Search

We present cosmological constraints from the sample of Type Ia supernovae (SNe Ia) discovered and measured during the full 5 yr of the Dark Energy Survey (DES) SN program. In contrast to most previous cosmological samples, in which SNe are classified based on their spectra, we classify the DES SNe using a machine learning algorithm applied to their light curves in four photometric bands. Spectroscopic redshifts are acquired from a dedicated follow-up survey of the host galaxies. After accounting for the likelihood of each SN being an SN Ia, we find 1635 DES SNe in the redshift range 0.10 < z < 1.13 that pass quality selection criteria sufficient to constrain cosmological parameters. This quintuples the number of high-quality z > 0.5 SNe compared to the previous leading compilation of Pantheon+ and results in the tightest cosmological constraints achieved by any SN data set to date. To derive cosmological constraints, we combine the DES SN data with a high-quality external low-redshift sample consisting of 194 SNe Ia spanning 0.025 < z < 0.10. Using SN data alone and including systematic uncertainties, we find Ω _M = 0.352 ± 0.017 in flat ΛCDM. SN data alone now require acceleration ( q _0 < 0 in ΛCDM) with over 5 σ confidence. We find $({{\rm{\Omega }}}_{{\rm{M}}},w)=({0.264}_{-0.096}^{+0.074},-{0.80}_{-0.16}^{+0.14})$ in flat w CDM. For flat w _0 w _a CDM, we find $({{\rm{\Omega }}}_{{\rm{M}}},{w}_{0},{w}_{a})=({0.495}_{-0.043}^{+0.033},-{0.36}_{-0.30}^{+0.36},-{8.8}_{-4.5}^{+3.7})$ , consistent with a constant equation of state to within ∼2 σ . Including Planck cosmic microwave background, Sloan Digital Sky Survey baryon acoustic oscillation, and DES 3 × 2pt data gives (Ω _M , w ) = (0.321 ± 0.007, −0.941 ± 0.026). In all cases, dark energy is consistent with a cosmological constant to within ∼2 σ . Systematic errors on cosmological parameters are subdominant compared to statistical errors; these results thus pave the way for future photometrically classified SN analyses.

Redshift measurements, primarily obtained from host galaxies, are essential for inferring cosmological parameters from type Ia supernovae (SNe Ia). Matching SNe to host galaxies using images is nontrivial, resulting in a subset of SNe with mismatched hosts and thus incorrect redshifts. We evaluate the host galaxy mismatch rate and resulting biases on cosmological parameters from simulations modeled after the Dark Energy Survey 5 Yr (DES-SN5YR) photometric sample. For both DES-SN5YR data and simulations, we employ the directional light radius method for host galaxy matching. In our SN Ia simulations, we find that 1.7% of SNe are matched to the wrong host galaxy, with redshift differences between the true and matched hosts of up to 0.6. Using our analysis pipeline, we determine the shift in the dark energy equation of state parameter (Δ w ) due to including SNe with incorrect host galaxy matches. For SN Ia–only simulations, we find Δ w = 0.0013 ± 0.0026 with constraints from the cosmic microwave background. Including core-collapse SNe and peculiar SNe Ia in the simulation, we find that Δ w ranges from 0.0009 to 0.0032, depending on the photometric classifier used. This bias is an order of magnitude smaller than the expected total uncertainty on w from the DES-SN5YR sample of ∼0.03. We conclude that the bias on w from host galaxy mismatch is much smaller than the uncertainties expected from the DES-SN5YR sample, but we encourage further studies to reduce this bias through better host-matching algorithms or selection cuts.

The tip of the red giant branch (TRGB) provides a luminous standard candle for constructing distance ladders to measure the Hubble constant. In practice, its measurements via edge-detection response (EDR) are complicated by the apparent fuzziness of the tip and the multipeak landscape of the EDR. Previously, we optimized an unsupervised algorithm, Comparative Analysis of TRGBs, to minimize the variance among multiple halo fields per host without relying on individualized choices, achieving state-of-the-art ∼

