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A. K. Romer

Publications and source records attributed to A. K. Romer.

At least 181 records · Page 10Linked to original sources

Cosmic Voids and Void Lensing in the Dark Energy Survey Science Verification Data

Galaxies and their dark matter halos populate a complicated filamentary network around large, nearly empty regions known as cosmic voids. Cosmic voids are usually identified in spectroscopic galaxy surveys, where 3D information about the large-scale structure of the Universe is available. Although an increasing amount of photometric data is being produced, its potential for void studies is limited since photometric redshifts induce line-of-sight position errors of $\sim50$ Mpc/$h$ or more that can render many voids undetectable. In this paper we present a new void finder designed for photometric surveys, validate it using simulations, and apply it to the high-quality photo-$z$ redMaGiC galaxy sample of the Dark Energy Survey Science Verification (DES-SV) data. The algorithm works by projecting galaxies into 2D slices and finding voids in the smoothed 2D galaxy density field of the slice. Fixing the line-of-sight size of the slices to be at least twice the photo-$z$ scatter, the number of voids found in these projected slices of simulated spectroscopic and photometric galaxy catalogs is within 20% for all transverse void sizes, and indistinguishable for the largest voids of radius $\sim 70$ Mpc/$h$ and larger. The positions, radii, and projected galaxy profiles of photometric voids also accurately match the spectroscopic void sample. Applying the algorithm to the DES-SV data in the redshift range $0.2<z<0.8$, we identify 87 voids with comoving radii spanning the range 18-120 Mpc/$h$, and carry out a stacked weak lensing measurement. With a significance of $4.4σ$, the lensing measurement confirms the voids are truly underdense in the matter field and hence not a product of Poisson noise, tracer density effects or systematics in the data. It also demonstrates, for the first time in real data, the viability of void lensing studies in photometric surveys.

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Nearest Neighbor: The Low-Mass Milky Way Satellite Tucana III

We present Magellan/IMACS spectroscopy of the recently discovered Milky Way satellite Tucana III (Tuc III). We identify 26 member stars in Tuc III, from which we measure a mean radial velocity of v_hel = -102.3 +/- 0.4 (stat.) +/- 2.0 (sys.) km/s, a velocity dispersion of 0.1^+0.7_-0.1 km/s, and a mean metallicity of [Fe/H] = -2.42^+0.07_-0.08. The upper limit on the velocity dispersion is sigma < 1.5 km/s at 95.5% confidence, and the corresponding upper limit on the mass within the half-light radius of Tuc III is 9.0 x 10^4 Msun. We cannot rule out mass-to-light ratios as large as 240 Msun/Lsun for Tuc III, but much lower mass-to-light ratios that would leave the system baryon-dominated are also allowed. We measure an upper limit on the metallicity spread of the stars in Tuc III of 0.19 dex at 95.5% confidence. Tuc III has a smaller metallicity dispersion and likely a smaller velocity dispersion than any known dwarf galaxy, but a larger size and lower surface brightness than any known globular cluster. Its metallicity is also much lower than those of the clusters with similar luminosity. We therefore tentatively suggest that Tuc III is the tidally-stripped remnant of a dark matter-dominated dwarf galaxy, but additional precise velocity and metallicity measurements will be necessary for a definitive classification. If Tuc III is indeed a dwarf galaxy, it is one of the closest external galaxies to the Sun. Because of its proximity, the most luminous stars in Tuc III are quite bright, including one star at V=15.7 that is the brightest known member star of an ultra-faint satellite.

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A DECam Search for an Optical Counterpart to the LIGO Gravitational Wave Event GW151226

