Explore the vast range of titles available.

The Dark Energy Survey (DES) is a five-year optical imaging campaign with the goal of understanding the origin of cosmic acceleration. DES performs a ∼5000 deg2 survey of the southern sky in five optical bands (g, r, i, z, Y) to a depth of ∼24th magnitude. Contemporaneously, DES performs a deep, time-domain survey in four optical bands (g, r, i, z) over ∼27 deg2. DES exposures are processed nightly with an evolving data reduction pipeline and evaluated for image quality to determine if they need to be retaken. Difference imaging and transient source detection are also performed in the time domain component nightly. On a bi-annual basis, DES exposures are reprocessed with a refined pipeline and coadded to maximize imaging depth. Here we describe the DES image processing pipeline in support of DES science, as a reference for users of archival DES data, and as a guide for future astronomical surveys.

We describe the model for mapping from sky brightness to the digital output of the Dark Energy Camera (DECam) and the algorithms adopted by the Dark Energy Survey (DES) for inverting this model to obtain photometric measures of celestial objects from the raw camera output. This calibration aims for fluxes that are uniform across the camera field of view and across the full angular and temporal span of the DES observations, approaching the accuracy limits set by shot noise for the full dynamic range of DES observations. The DES pipeline incorporates several substantive advances over standard detrending techniques, including principal-components-based sky and fringe subtraction; correction of the \"brighter-fatter\" nonlinearity; use of internal consistency in on-sky observations to disentangle the influences of quantum efficiency, pixel-size variations, and scattered light in the dome flats; and pixel-by-pixel characterization of instrument spectral response, through combination of internal-consistency constraints with auxiliary calibration data. This article provides conceptual derivations of the detrending/calibration steps, and the procedures for obtaining the necessary calibration data. Other publications will describe the implementation of these concepts for the DES operational pipeline, the detailed methods, and the validation that the techniques can bring DECam photometry and astrometry within 2 mmag and 3 mas, respectively, of fundamental atmospheric and statistical limits. The DES techniques should be broadly applicable to wide-field imagers.

The transactivation properties of the two estrogen receptors, ERα and ERβ, were examined with different ligands in the context of an estrogen response element and an AP1 element. ERα and ERβ were shown to signal in opposite ways when complexed with the natural hormone estradiol from an AP1 site: with ERα, 17β-estradiol activated transcription, whereas with ERβ, 17β-estradiol inhibited transcription. Moreover, the antiestrogens tamoxifen, raloxifene, and Imperial Chemical Industries 164384 were potent transcriptional activators with ERβ at an AP1 site. Thus, the two ERs signal in different ways depending on ligand and response element. This suggests that ERα and ERβ may play different roles in gene regulation.

We describe the model for mapping from sky brightness to the digital output of the Dark Energy Camera (DECam) and the algorithms adopted by the Dark Energy Survey (DES) for inverting this model to obtain photometric measures of celestial objects from the raw camera output. This calibration aims for fluxes that are uniform across the camera field of view and across the full angular and temporal span of the DES observations, approaching the accuracy limits set by shot noise for the full dynamic range of DES observations. The DES pipeline incorporates several substantive advances over standard detrending techniques, including principal-components-based sky and fringe subtraction; correction of the “brighter-fatter” nonlinearity; use of internal consistency in on-sky observations to disentangle the influences of quantum efficiency, pixel-size variations, and scattered light in the dome flats; and pixel-by-pixel characterization of instrument spectral response, through combination of internal-consistency constraints with auxiliary calibration data. This article provides conceptual derivations of the detrending/calibration steps, and the procedures for obtaining the necessary calibration data. Other publications will describe the implementation of these concepts for the DES operational pipeline, the detailed methods, and the validation that the techniques can bring DECam photometry and astrometry within ≈2 mmag and ≈3 mas, respectively, of fundamental atmospheric and statistical limits. The DES techniques should be broadly applicable to wide-field imagers.

The Dark Energy Survey (DES) is a five-year optical imaging campaign with the goal of understanding the origin of cosmic acceleration. DES performs a ∼5000 deg² survey of the southern sky in five optical bands (g, r, i, z, Y) to a depth of ∼24th magnitude. Contemporaneously, DES performs a deep, time-domain survey in four optical bands (g, r, i, z) over ∼27 deg². DES exposures are processed nightly with an evolving data reduction pipeline and evaluated for image quality to determine if they need to be retaken. Difference imaging and transient source detection are also performed in the time domain component nightly. On a bi-annual basis, DES exposures are reprocessed with a refined pipeline and coadded to maximize imaging depth. Here we describe the DES image processing pipeline in support of DES science, as a reference for users of archival DES data, and as a guide for future astronomical surveys.

The Dark Energy Survey (DES) is a five-year optical imaging campaign with the goal of understanding the origin of cosmic acceleration. DES performs a 5000 deg2 survey of the southern sky in five optical bands (g, r, i, z, Y) to a depth of 24th magnitude. Contemporaneously, DES performs a deep, time-domain survey in four optical bands (g, r, i, z) over 27 deg2. DES exposures are processed nightly with an evolving data reduction pipeline and evaluated for image quality to determine if they need to be retaken. Difference imaging and transient source detection are also performed in the time domain component nightly. On a bi-annual basis, DES exposures are reprocessed with a refined pipeline and coadded to maximize imaging depth. In this paper, we describe the DES image processing pipeline in support of DES science, as a reference for users of archival DES data, and as a guide for future astronomical surveys.

