273 Search Results

Abstract We evaluate the performance of the Legacy Survey of Space and Time Science Pipelines Difference Image Analysis (DIA) on simulated images. By adding synthetic sources to galaxies on images, we trace the recovery of injected synthetic sources to evaluate the pipeline on images from the Dark Energy Science Collaboration Data Challenge 2. The pipeline performs well, with efficiency and flux accuracy consistent with the signal-to-noise ratio of the input images. We explore different spatial degrees of freedom for the Alard–Lupton polynomial-Gaussian image subtraction kernel and analyze for trade-offs in efficiency versus artifact rate. Increasing the kernel spatial degrees of freedom reduces the artifact rate without loss of efficiency. The flux measurements with different kernel spatial degrees of freedom are consistent. We also here provide a set of DIA flags that substantially filter out artifacts from the DIA source table. We explore the morphology and possible origins of the observed remaining subtraction artifacts and suggest that given the complexity of these artifact origins, a convolution kernel with a set of flexible bases with spatial variation may be needed to yield further improvements.

This paper presents the results of the Power To Melt and Maneuverability (P2M) Simulation Exercise on past fuel melting irradiation experiments, organized within the Organisation for Economic Co-operation and Development/Nuclear Energy Agency Framework for IrraDiation ExperimentS (FIDES) framework by the Core Group (CEA, EDF, and SCK·CEN) and open to all FIDES members. The exercise consisted in simulating two past power ramps where fuel melting was detected: (1) the xM3 staircase power transient [ramp terminal level (RTL) 70 kW·m^-1, average burnup 27 GWd·tU^-1], carried out in 2005 in the R2 reactor at Studsvik (Sweden), where the rodlet maintained its integrity, and (2) the HBC4 fast power transient (RTL 66 kW·m^-1, average burnup 48 GWd·tU^-1), carried out in 1987 in the BR2 reactor at SCK·CEN (Belgium), where the cladding failed during the experiment. The exercise was joined by 13 organizations from 9 countries using 11 different fuel performance codes. In this paper, the main results of the Simulation Exercise are presented and compared to available postirradiation examinations (PIE) or on-line measurements during the power ramps (fuel and clad diameters, rod elongation, pellet-clad gap, and fission gas release). Since the focus of the Simulation Exercise is on fuel melting assessment, determination of the boundary between melted/nonmelted fuel and the consequent definition of a melting radius from PIE are first discussed. During the HBC4 ramp, fuel melting was predicted by most of the codes despite differences in the melting models. Higher discrepancies were observed for the xM3 rod that can be attributed partly to power uncertainty and partly to the limited capability of the models to describe partial melting of the fuel during this ramp. Finally, possible code developments to improve simulation results are presented.

The Vera Rubin Observatory Legacy Survey of Space and Time (LSST) is expected to process ~10⁶ transient detections per night. For precision measurements of cosmological parameters and rates, it is critical to understand the detection efficiency, magnitude limits, artifact contamination levels, and biases in the selection and photometry. Here we rigorously test the LSST Difference Image Analysis (DIA) pipeline using simulated images from the Rubin Observatory LSST Dark Energy Science Collaboration Data Challenge (DC2) simulation for the Wide-Fast-Deep survey area. DC2 is the first large-scale (300 deg²) image simulation of a transient survey that includes realistic cadence, variable observing conditions, and CCD image artifacts. We analyze ~15 deg² of DC2 over a 5 yr time span in which artificial point sources from Type Ia supernova (SNIa) light curves have been overlaid onto the images. The magnitude limits per filter are u = 23.66 mag, g = 24.69 mag, r = 24.06 mag, i = 23.45 mag, z = 22.54 mag, and y = 21.62 mag. The artifact contamination levels are ~90% of all detections, corresponding to ~1000 artifacts deg^–2 in g band, and falling to 300 deg^–2 in y band. The photometry has biases <1% for magnitudes 19.5 < m < 23. Our DIA performance on simulated images is similar to that of the Dark Energy Survey difference-imaging pipeline on real images. We also characterize DC2 image properties to produce catalog-level simulations needed for distance bias corrections. We find good agreement between DC2 data and simulations for distributions of signal-to-noise ratio, redshift, and fitted light-curve properties. Applying a realistic SNIa cosmology analysis for redshifts z < 1, we recover the input cosmology parameters to within statistical uncertainties.