We report the results of a Dark Energy Camera (DECam) optical follow-up of the gravitational wave (GW) event GW151226, discovered by the Advanced LIGO detectors. Our observations cover 28.8 deg$^2$ of the localization region in the $i$ and $z$ bands (containing 3% of the BAYESTAR localization probability), starting 10 hours after the event was announced and spanning four epochs at $2-24$ days after the GW detection. We achieve $5σ$ point-source limiting magnitudes of $i\approx21.7$ and $z\approx21.5$, with a scatter of $0.4$ mag, in our difference images. Given the two day delay, we search this area for a rapidly declining optical counterpart with $\gtrsim 3σ$ significance steady decline between the first and final observations. We recover four sources that pass our selection criteria, of which three are cataloged AGN. The fourth source is offset by $5.8$ arcsec from the center of a galaxy at a distance of 187 Mpc, exhibits a rapid decline by $0.5$ mag over $4$ days, and has a red color of $i-z\approx 0.3$ mag. These properties roughly match the expectations for a kilonova. However, this source was detected several times, starting $94$ days prior to GW151226, in the Pan-STARRS Survey for Transients (dubbed as PS15cdi) and is therefore unrelated to the GW event. Given its long-term behavior, PS15cdi is likely a Type IIP supernova that transitioned out of its plateau phase during our observations, mimicking a kilonova-like behavior. We comment on the implications of this detection for contamination in future optical follow-up observations.

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DESAlert: Enabling Real-Time Transient Follow-Up with Dark Energy Survey Data

The Dark Energy Survey (DES) is currently undertaking an observational program imaging $1/4$ of the southern hemisphere sky with unprecedented photometric accuracy. In the process of observing millions of faint stars and galaxies to constrain the parameters of the dark energy equation of state, the DES will obtain pre-discovery images of the regions surrounding an estimated 100 gamma-ray bursts (GRBs) over five years. Once GRBs are detected by, e.g., the Swift satellite, the DES data will be extremely useful for follow-up observations by the transient astronomy community. We describe a recently-commissioned suite of software that listens continuously for automated notices of GRB activity, collates useful information from archival DES data, and disseminates relevant data products back to the community in near-real-time. Of particular importance are the opportunities that non-public DES data provide for relative photometry of the optical counterparts of GRBs, as well as for identifying key characteristics (e.g., photometric redshifts) of potential GRB host galaxies. We provide the functional details of the DESAlert software as it presently operates, as well as the data products that it produces, and we show sample results from the application of DESAlert to several previously-detected GRBs.

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Inference from the small scales of cosmic shear with current and future Dark Energy Survey data

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 AGN 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 nonlinear scales, `lensing bias', and shape measurement selection effects. For the latter two, we make use of novel image simulations. While future cosmic shear datasets 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.

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Cosmic Shear Measurements with DES Science Verification Data

We present measurements of weak gravitational lensing cosmic shear two-point statistics using Dark Energy Survey Science Verification data. We demonstrate that our results are robust to the choice of shear measurement pipeline, either ngmix or im3shape, and robust to the choice of two-point statistic, including both real and Fourier-space statistics. Our results pass a suite of null tests including tests for B-mode contamination and direct tests for any dependence of the two-point functions on a set of 16 observing conditions and galaxy properties, such as seeing, airmass, galaxy color, galaxy magnitude, etc. We furthermore use a large suite of simulations to compute the covariance matrix of the cosmic shear measurements and assign statistical significance to our null tests. We find that our covariance matrix is consistent with the halo model prediction, indicating that it has the appropriate level of halo sample variance. We compare the same jackknife procedure applied to the data and the simulations in order to search for additional sources of noise not captured by the simulations. We find no statistically significant extra sources of noise in the data. The overall detection significance with tomography for our highest source density catalog is 9.7sigma. Cosmological constraints from the measurements in this work are presented in a companion paper (DES et al. 2015).

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Detection of the kinematic Sunyaev-Zel'dovich effect with DES Year 1 and SPT

We detect the kinematic Sunyaev-Zel'dovich (kSZ) effect with a statistical significance of $4.2 σ$ by combining a cluster catalogue derived from the first year data of the Dark Energy Survey (DES) with CMB temperature maps from the South Pole Telescope Sunyaev-Zel'dovich (SPT-SZ) Survey. This measurement is performed with a differential statistic that isolates the pairwise kSZ signal, providing the first detection of the large-scale, pairwise motion of clusters using redshifts derived from photometric data. By fitting the pairwise kSZ signal to a theoretical template we measure the average central optical depth of the cluster sample, $\barτ_e = (3.75 \pm 0.89)\cdot 10^{-3}$. We compare the extracted signal to realistic simulations and find good agreement with respect to the signal-to-noise, the constraint on $\barτ_e$, and the corresponding gas fraction. High-precision measurements of the pairwise kSZ signal with future data will be able to place constraints on the baryonic physics of galaxy clusters, and could be used to probe gravity on scales $ \gtrsim 100$ Mpc.