The tip of the red giant branch (TRGB) is an apparent discontinuity of the luminosity function (LF) due to the end of the red giant evolutionary phase and is used to measure distances in the local universe. In practice, tip localization via edge detection response (EDR) relies on several methods applied on a case-by-case basis. It is hard to evaluate how individual choices affect a distance estimation using only a single host field while also avoiding confirmation bias. To devise a standardized approach, we compare unsupervised , algorithmic analyses of the TRGB in multiple halo fields per galaxy. We first optimize methods for the lowest field-to-field dispersion, including spatial filtering, smoothing, and weighting of LF, color band selection, and tip selection based on the number of likely RGB stars and the ratio of stars below versus above the tip ( R ). We find R , which we call the tip contrast , to be the most important indicator of the quality of EDR measurements; higher R selection can decrease field-to-field dispersion. Further, since R is found to correlate with the age or metallicity of the stellar population based on theoretical modeling, it might result in a displacement of the detected tip magnitude. We find a tip-contrast relation with a slope of −0.023 ± 0.0046 mag/ratio, an ∼5 σ result that can be used to correct these variations in the detections. When using TRGB to establish a distance ladder, consistent TRGB standardization using tip-contrast relation across rungs is vital to make robust cosmological measurements.

Wavelength-dependent atmospheric effects impact photometric supernova flux measurements for ground-based observations. We present corrections on supernova flux measurements from the Dark Energy Survey Supernova Program’s 5YR sample (DES-SN5YR) for differential chromatic refraction (DCR) and wavelength-dependent seeing, and we show their impact on the cosmological parameters w and Ω _m . We use g − i colors of Type Ia supernovae to quantify astrometric offsets caused by DCR and simulate point-spread functions (PSFs) using the GalSIM package to predict the shapes of the PSFs with DCR and wavelength-dependent seeing. We calculate the magnitude corrections and apply them to the magnitudes computed by the DES-SN5YR photometric pipeline. We find that for the DES-SN5YR analysis, not accounting for the astrometric offsets and changes in the PSF shape cause an average bias of +0.2 mmag and −0.3 mmag, respectively, with standard deviations of 0.7 mmag and 2.7 mmag across all DES observing bands ( griz ) throughout all redshifts. When the DCR and seeing effects are not accounted for, we find that w and Ω _m are lower by less than 0.004 ± 0.02 and 0.001 ± 0.01, respectively, with 0.02 and 0.01 being the 1 σ statistical uncertainties. Although we find that these biases do not limit the constraints of the DES-SN5YR sample, future surveys with much higher statistics, lower systematics, and especially those that observe in the u band will require these corrections as wavelength-dependent atmospheric effects are larger at shorter wavelengths. We also discuss limitations of our method and how they can be better accounted for in future surveys.

Photometric classification of supernovae (SNe) is imperative as recent and upcoming optical time-domain surveys, such as the Large Synoptic Survey Telescope (LSST), overwhelm the available resources for spectrosopic follow-up. Here we develop a range of light curve (LC) classification pipelines, trained on 513 spectroscopically classified SNe from the Pan-STARRS1 Medium-Deep Survey (PS1-MDS): 357 Type Ia, 93 Type II, 25 Type IIn, 21 Type Ibc, and 17 Type I superluminous SNe (SLSNe). We present a new parametric analytical model that can accommodate a broad range of SN LC morphologies, including those with a plateau, and fit this model to data in four PS1 filters (gP1rP1iP1zP1). We test a number of feature extraction methods, data augmentation strategies, and machine-learning algorithms to predict the class of each SN. Our best pipelines result in ≈90% average accuracy, ≈70% average purity, and ≈80% average completeness for all SN classes, with the highest success rates for SNe Ia and SLSNe and the lowest for SNe Ibc. Despite the greater complexity of our classification scheme, the purity of our SN Ia classification, ≈95%, is on par with methods developed specifically for Type Ia versus non-Type Ia binary classification. As the first of its kind, this study serves as a guide to developing and training classification algorithms for a wide range of SN types with a purely empirical training set, particularly one that is similar in its characteristics to the expected LSST main survey strategy. Future work will implement this classification pipeline on ≈3000 PS1/MDS LCs that lack spectroscopic classification. [ABSTRACT FROM AUTHOR]