ABSTRACT African dust from the Sahara and Sahel regions of Northern Africa is blown intercontinental distances and is the highest portion of atmospheric dust generated each year. During the Northern Hemisphere summer months (boreal summer), these dust events travel into the Caribbean and southern United States. While viability assays, microscopy and bacterial amplicon analyses have shown that dust-associated microbes may be diverse, the specific microbial taxa that are transported intercontinental distances with these dust events remain poorly characterized. To provide new insights into these issues, five metagenomes of Saharan dust events occurring in the Caribbean, collected in the summer months of 2002 and 2008, were analyzed. The data revealed that similar microbial composition existed between three out of the five of the distinct dust events and that fungi were a prominent feature of the metagenomes compared to other environmental samples. These results have implications for better understanding of microbial transport through the atmosphere and may implicate that the dust-associated microbial load transiting the Atlantic with Saharan dust is similar from year to year.

In this work, we introduce the first measurement of cross-correlation between the lensing potential, reconstructed from cosmic microwave background (CMB) polarization data, and the cosmic shear field from galaxy shapes. This measurement is made using data from the POLARBEAR CMB experiment and the Subaru Hyper Suprime-Cam (HSC) survey. By analyzing an 11 deg² overlapping region, we reject the null hypothesis at 3.5σ and constrain the amplitude of the cross-spectrum to $$\widehat{A}$$_lens = 1.70 ± 0.48, where $$\widehat{A}$$_lens is the amplitude normalized with respect to the Planck 2018 prediction, based on the flat Λ cold dark matter cosmology. The first measurement of this cross-spectrum without relying on CMB temperature measurements is possible owing to the deep POLARBEAR map with a noise level of ~6 μK arcmin, as well as the deep HSC data with a high galaxy number density of n_g = 23 arcmin^-2. We present a detailed study of the systematics budget to show that residual systematics in our findings are negligibly small, which demonstrates the future potential of this cross-correlation technique.

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.

We characterize the variation in photometric response of the Dark Energy Camera (DECam) across its 520 Mpix science array during 4 years of operation. These variations are measured using high signal-to-noise aperture photometry of >10⁷ stellar images in thousands of exposures of a few selected fields, with the telescope dithered to move the sources around the array. A calibration procedure based on these results brings the rms variation in aperture magnitudes of bright stars on cloudless nights down to 2–3 mmag, with <1 mmag of correlated photometric errors for stars separated by ≥20''. On cloudless nights, any departures of the exposure zeropoints from a secant airmass law exceeding 1 mmag are plausibly attributable to spatial/temporal variations in aperture corrections. These variations can be inferred and corrected by measuring the fraction of stellar light in an annulus between 6'' and 8'' diameter. Key elements of this calibration include: correction of amplifier nonlinearities; distinguishing pixel-area variations and stray light from quantum-efficiency variations in the flat fields; field-dependent color corrections; and the use of an aperture-correction proxy. The DECam response pattern across the 2° field drifts over months by up to ±9 mmag, in a nearly wavelength-independent low-order pattern. Here, we find no fundamental barriers to pushing global photometric calibrations toward mmag accuracy.

