Wide field images taken in several photometric bands allow simultaneous measurement of redshifts for thousands of galaxies. A variety of algorithms to make this measurement have appeared in the last ...few years, the majority of which can be classified as either template- or training-based methods. Among the latter, nearest neighbour estimators stand out as one of the most successful, in terms of both precision and the quality of error estimation. In this paper we describe the Directional Neighbourhood Fitting (DNF) algorithm based on the following: a new neighbourhood metric (Directional Neighbourhood), a photo-z estimation strategy (Neighbourhood Fitting) and a method for generating the photo-z probability distribution function. We compare DNF with other well-known empirical photometric redshift tools using different public data sets (Sloan Digital Sky Survey, VIMOS VLT Deep Survey and Photo-z Accuracy Testing). DNF achieves high-quality results with reliable error.
ABSTRACT We search for excess γ-ray emission coincident with the positions of confirmed and candidate Milky Way satellite galaxies using six years of data from the Fermi Large Area Telescope (LAT). ...Our sample of 45 stellar systems includes 28 kinematically confirmed dark-matter-dominated dwarf spheroidal galaxies (dSphs) and 17 recently discovered systems that have photometric characteristics consistent with the population of known dSphs. For each of these targets, the relative predicted γ-ray flux due to dark matter annihilation is taken from kinematic analysis if available, and estimated from a distance-based scaling relation otherwise, assuming that the stellar systems are DM-dominated dSphs. LAT data coincident with four of the newly discovered targets show a slight preference (each 2 local) for γ-ray emission in excess of the background. However, the ensemble of derived γ-ray flux upper limits for individual targets is consistent with the expectation from analyzing random blank-sky regions, and a combined analysis of the population of stellar systems yields no globally significant excess (global significance ). Our analysis has increased sensitivity compared to the analysis of 15 confirmed dSphs by Ackermann et al. The observed constraints on the DM annihilation cross section are statistically consistent with the background expectation, improving by a factor of ∼2 for large DM masses ( and ) and weakening by a factor of ∼1.5 at lower masses relative to previously observed limits.
ABSTRACT
Analyses of Type Ia supernovae (SNe Ia) have found puzzling correlations between their standardized luminosities and host galaxy properties: SNe Ia in high-mass, passive hosts appear ...brighter than those in lower mass, star-forming hosts. We examine the host galaxies of SNe Ia in the Dark Energy Survey 3-yr spectroscopically confirmed cosmological sample, obtaining photometry in a series of ‘local’ apertures centred on the SN, and for the global host galaxy. We study the differences in these host galaxy properties, such as stellar mass and rest-frame U − R colours, and their correlations with SN Ia parameters including Hubble residuals. We find all Hubble residual steps to be >3σ in significance, both for splitting at the traditional environmental property sample median and for the step of maximum significance. For stellar mass, we find a maximal local step of 0.098 ± 0.018 mag; ∼0.03 mag greater than the largest global stellar mass step in our sample (0.070 ± 0.017 mag). When splitting at the sample median, differences between local and global U − R steps are small, both ∼0.08 mag, but are more significant than the global stellar mass step (0.057 ± 0.017 mag). We split the data into sub-samples based on SN Ia light-curve parameters: stretch (x1) and colour (c), finding that redder objects (c > 0) have larger Hubble residual steps, for both stellar mass and U − R, for both local and global measurements, of ∼0.14 mag. Additionally, the bluer (star-forming) local environments host a more homogeneous SN Ia sample, with local U − R rms scatter as low as 0.084 ± 0.017 mag for blue (c < 0) SNe Ia in locally blue U − R environments.
ABSTRACT
Wide-field imaging surveys such as the Dark Energy Survey (DES) rely on coarse measurements of spectral energy distributions in a few filters to estimate the redshift distribution of source ...galaxies. In this regime, sample variance, shot noise, and selection effects limit the attainable accuracy of redshift calibration and thus of cosmological constraints. We present a new method to combine wide-field, few-filter measurements with catalogues from deep fields with additional filters and sufficiently low photometric noise to break degeneracies in photometric redshifts. The multiband deep field is used as an intermediary between wide-field observations and accurate redshifts, greatly reducing sample variance, shot noise, and selection effects. Our implementation of the method uses self-organizing maps to group galaxies into phenotypes based on their observed fluxes, and is tested using a mock DES catalogue created from N-body simulations. It yields a typical uncertainty on the mean redshift in each of five tomographic bins for an idealized simulation of the DES Year 3 weak-lensing tomographic analysis of σΔz = 0.007, which is a 60 per cent improvement compared to the Year 1 analysis. Although the implementation of the method is tailored to DES, its formalism can be applied to other large photometric surveys with a similar observing strategy.
ABSTRACT
We study the optical gri photometric variability of a sample of 190 quasars within the SDSS Stripe 82 region that have long-term photometric coverage during ∼1998−2020 with SDSS, ...PanSTARRS-1, the Dark Energy Survey, and dedicated follow-up monitoring with Blanco 4m/DECam. With on average ∼200 nightly epochs per quasar per filter band, we improve the parameter constraints from a Damped Random Walk (DRW) model fit to the light curves over previous studies with 10–15 yr baselines and ≲ 100 epochs. We find that the average damping time-scale τDRW continues to rise with increased baseline, reaching a median value of ∼750 d (g band) in the rest frame of these quasars using the 20-yr light curves. Some quasars may have gradual, long-term trends in their light curves, suggesting that either the DRW fit requires very long baselines to converge, or that the underlying variability is more complex than a single DRW process for these quasars. Using a subset of quasars with better-constrained τDRW (less than 20 per cent of the baseline), we confirm a weak wavelength dependence of τDRW∝λ0.51 ± 0.20. We further quantify optical variability of these quasars over days to decades time-scales using structure function (SF) and power spectrum density (PSD) analyses. The SF and PSD measurements qualitatively confirm the measured (hundreds of days) damping time-scales from the DRW fits. However, the ensemble PSD is steeper than that of a DRW on time-scales less than ∼ a month for these luminous quasars, and this second break point correlates with the longer DRW damping time-scale.