In this work, we investigate the likelihood of association between real-time, neutrino alerts with teraelectronvolt to petaelectronvolt energy from IceCube and optical counterparts in the form of core-collapse supernovae (CC SNe). The optical follow-up of IceCube alerts requires two main instrumental capabilities: (1) deep imaging, since 73% of neutrinos would come from CC SNe at redshifts z > 0.3, and (2) a large field of view (FoV), since typical IceCube muon neutrino pointing accuracy is on the order of ∼1 deg. With Blanco/DECam (gri to 24th magnitude and 2.2 deg diameter FoV), we performed a triggered optical follow-up observation of two IceCube alerts, IC170922A and IC171106A, on six nights during the three weeks following each alert. For the IC170922A (IC171106A) follow-up observations, we expect that 12.1% (9.5%) of coincident CC SNe at z ≲ 0.3 are detectable, and that, on average, 0.23 (0.07) unassociated SNe in the neutrino 90% containment regions also pass our selection criteria. We find two candidate CC SNe that are temporally coincident with the neutrino alerts in the FoV, but none in the 90% containment regions, a result that is statistically consistent with expected rates of background CC SNe for these observations. If CC SNe are the dominant source of teraelectronvolt to petaelectronvolt neutrinos, we would expect an excess of coincident CC SNe to be detectable at the 3σ confidence level using DECam observations similar to those of this work for ∼60 (∼200) neutrino alerts with (without) redshift information for all candidates. [ABSTRACT FROM AUTHOR]

We present a new Bayesian hierarchical model (BHM) named Steve for performing Type Ia supernova (SN Ia) cosmology fits. This advances previous works by including an improved treatment of Malmquist bias, accounting for additional sources of systematic uncertainty, and increasing numerical efficiency. Given light-curve fit parameters, redshifts, and host-galaxy masses, we fit Steve simultaneously for parameters describing cosmology, SN Ia populations, and systematic uncertainties. Selection effects are characterized using Monte Carlo simulations. We demonstrate its implementation by fitting realizations of SN Ia data sets where the SN Ia model closely follows that used in Steve. Next, we validate on more realistic SNANA simulations of SN Ia samples from the Dark Energy Survey and low-redshift surveys (DES Collaboration et al. 2018). These simulated data sets contain more than 60,000 SNe Ia, which we use to evaluate biases in the recovery of cosmological parameters, specifically the equation of state of dark energy, w. This is the most rigorous test of a BHM method applied to SN Ia cosmology fitting and reveals small w biases that depend on the simulated SN Ia properties, in particular the intrinsic SN Ia scatter model. This w bias is less than 0.03 on average, less than half the statistical uncertainty on w. These simulation test results are a concern for BHM cosmology fitting applications on large upcoming surveys; therefore, future development will focus on minimizing the sensitivity of Steve to the SN Ia intrinsic scatter model. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

We present griz light curves of 251 SNe Ia from the first 3 years of the Dark Energy Survey Supernova Program’s (DES-SN) spectroscopically classified sample. The photometric pipeline described in this paper produces the calibrated fluxes and associated uncertainties used in the cosmological parameter analysis by employing a scene modeling approach that simultaneously models a variable transient flux and temporally constant host galaxy. We inject artificial point sources onto DECam images to test the accuracy of our photometric method. Upon comparison of input and measured artificial supernova fluxes, we find that flux biases peak at 3 mmag. We require corrections to our photometric uncertainties as a function of host galaxy surface brightness at the transient location, similar to that seen by the DES Difference Imaging Pipeline used to discover transients. The public release of the light curves can be found at https://des.ncsa.illinois.edu/releases/sn. [ABSTRACT FROM AUTHOR]

The Wide Field InfraRed Survey Telescope (WFIRST) was the highest-ranked large space-based mission of the 2010 New Worlds, New Horizons decadal survey. It is now a NASA mission in formulation with a planned launch in the mid 2020s. A primary mission objective is to precisely constrain the nature of dark energy through multiple probes, including Type Ia supernovae (SN Ia). Here, we present the first realistic simulations of the WFIRST SN survey based on current hardware specifications and using open-source tools. We simulate SN light curves and spectra as viewed by the WFIRST wide-field channel (WFC) imager and integral field channel (IFC) spectrometer, respectively. We examine 11 survey strategies with different time allocations between the WFC and IFC, two of which are based upon the strategy described by the WFIRST Science Definition Team, which measures SN distances exclusively from IFC data. We propagate statistical and, crucially, systematic uncertainties to predict the Dark Energy Task Force figure of merit (FoM) for each strategy. Of the strategies investigated, we find the most successful to be WFC focused. However, further work in constraining systematics is required to fully optimize the use of the IFC. Even without improvements to other cosmological probes, the WFIRST SN survey has the potential to increase the FoM by more than an order of magnitude from the current values. Although the survey strategies presented here have not been fully optimized, these initial investigations are an important step in the development of the final hardware design and implementation of the WFIRST mission. [ABSTRACT FROM AUTHOR]