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Joint Measurement of Lensing-Galaxy Correlations Using SPT and DES SV Data

We measure the correlation of galaxy lensing and cosmic microwave background lensing with a set of galaxies expected to trace the matter density field. The measurements are performed using pre-survey Dark Energy Survey (DES) Science Verification optical imaging data and millimeter-wave data from the 2500 square degree South Pole Telescope Sunyaev-Zel'dovich (SPT-SZ) survey. The two lensing-galaxy correlations are jointly fit to extract constraints on cosmological parameters, constraints on the redshift distribution of the lens galaxies, and constraints on the absolute shear calibration of DES galaxy lensing measurements. We show that an attractive feature of these fits is that they are fairly insensitive to the clustering bias of the galaxies used as matter tracers. The measurement presented in this work confirms that DES and SPT data are consistent with each other and with the currently favored $Λ$CDM cosmological model. It also demonstrates that joint lensing-galaxy correlation measurement considered here contains a wealth of information that can be extracted using current and future surveys.

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SDSS-IV eBOSS emission-line galaxy pilot survey

The Sloan Digital Sky Survey IV extended Baryonic Oscillation Spectroscopic Survey (SDSS-IV/eBOSS) will observe 195,000 emission-line galaxies (ELGs) to measure the Baryonic Acoustic Oscillation standard ruler (BAO) at redshift 0.9. To test different ELG selection algorithms, 9,000 spectra were observed with the SDSS spectrograph as a pilot survey based on data from several imaging surveys. First, using visual inspection and redshift quality flags, we show that the automated spectroscopic redshifts assigned by the pipeline meet the quality requirements for a reliable BAO measurement. We also show the correlations between sky emission, signal-to-noise ratio in the emission lines, and redshift error. Then we provide a detailed description of each target selection algorithm we tested and compare them with the requirements of the eBOSS experiment. As a result, we provide reliable redshift distributions for the different target selection schemes we tested. Finally, we determine an target selection algorithms that is best suited to be applied on DECam photometry because they fulfill the eBOSS survey efficiency requirements.

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Optical-SZE Scaling Relations for DES Optically Selected Clusters within the SPT-SZ Survey

We study the Sunyaev-Zel'dovich effect (SZE) signature in South Pole Telescope (SPT) data for an ensemble of 719 optically identified galaxy clusters selected from 124.6 deg$^2$ of the Dark Energy Survey (DES) science verification data, detecting a stacked SZE signal down to richness $λ\sim20$. The SZE signature is measured using matched-filtered maps of the 2500 deg$^2$ SPT-SZ survey at the positions of the DES clusters, and the degeneracy between SZE observable and matched-filter size is broken by adopting as priors SZE and optical mass-observable relations that are either calibrated using SPT selected clusters or through the Arnaud et al. (2010, A10) X-ray analysis. We measure the SPT signal to noise $ζ$-$λ$, relation and two integrated Compton-$y$ $Y_\textrm{500}$-$λ$ relations for the DES-selected clusters and compare these to model expectations accounting for the SZE-optical center offset distribution. For clusters with $λ> 80$, the two SPT calibrated scaling relations are consistent with the measurements, while for the A10-calibrated relation the measured SZE signal is smaller by a factor of $0.61 \pm 0.12$ compared to the prediction. For clusters at $20 < λ< 80$, the measured SZE signal is smaller by a factor of $\sim$0.20-0.80 (between 2.3 and 10~$σ$ significance) compared to the prediction, with the SPT calibrated scaling relations and larger $λ$ clusters showing generally better agreement. We quantify the required corrections to achieve consistency, showing that there is a richness dependent bias that can be explained by some combination of contamination of the observables and biases in the estimated masses. We discuss possible physical effects, as contamination from line-of-sight projections or from point sources, larger offsets in the SZE-optical centering or larger scatter in the $λ$-mass relation at lower richnesses.

