On 17 August 2017, the Advanced LIGO and Virgo detectors observed the gravitational-wave event GW170817-a strong signal from the merger of a binary neutron-star system. Less than two seconds after the merger, a γ-ray burst (GRB 170817A) was detected within a region of the sky consistent with the LIGO-Virgo-derived location of the gravitational-wave source. This sky region was subsequently observed by optical astronomy facilities, resulting in the identification of an optical transient signal within about ten arcseconds of the galaxy NGC 4993. This detection of GW170817 in both gravitational waves and electromagnetic waves represents the first 'multi-messenger' astronomical observation. Such observations enable GW170817 to be used as a 'standard siren' (meaning that the absolute distance to the source can be determined directly from the gravitational-wave measurements) to measure the Hubble constant. This quantity represents the local expansion rate of the Universe, sets the overall scale of the Universe and is of fundamental importance to cosmology. Here we report a measurement of the Hubble constant that combines the distance to the source inferred purely from the gravitational-wave signal with the recession velocity inferred from measurements of the redshift using the electromagnetic data. In contrast to previous measurements, ours does not require the use of a cosmic 'distance ladder': the gravitational-wave analysis can be used to estimate the luminosity distance out to cosmological scales directly, without the use of intermediate astronomical distance measurements. We determine the Hubble constant to be about 70 kilometres per second per megaparsec. This value is consistent with existing measurements, while being completely independent of them. Additional standard siren measurements from future gravitational-wave sources will enable the Hubble constant to be constrained to high precision.

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We present the first cosmological parameter constraints using measurements of type Ia supernovae (SNe Ia) from the Dark Energy Survey Supernova Program (DES-SN). The analysis uses a subsample of 207 spectroscopically confirmed SNe Ia from the first three years of DES-SN, combined with a low-redshift sample of 122 SNe from the literature. Our “DES-SN3YR” result from these 329 SNe Ia is based on a series of companion analyses and improvements covering SN Ia discovery, spectroscopic selection, photometry, calibration, distance bias corrections, and evaluation of systematic uncertainties. For a flat ΛCDM model we find a matter density . For a flat wCDM model, and combining our SN Ia constraints with those from the cosmic microwave background (CMB), we find a dark energy equation of state , and . For a flat w 0 w a CDM model, and combining probes from SN Ia, CMB and baryon acoustic oscillations, we find and . These results are in agreement with a cosmological constant and with previous constraints using SNe Ia (Pantheon, JLA).

We study radial profiles in Hα equivalent width and specific star formation rate (sSFR) derived from spatially-resolved SDSS-IV MaNGA spectroscopy to gain insight on the physical mechanisms that suppress star formation and determine a galaxy's location in the SFR-M diagram. Even within the star-forming 'main sequence', the measured sSFR decreases with stellar mass, both in an integrated and spatially-resolved sense. Flat sSFR radial profiles are observed for log(M /M ) < 10.5, while star-forming galaxies of higher mass show a significant decrease in sSFR in the central regions, a likely consequence of both larger bulges and an inside-out growth history. Our primary focus is the green valley, constituted by galaxies lying below the star formation main sequence, but not fully passive. In the green valley we find sSFR profiles that are suppressed with respect to star-forming galaxies of the same mass at all galactocentric distances out to 2 effective radii. The responsible quenching mechanism therefore appears to affect the entire galaxy, not simply an expanding central region. The majority of green valley galaxies of log(M /M ) > 10.0 are classified spectroscopically as central low-ionisation emission-line regions (cLIERs). Despite displaying a higher central stellar mass concentration, the sSFR suppression observed in cLIER galaxies is not simply due to the larger mass of the bulge. Drawing a comparison sample of star forming galaxies with the same M and Σ 1 kpc (the mass surface density within 1 kpc), we show that a high Σ 1 kpc is not a sufficient condition for determining central quiescence.

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.