Empirical models of supernova (SN) spectral energy distributions (SEDs) are widely used for SN survey simulations and photometric classifications. The existing library of SED models has excellent optical templates, but limited, poorly constrained coverage of ultraviolet (UV) and infrared (IR) wavelengths. However, both regimes are critical for the design and operation of future SN surveys, particularly at IR wavelengths that will be accessible with the James Webb Space Telescope and the Wide-Field Infrared Survey Telescope. We create a public repository of improved empirical SED templates using a sampling of Type Ia and core-collapse (CC) photometric light curves to extend the Type Ia parameterized SALT2 model and a set of SN Ib, SN Ic, and SN II SED templates into the UV and near-IR. We apply this new repository of extrapolated SN SED models to examine how future surveys can discriminate between CC and Type Ia SNe at UV and IR wavelengths, and present an open-source software package written in Python, SNSEDextend, that enables users to generate their own extrapolated SEDs. [ABSTRACT FROM AUTHOR]

The coalescence of a binary neutron star pair is expected to produce gravitational waves (GW) and electromagnetic radiation, both of which may be detectable with currently available instruments. We describe a search for a predicted r-process optical transient from these mergers, dubbed the “kilonova” (KN), using griz broadband data from the Dark Energy Survey Supernova Program (DES-SN). Some models predict KNe to be redder, shorter-lived, and dimmer than supernovae (SNe), but the event rate of KNe is poorly constrained. We simulate KN and SN light curves with the Monte-Carlo simulation code SNANA to optimize selection requirements, determine search efficiency, and predict SN backgrounds. Our analysis of the first two seasons of DES-SN data results in 0 events, and is consistent with our prediction of 1.1 ± 0.2 background events based on simulations of SNe. From our prediction, there is a 33% chance of finding 0 events in the data. Assuming no underlying galaxy flux, our search sets 90% upper limits on the KN volumetric rate of 1.0 Gpc−3 yr−1 for the dimmest KN model we consider (peak i-band absolute magnitude mag) and 2.4 Gpc−3 yr−1 for the brightest ( mag). Accounting for anomalous subtraction artifacts on bright galaxies, these limits are ∼3 times higher. This analysis is the first untriggered optical KN search and informs selection requirements and strategies for future KN searches. Our upper limits on the KN rate are consistent with those measured by GW and gamma-ray burst searches. [ABSTRACT FROM AUTHOR]

We present a new technique to create a bin-averaged Hubble diagram (HD) from photometrically identified SN Ia data. The resulting HD is corrected for selection biases and contamination from core-collapse (CC) SNe, and can be used to infer cosmological parameters. This method, called “BEAMS with Bias Corrections” (BBC), includes two fitting stages. The first BBC fitting stage uses a posterior distribution that includes multiple SN likelihoods, a Monte Carlo simulation to bias-correct the fitted SALT-II parameters, and CC probabilities determined from a machine-learning technique. The BBC fit determines (1) a bin-averaged HD (average distance versus redshift), and (2) the nuisance parameters α and β, which multiply the stretch and color (respectively) to standardize the SN brightness. In the second stage, the bin-averaged HD is fit to a cosmological model where priors can be imposed. We perform high-precision tests of the BBC method by simulating large (150,000 event) data samples corresponding to the Dark Energy Survey Supernova Program. Our tests include three models of intrinsic scatter, each with two different CC rates. In the BBC fit, the SALT-II nuisance parameters α and β are recovered to within 1% of their true values. In the cosmology fit, we determine the dark energy equation of state parameter w using a fixed value of as a prior: averaging over all six tests based on 6 × 150,000 = 900,000 SNe, there is a small w-bias of . Finally, the BBC fitting code is publicly available in the SNANA package. [ABSTRACT FROM AUTHOR]