Synergies between large-scale radio-continuum and optical/near-infrared galaxy surveys are a powerful tool for cosmology. Cross-correlating these surveys can constrain the redshift distribution of radio sources, mitigate systematic effects, and place constraints on cosmological models. We perform the first measurement of the clustering cross-spectrum between radio-continuum sources in the Evolutionary Map of the Universe (EMU) survey and galaxies from the ESA Euclid satellite mission's Q1 release. Our goal is to detect and characterise the cross-correlation signal, test its robustness against systematic effects, and compare our measurements with theoretical predictions. We use data from the Australian SKA Pathfinder's EMU Main Survey, which overlaps with the Euclid Deep Field South. We generate two radio-source catalogues using different source finders to create galaxy maps. We measure the harmonic-space cross-correlation signal using a pseudo-spectrum estimator. The measured signal is compared to theoretical predictions based on a CDM cosmology, using several models for the EMU source redshift distribution and bias. We report detection above 8 of the cross-correlation signal consistent across all tested models and data sets. The measured cross-spectra from the two radio catalogues are in excellent agreement, demonstrating that the cross-correlation is robust against the choice of source-finding algorithm. The measured signal also agrees with theoretical models developed from previous cross-correlation studies and simulations. This pathfinder study establishes a statistically significant cross-correlation between EMU and Euclid. The robustness of the signal is a crucial validation of the methodology, paving the way for future large-scale analyses leveraging the full power of this synergy to constrain cosmological parameters and our understanding of galaxy evolution.

We present a new atmospheric extinction curve for Mauna Kea spanning 3200--9700 It is the most comprehensive to date, being based on some 4285 standard star spectra obtained on 478 nights spread over a period of 7 years obtained by the Nearby SuperNova Factory using the SuperNova Integral Field Spectrograph. This mean curve and its dispersion can be used as an aid in calibrating spectroscopic or imaging data from Mauna Kea, and in estimating the calibration uncertainty associated with the use of a mean extinction curve. Our method for decomposing the extinction curve into physical components, and the ability to determine the chromatic portion of the extinction even on cloudy nights, is described and verified over the wide range of conditions sampled by our large dataset. We demonstrate good agreement with atmospheric science data obtain at nearby Mauna Loa Observatory, and with previously published measurements of the extinction above Mauna Kea.

Strong lensing by massive galaxy clusters can provide magnification of the flux and even multiple images of the galaxies that lie behind them. This phenomenon facilitates observations of high-redshift supernovae (SNe), that would otherwise remain undetected. Type Ia supernovae (SNe Ia) detections are of particular interest because of their standard brightness, since they can be used to improve either cluster lensing models or cosmological parameter measurements. We present a ground-based, near-infrared search for lensed SNe behind the galaxy cluster Abell 370. Our survey was based on 15 epochs of J-band observations with the HAWK-I instrument on the Very Large Telescope (VLT). We use Hubble Space Telescope (HST) photometry to infer the global properties of the multiply-imaged galaxies. Using a recently published lensing model of Abell 370, we also present the predicted magnifications and time delays between the images. In our survey, we did not discover any live SNe from the 13 lensed galaxies with 47 multiple images behind Abell 370. This is consistent with the expectation of \\(0.090.02\\) SNe calculated based on the measured star formation rate. We compare the expectations of discovering strongly lensed SNe in our survey and that performed with HST during the Hubble Frontier Fields (HFF) programme. We also show the expectations of search campaigns that can be conducted with future facilities, such as the James Webb Space Telescope (JWST) or the Wide-Field Infrared Survey Telescope (WFIRST). We show that the NIRCam instrument aboard the JWST will be sensitive to most SN multiple images in the strongly lensed galaxies and thus will be able to measure their time delays if observations are scheduled accordingly.

The Cosmology Data Management system (CosmoDM) is an automated and flexible data management system for the processing and calibration of data from optical photometric surveys. It is designed to run on supercomputers and to minimize disk I/O to enable scaling to very high throughput during periods of reprocessing. It serves as an early prototype for one element of the ground-based processing required by the Euclid mission and will also be employed in the preparation of ground based data needed in the eROSITA X-ray all sky survey mission. CosmoDM consists of two main pipelines. The first is the single-epoch or detrending pipeline, which is used to carry out the photometric and astrometric calibration of raw exposures. The second is the co- addition pipeline, which combines the data from individual exposures into deeper coadd images and science ready catalogs. A novel feature of CosmoDM is that it uses a modified stack of As- tromatic software which can read and write tile compressed images. Since 2011, CosmoDM has been used to process data from the DECam, the CFHT MegaCam and the Pan-STARRS cameras. In this paper we shall describe how processed Pan-STARRS data from CosmoDM has been used to optically confirm and measure photometric redshifts of Planck-based Sunyaev-Zeldovich effect selected cluster candidates.