We characterize the ability of the Dark Energy Camera (DECam) to perform relative astrometry across its 500 Mpix, 3 $deg^2$ science field of view, and across 4 years of operation. This is done using internal comparisons of $~ 4 x 10^7$ measurements of high-S/N stellar images obtained in repeat visits to fields of moderate stellar density, with the telescope dithered to move the sources around the array. An empirical astrometric model includes terms for: optical distortions; stray electric fields in the CCD detectors; chromatic terms in the instrumental and atmospheric optics; shifts in CCD relative positions of up to $$\approx 10 \mu m$$ when the DECam temperature cycles; and low-order distortions to each exposure from changes in atmospheric refraction and telescope alignment. Errors in this astrometric model are dominated by stochastic variations with typical amplitudes of 10-30 mas (in a 30 s exposure) and $$5^{\prime}-10^{\prime}$$ arcmin coherence length, plausibly attributed to Kolmogorov-spectrum atmospheric turbulence. The size of these atmospheric distortions is not closely related to the seeing. Given an astrometric reference catalog at density $$\approx 0.7$$ $$arcmin^{-2}$$, e.g. from Gaia, the typical atmospheric distortions can be interpolated to $$\approx$$ 7 mas RMS accuracy (for 30 s exposures) with $$1^{\prime}$$ arcmin coherence length for residual errors. Remaining detectable error contributors are 2-4 mas RMS from unmodelled stray electric fields in the devices, and another 2-4 mas RMS from focal plane shifts between camera thermal cycles. Thus the astrometric solution for a single DECam exposure is accurate to 3-6 mas ( $$\approx$$ 0.02 pixels, or $$\approx$$ 300 nm) on the focal plane, plus the stochastic atmospheric distortion.

Cosmic shear is sensitive to fluctuations in the cosmological matter density field, including on small physical scales, where matter clustering is affected by baryonic physics in galaxies and galaxy clusters, such as star formation, supernovae feedback, and active galactic nuclei feedback. While muddying any cosmological information that is contained in small-scale cosmic shear measurements, this does mean that cosmic shear has the potential to constrain baryonic physics and galaxy formation. We perform an analysis of the Dark Energy Survey (DES) Science Verification (SV) cosmic shear measurements, now extended to smaller scales, and using the Mead et al. (2015) halo model to account for baryonic feedback. While the SV data has limited statistical power, we demonstrate using a simulated likelihood analysis that the final DES data will have the statistical power to differentiate among baryonic feedback scenarios. We also explore some of the difficulties in interpreting the small scales in cosmic shear measurements, presenting estimates of the size of several other systematic effects that make inference from small scales difficult, including uncertainty in the modelling of intrinsic alignment on non-linear scales, ‘lensing bias’, and shape measurement selection effects. For the latter two, we make use of novel image simulations. In conclusion, while future cosmic shear data sets have the statistical power to constrain baryonic feedback scenarios, there are several systematic effects that require improved treatments, in order to make robust conclusions about baryonic feedback.

The macroscopic description of the hysteretic behavior of two–phase flow in porous media remains a challenge. It is not obvious how to represent the underlying pore–scale processes at the Darcy–scale in a consistent way. Darcy–scale thermodynamic models do not completely eliminate hysteresis and our findings indicate that the shape of displacement fronts is an additional source of hysteresis that has not been considered before. This is a shortcoming because effective process behavior such as trapping efficiency of CO₂ or oil production during water flooding are directly linked to pore–scale displacement mechanisms with very different front shape such as capillary fingering, flat frontal displacement, or cluster growth. Here we introduce fluid topology, expressed by the Euler characteristic of the nonwetting phase (χn), as a shape measure of displacement fronts. Using two high–quality data sets obtained by fast X–ray tomography, we show that χn is hysteretic between drainage and imbibition and characteristic for the underlying displacement pattern. In a more physical sense, the Euler characteristic can be interpreted as a parameter describing local fluid connectedness. It may provide the closing link between a topological characterization and macroscopic formulations of two–phase immiscible displacement in porous rock. Since fast X–ray tomography is currently becoming a mature technique, we expect a significant growth in high–quality data sets of real time fluid displacement processes in the future. As a result, the novel measures of fluid topology presented here have the potential to become standard metrics needed to fully explore them.