We analyze the wavelength-dependent variability of a sample of spectroscopically confirmed active galactic nuclei selected from near-UV (NUV) variable sources in the GALEX Time Domain Survey that have a large amplitude of optical variability (difference-flux S/N > 3) in the Pan-STARRS1 Medium Deep Survey (PS1 MDS). By matching GALEX and PS1 epochs in five bands (NUV, gP1, rP1, iP1, zP1) in time, and taking their flux difference, we create co-temporal difference-flux spectral energy distributions () using two chosen epochs for each of the 23 objects in our sample, on timescales of about a year. We confirm the “bluer-when-brighter” trend reported in previous studies, and measure a median spectral index of the of = 2.1 that is consistent with an accretion disk spectrum. We further fit the of each source with a standard accretion disk model in which the accretion rate changes from one epoch to the other. In our sample, 17 out of 23 (∼74%) sources are described well by this variable accretion-rate disk model, with a median average characteristic disk temperature of K that is consistent with the temperatures expected, given the distribution of accretion rates and black hole masses inferred for the sample. Our analysis also shows that the variable accretion rate model is a better fit to the than a simple power law. [ABSTRACT FROM AUTHOR]

We present photometry and spectroscopy of PS1-14bj, a hydrogen-poor superluminous supernova (SLSN) at redshift z = 0.5215 discovered in the last months of the Pan-STARRS1 Medium Deep Survey. PS1-14bj stands out because of its extremely slow evolution, with an observed rise of rest-frame days, and exponential decline out to ∼250 days past peak at a measured rate of , consistent with fully trapped 56Co decay. This is the longest rise time measured in an SLSN to date, and the first SLSN to show a rise time consistent with pair-instability supernova (PISN) models. Compared to other slowly evolving SLSNe, it is spectroscopically similar to the prototype SN 2007bi at maximum light, although lower in luminosity () and with a flatter peak than previous events. PS1-14bj shows a number of peculiar properties, including a near-constant color temperature for days past peak, and strong emission lines from [O iii] λ5007 and [O iii] λ4363 with a velocity width of ∼3400 km s−1 in its late-time spectra. These both suggest there is a sustained source of heating over very long timescales, and are incompatible with a simple 56Ni-powered/PISN interpretation. A modified magnetar model including emission leakage at late times can reproduce the light curve, in which case the blue continuum and [O iii] features are interpreted as material heated and ionized by the inner pulsar wind nebula becoming visible at late times. Alternatively, the late-time heating could be due to interaction with a shell of H-poor circumstellar material. [ABSTRACT FROM AUTHOR]

Current cosmological analyses, which use Type Ia supernova observations, combine supernova (SN) samples to expand the redshift range beyond that of a single sample and increase the overall sample size. The inhomogeneous photometric calibration between different SN samples is one of the largest systematic uncertainties of the cosmological parameter estimation. To place these different samples on a single system, analyses currently use observations of a small sample of very bright flux standards on the Hubble Space Telescope system. We propose a complementary method, called “Supercal,” in which we use measurements of secondary standards in each system, compare these to measurements of the same stars in the Pan-STARRS1 (PS1) system, and determine the offsets for each system relative to PS1, placing all SN observations on a single, consistent photometric system. PS1 has observed 3π of the sky and has a relative calibration of better than 5 mmag (for ∼15 < griz < 21 mag), making it an ideal reference system. We use this process to recalibrate optical observations taken by the following SN samples: PS1, Supernova Legacy Survey, SDSS, CSP, and CfA1-4. We measure discrepancies on average of 10 mmag, but up to 35 mmag, in various optical passbands. We find that correcting for these differences changes the recovered values for the dark energy equation of state parameter, w, by an average of 2.6%. This change is roughly half the size of current statistical constraints on w. The size of this effect strongly depends on the error in the B − V calibration of the low-z surveys. The Supercal method will allow future analyses to tie past samples to the best calibrated sample. [ABSTRACT FROM AUTHOR]

We present Hubble Space Telescope (HST) rest-frame ultraviolet imaging of the host galaxies of 16 hydrogen-poor superluminous supernovae (SLSNe), including 11 events from the Pan-STARRS Medium Deep Survey. Taking advantage of the superb angular resolution of HST, we characterize the galaxies’ morphological properties, sizes, and star formation rate (SFR) densities. We determine the supernova (SN) locations within the host galaxies through precise astrometric matching and measure physical and host-normalized offsets as well as the SN positions within the cumulative distribution of UV light pixel brightness. We find that the host galaxies of H-poor SLSNe are irregular, compact dwarf galaxies, with a median half-light radius of just 0.9 kpc. The UV-derived SFR densities are high (), suggesting that SLSNe form in overdense environments. Their locations trace the UV light of their host galaxies, with a distribution intermediate between that of long-duration gamma-ray bursts (LGRBs; which are strongly clustered on the brightest regions of their hosts) and a uniform distribution (characteristic of normal core-collapse SNe), though cannot be statistically distinguished from either with the current sample size. Taken together, this strengthens the picture that SLSN progenitors require different conditions than those of ordinary core-collapse SNe to form and that they explode in broadly similar galaxies as do LGRBs. If the tendency for SLSNe to be less clustered on the brightest regions than are LGRBs is confirmed by a larger sample, this would indicate a different, potentially lower-mass progenitor for SLSNe than LRGBs. [ABSTRACT FROM AUTHOR]

