN~Ia distance moduli that are used to measure cosmological parameters. To generate realistic light curves, the simulation uses a detailed SN~Ia model, incorporates information from observations (PSF, sky noise, zero point), and uses summary information (e.g., detection efficiency vs. signal to noise ratio) based on 10,000 fake SN light curves whose fluxes were overlaid on images and processed with our analysis pipelines. The quality of the simulation is illustrated by predicting distributions observed in the data. Averaging within redshift bins, we find distance modulus biases up to 0.05~mag over the redshift ranges of the low-z and DES-SN samples. For individual events, particularly those with extreme red or blue color, distance biases can reach 0.4~mag. Therefore, accurately determining bias corrections is critical for precision measurements of cosmological parameters. Files used to make these corrections are available at this https URL

First Cosmology Results Using SNe Ia from the Dark Energy Survey: Analysis, Systematic Uncertainties, and Validation

We present the analysis underpinning the measurement of cosmological parameters from 207 spectroscopically classified SNe Ia from the first 3 years of the Dark Energy Survey Supernova Program (DES-SN), spanning a redshift range of 0.017 < z < 0.849. We combine the DES-SN sample with an external sample of 122 low-redshift (z < 0.1) SNe Ia, resulting in a "DES-SN3YR" sample of 329 SNe Ia. Our cosmological analyses are blinded: after combining our DES-SN3YR distances with constraints from the Cosmic Microwave Background, our uncertainties in the measurement of the dark energy equation-of-state parameter, w, are 0.042 (stat) and 0.059 (stat+syst) at 68% confidence. We provide a detailed systematic uncertainty budget, which has nearly equal contributions from photometric calibration, astrophysical bias corrections, and instrumental bias corrections. We also include several new sources of systematic uncertainty. While our sample is less than one-third the size of the Pantheon sample, our constraints on w are only larger by 1.4×, showing the impact of the DES-SN Ia light-curve quality. We find that the traditional stretch and color standardization parameters of the DES-SNe Ia are in agreement with earlier SN Ia samples such as Pan-STARRS1 and the Supernova Legacy Survey. However, we find smaller intrinsic scatter about the Hubble diagram (0.077 mag). Interestingly, we find no evidence for a Hubble residual step (0.007 ± 0.018 mag) as a function of host-galaxy mass for the DES subset, in 2.4σ tension with previous measurements. We also present novel validation methods of our sample using simulated SNe Ia inserted in DECam images and using large catalog-level simulations to test for biases in our analysis pipelines

A double-blind placebo controlled experimental study of nicotine: I - effects on incentive motivation.

Rationale Brain reward pathways implicated in addiction appear to be less reactive in regular drug users; behavioural manifestations may include decreased sensitivity to natural reinforcers. Objectives This study aimed to replicate earlier findings of abstinence-associated incentive motivation deficits in smokers and to determine whether these can be reversed with nicotine in the form of lozenge. Methods One hundred forty-five smokers were each tested twice, once after receiving nicotine, and once after receiving placebo lozenge in counterbalanced order. Participants completed various tests of incentive motivational functioning: a measure of subjective enjoyment, the Snaith?Hamilton pleasure scale (SHAPS); a simple card sorting task, the card arranging reward responsivity objective test (CARROT) with and without financial incentive; the modified emotional Stroop test; a cue-reactivity task; and a novel reaction time task to explore effects of signals of reward, the incentive motivational enhancement of response speed task. Results Compared with performance during abstinence (placebo condition), nicotine was associated with: higher self-reported pleasure expectations on the SHAPS; enhanced responsiveness to financial reward on the CARROT in smokers who smoked 15 or more cigarettes a day; and greater interference from appetitive words on the Stroop task. Conclusions These results are generally consistent with contemporary neurobiological theories of addiction and suggest that short-term smoking abstinence is associated with impaired reward motivation which can be reversed with nicotine

Spatio-temporal vigilance architecture of an Australian flying-fox colony

The social structure of animal aggregations may vary considerably in both space and time, yet little is known about how this affects vigilance. Here, we investigate the vigilance architecture of a colony of wild-living grey-headed flying-foxes (Pteropus poliocephalus) in Australia, and examine how spatial as well as temporal variation in social organisation influences social and environmental vigilance. We sampled colour-marked individuals at different stages of the reproductive cycle and the year, and at different locations in the colony to examine the effects of temporal and spatial factors on social and environmental vigilance. We found that vigilance architecture reflected the social structure of the colony, with the highest environmental vigilance being displayed by bats at the periphery of the colony, and the highest social vigilance by bats that roosted at intermediate distances from the colony’s edge. Furthermore, we found that vigilance levels reflected changes in reproductive state, with social vigilance increasing towards the mating season, particularly in males. Our findings show that spatial and temporal variation in social structure can have differential effects on social and environmental vigilance. This highlights the necessity to differentiate between functions of vigilance to understand fully vigilance architecture in aggregations of social animals