Abstract
We describe a multicomponent matched filter (MCMF) cluster confirmation tool designed for the study of large X-ray source catalogues produced by the upcoming X-ray all-sky survey mission ...eROSITA. We apply the method to confirm a sample of 88 clusters with redshifts 0.05 < z < 0.8 in the recently published 2RXS catalogue from the ROSAT All-Sky Survey (RASS) over the 208 deg2 region overlapped by the Dark Energy Survey (DES) Science Verification (DES-SV) data set. In our pilot study, we examine all X-ray sources, regardless of their extent. Our method employs a multicolour red sequence (RS) algorithm that incorporates the X-ray count rate and peak position in determining the region of interest for follow-up and extracts the positionally and colour-weighted optical richness λMCMF as a function of redshift for each source. Peaks in the λMCMF–redshift distribution are identified and used to extract photometric redshifts, richness and uncertainties. The significances of all optical counterparts are characterized using the distribution of richnesses defined along random lines of sight. These significances are used to extract cluster catalogues and to estimate the contamination by random superpositions of unassociated optical systems. The delivered photometric redshift accuracy is δz/(1 + z) = 0.010. We find a well-defined X-ray luminosity–λMCMF relation with an intrinsic scatter of δln (λMCMF|Lx) = 0.21. Matching our catalogue with the DES-SV redMaPPer catalogue yields good agreement in redshift and richness estimates; comparing our catalogue with the South Pole Telescope (SPT) selected clusters shows no inconsistencies. SPT clusters in our data set are consistent with the high-mass extension of the RASS-based λMCMF–mass relation.
The Dark Energy Survey Image Processing Pipeline Morganson, E.; Gruendl, R. A.; Menanteau, F. ...
Publications of the Astronomical Society of the Pacific,
07/2018, Letnik:
130, Številka:
989
Journal Article
Recenzirano
Odprti dostop
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.
ABSTRACT
In this paper, we introduce the deepz deep learning photometric redshift (photo-z) code. As a test case, we apply the code to the PAU survey (PAUS) data in the COSMOS field. deepz reduces ...the σ68 scatter statistic by 50 per cent at iAB = 22.5 compared to existing algorithms. This improvement is achieved through various methods, including transfer learning from simulations where the training set consists of simulations as well as observations, which reduces the need for training data. The redshift probability distribution is estimated with a mixture density network (MDN), which produces accurate redshift distributions. Our code includes an autoencoder to reduce noise and extract features from the galaxy SEDs. It also benefits from combining multiple networks, which lowers the photo-z scatter by 10 per cent. Furthermore, training with randomly constructed coadded fluxes adds information about individual exposures, reducing the impact of photometric outliers. In addition to opening up the route for higher redshift precision with narrow bands, these machine learning techniques can also be valuable for broad-band surveys.
Abstract
The Physics of the Accelerating Universe Survey (PAUS) is an innovative photometric survey with 40 narrow-bands at the William Herschel Telescope (WHT). The narrow-bands are spaced at 100 Å ...intervals covering the range 4500–8500 Å and, in combination with standard broad-bands, enable excellent redshift precision. This paper describes the technique, galaxy templates, and additional photometric calibration used to determine early photometric redshifts from PAUS. Using bcnz2, a new photometric redshift code developed for this purpose, we characterize the photometric redshift performance using PAUS data on the COSMOS field. Comparison to secure spectra from zCOSMOS DR3 shows that PAUS achieves σ68/(1 + $z$) = 0.0037 to iAB < 22.5 for the redshift range 0 < $z$ < 1.2, when selecting the best 50 per cent of the sources based on a photometric redshift quality cut. Furthermore, a higher photo-z precision σ68/(1 + $z$) ∼ 0.001 is obtained for a bright and high-quality selection, which is driven by the identification of emission lines. We conclude that PAUS meets its design goals, opening up a hitherto uncharted regime of deep, wide, and dense galaxy survey with precise redshifts that will provide unique insights into the formation, evolution, and clustering of galaxies, as well as their intrinsic alignments.
We search Dark Energy Survey (DES) Year 3 imaging for galaxy-galaxy strong gravitational lenses using convolutional neural networks, extending previous work with new training sets and covering a ...wider range of redshifts and colors. We train two neural networks using images of simulated lenses, then use them to score postage-stamp images of 7.9 million sources from DES chosen to have plausible lens colors based on simulations. We examine 1175 of the highest-scored candidates and identify 152 probable or definite lenses. Examining an additional 20,000 images with lower scores, we identify a further 247 probable or definite candidates. After including 86 candidates discovered in earlier searches using neural networks and 26 candidates discovered through visual inspection of blue-near-red objects in the DES catalog, we present a catalog of 511 lens candidates.