We present the GALEX detection of a UV burst at the time of explosion of an optically normal supernova (SN) IIP (PS1-13arp) from the Pan-STARRS1 survey at z = 0.1665. The temperature and luminosity of the UV burst match the theoretical predictions for shock breakout in a red supergiant (RSG), but with a duration a factor of ∼50 longer than expected. We compare the NUV light curve of PS1-13arp to previous GALEX detections of SNe IIP and find clear distinctions that indicate that the UV emission is powered by shock breakout, and not by the subsequent cooling envelope emission previously detected in these systems. We interpret the ∼1 day duration of the UV signal with a shock breakout in the wind of an RSG with a pre-explosion mass-loss rate of yr−1. This mass-loss rate is enough to prolong the duration of the shock breakout signal, but not enough to produce an excess in the optical plateau light curve or narrow emission lines powered by circumstellar interaction. This detection of non-standard, potentially episodic high mass loss in an RSG SN progenitor has favorable consequences for the prospects of future wide-field UV surveys to detect shock breakout directly in these systems, and provide a sensitive probe of the pre-explosion conditions of SN progenitors. [ABSTRACT FROM AUTHOR]

The combination of multiple observational probes has long been advocated as a powerful technique to constrain cosmological parameters, in particular dark energy. The Dark Energy Survey has measured 207 spectroscopically confirmed type Ia supernova light curves, the baryon acoustic oscillation feature, weak gravitational lensing, and galaxy clustering. Here we present combined results from these probes, deriving constraints on the equation of state, w, of dark energy and its energy density in the Universe. Independently of other experiments, such as those that measure the cosmic microwave background, the probes from this single photometric survey rule out a Universe with no dark energy, finding w=-0.80&#95;{-0.11}^{+0.09}. The geometry is shown to be consistent with a spatially flat Universe, and we obtain a constraint on the baryon density of Ω&#95;{b}=0.069&#95;{-0.012}^{+0.009} that is independent of early Universe measurements. These results demonstrate the potential power of large multiprobe photometric surveys and pave the way for order of magnitude advances in our constraints on properties of dark energy and cosmology over the next decade.

The Hubble constant (H&#95;{0}) estimated from the local Cepheid-supernova distance ladder is in 3-σ tension with the value extrapolated from cosmic microwave background (CMB) data assuming the standard cosmological model. Whether this tension represents new physics or systematic effects is the subject of intense debate. Here, we investigate how new, independent H&#95;{0} estimates can arbitrate this tension, assessing whether the measurements are consistent with being derived from the same model using the posterior predictive distribution (PPD). We show that, with existing data, the inverse distance ladder formed from BOSS baryon acoustic oscillation measurements and the Pantheon supernova sample yields an H&#95;{0} posterior near identical to the Planck CMB measurement. The observed local distance ladder value is a very unlikely draw from the resulting PPD. Turning to the future, we find that a sample of ∼50 binary neutron star "standard sirens" (detectable within the next decade) will be able to adjudicate between the local and CMB estimates.

In 1964, Refsdal hypothesized that a supernova whose light traversed multiple paths around a strong gravitational lens could be used to measure the rate of cosmic expansion. We report the discovery of such a system. In Hubble Space Telescope imaging, we have found four images of a single supernova forming an Einstein cross configuration around a redshift z = 0.54 elliptical galaxy in the MACS J1149.6+2223 cluster. The cluster's gravitational potential also creates multiple images of the z = 1.49 spiral supernova host galaxy, and a future appearance of the supernova elsewhere in the cluster field is expected. The magnifications and staggered arrivals of the supernova images probe the cosmic expansion rate, as well as the distribution of matter in the galaxy and cluster lenses., (Copyright © 2015, American Association for the Advancement of Science.)