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The redMaPPer Galaxy Cluster Catalog From DES Science Verification Data

We describe updates to the \redmapper{} algorithm, a photometric red-sequence cluster finder specifically designed for large photometric surveys. The updated algorithm is applied to $150\,\mathrm{deg}^2$ of Science Verification (SV) data from the Dark Energy Survey (DES), and to the Sloan Digital Sky Survey (SDSS) DR8 photometric data set. The DES SV catalog is locally volume limited, and contains 786 clusters with richness $λ>20$ (roughly equivalent to $M_{\rm{500c}}\gtrsim10^{14}\,h_{70}^{-1}\,M_{\odot}$) and $0.2<z<0.9$. The DR8 catalog consists of 26311 clusters with $0.08<z<0.6$, with a sharply increasing richness threshold as a function of redshift for $z\gtrsim 0.35$. The photometric redshift performance of both catalogs is shown to be excellent, with photometric redshift uncertainties controlled at the $σ_z/(1+z)\sim 0.01$ level for $z\lesssim0.7$, rising to $\sim0.02$ at $z\sim0.9$ in DES SV. We make use of \emph{Chandra} and \emph{XMM} X-ray and South Pole Telescope Sunyaev-Zeldovich data to show that the centering performance and mass--richness scatter are consistent with expectations based on prior runs of \redmapper{} on SDSS data. We also show how the \redmapper{} \photoz{} and richness estimates are relatively insensitive to imperfect star/galaxy separation and small-scale star masks.

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Testing the lognormality of the galaxy and weak lensing convergence distributions from Dark Energy Survey maps

It is well known that the probability distribution function (PDF) of galaxy density contrast is approximately lognormal; whether the PDF of mass fluctuations derived from weak lensing convergence (kappa_WL) is lognormal is less well established. We derive PDFs of the galaxy and projected matter density distributions via the Counts in Cells (CiC) method. We use maps of galaxies and weak lensing convergence produced from the Dark Energy Survey (DES) Science Verification data over 139 deg^2. We test whether the underlying density contrast is well described by a lognormal distribution for the galaxies, the convergence and their joint PDF. We confirm that the galaxy density contrast distribution is well modeled by a lognormal PDF convolved with Poisson noise at angular scales from 10-40 arcmin (corresponding to physical scales of 3-10 Mpc). We note that as kappa_WL is a weighted sum of the mass fluctuations along the line of sight, its PDF is expected to be only approximately lognormal. We find that the kappa_WL distribution is well modeled by a lognormal PDF convolved with Gaussian shape noise at scales between 10 and 20 arcmin, with a best-fit chi^2/DOF of 1.11 compared to 1.84 for a Gaussian model, corresponding to p-values 0.35 and 0.07 respectively, at a scale of 10 arcmin. Above 20 arcmin a simple Gaussian model is sufficient. The joint PDF is also reasonably fitted by a bivariate lognormal. As a consistency check we compare the variances derived from the lognormal modelling with those directly measured via CiC. Our methods are validated against maps from the MICE Grand Challenge N-body simulation.

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Crowdsourcing quality control for Dark Energy Survey images

We have developed a crowdsourcing web application for image quality control employed by the Dark Energy Survey. Dubbed the "DES exposure checker", it renders science-grade images directly to a web browser and allows users to mark problematic features from a set of predefined classes. Users can also generate custom labels and thus help identify previously unknown problem classes. User reports are fed back to hardware and software experts to help mitigate and eliminate recognized issues. We report on the implementation of the application and our experience with its over 100 users, the majority of which are professional or prospective astronomers but not data management experts. We discuss aspects of user training and engagement, and demonstrate how problem reports have been pivotal to rapidly correct artifacts which would likely have been too subtle or infrequent to be recognized otherwise. We conclude with a number of important lessons learned, suggest possible improvements, and recommend this collective exploratory approach for future astronomical surveys or other extensive data sets with a sufficiently large user base. We also release open-source code of the web application and host an online demo version at http://des-exp-checker.pmelchior.net

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Galaxy bias from the Dark Energy Survey Science Verification data: combining galaxy density maps and weak lensing maps

We measure the redshift evolution of galaxy bias for a magnitude-limited galaxy sample by combining the galaxy density maps and weak lensing shear maps for a $\sim$116 deg$^{2}$ area of the Dark Energy Survey (DES) Science Verification data. This method was first developed in Amara et al. (2012) and later re-examined in a companion paper (Pujol et al. 2016) with rigorous simulation tests and analytical treatment of tomographic measurements. In this work we apply this method to the DES SV data and measure the galaxy bias for a i$<$22.5 galaxy sample. We find the galaxy bias and 1$σ$ error bars in 4 photometric redshift bins to be 1.12$\pm$0.19 (z=0.2-0.4), 0.97$\pm$0.15 (z=0.4-0.6), 1.38$\pm$0.39 (z=0.6-0.8)), and 1.45$\pm$0.56 (z=0.8-1.0). These measurements are consistent at the 2$σ$ level with measurements on the same dataset using galaxy clustering and cross-correlation of galaxies with CMB lensing, with most of the redshift bins consistent within the 1σ error bars. In addition, our method provides the only $σ_8$-independent constraint among the three. We forward-model the main observational effects using mock galaxy catalogs by including shape noise, photo-z errors and masking effects. We show that our bias measurement from the data is consistent with that expected from simulations. With the forthcoming full DES data set, we expect this method to provide additional constraints on the galaxy bias measurement from more traditional methods. Furthermore, in the process of our measurement, we build up a 3D mass map that allows further exploration of the dark matter distribution and its relation to galaxy evolution.

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The DES Science Verification Weak Lensing Shear Catalogues

We present weak lensing shear catalogues for 139 square degrees of data taken during the Science Verification (SV) time for the new Dark Energy Camera (DECam) being used for the Dark Energy Survey (DES). We describe our object selection, point spread function estimation and shear measurement procedures using two independent shear pipelines, IM3SHAPE and NGMIX, which produce catalogues of 2.12 million and 3.44 million galaxies respectively. We detail a set of null tests for the shear measurements and find that they pass the requirements for systematic errors at the level necessary for weak lensing science applications using the SV data. We also discuss some of the planned algorithmic improvements that will be necessary to produce sufficiently accurate shear catalogues for the full 5-year DES, which is expected to cover 5000 square degrees.

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Galaxy Populations in Massive Galaxy Clusters to z=1.1: Color Distribution, Concentration, Halo Occupation Number and Red Sequence Fraction

We study the galaxy populations in 74 Sunyaev Zeldovich Effect (SZE) selected clusters from the South Pole Telescope (SPT) survey that have been imaged in the science verification phase of the Dark Energy Survey (DES). The sample extends up to $z\sim 1.1$ with $4 \times 10^{14} M_{\odot}\le M_{200}\le 3\times 10^{15} M_{\odot}$. Using the band containing the 4000~Å break and its redward neighbor, we study the color-magnitude distributions of cluster galaxies to $\sim m_*+2$, finding: (1) the intrinsic rest frame $g-r$ color width of the red sequence (RS) population is $\sim$0.03 out to $z\sim0.85$ with a preference for an increase to $\sim0.07$ at $z=1$ and (2) the prominence of the RS declines beyond $z\sim0.6$. The spatial distribution of cluster galaxies is well described by the NFW profile out to $4R_{200}$ with a concentration of $c_{\mathrm{g}} = 3.59^{+0.20}_{-0.18}$, $5.37^{+0.27}_{-0.24}$ and $1.38^{+0.21}_{-0.19}$ for the full, the RS and the blue non-RS populations, respectively, but with $\sim40$\% to 55\% cluster to cluster variation and no statistically significant redshift or mass trends. The number of galaxies within the virial region $N_{200}$ exhibits a mass trend indicating that the number of galaxies per unit total mass is lower in the most massive clusters, and shows no significant redshift trend. The red sequence (RS) fraction within $R_{200}$ is $(68\pm3)$\% at $z=0.46$, varies from $\sim$55\% at $z=1$ to $\sim$80\% at $z=0.1$, and exhibits intrinsic variation among clusters of $\sim14$\%. We discuss a model that suggests the observed redshift trend in RS fraction favors a transformation timescale for infalling field galaxies to become RS galaxies of 2 to 3~Gyr.

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Cosmology constraints from shear peak statistics in Dark Energy Survey Science Verification data

Shear peak statistics has gained a lot of attention recently as a practical alternative to the two point statistics for constraining cosmological parameters. We perform a shear peak statistics analysis of the Dark Energy Survey (DES) Science Verification (SV) data, using weak gravitational lensing measurements from a 139 deg$^2$ field. We measure the abundance of peaks identified in aperture mass maps, as a function of their signal-to-noise ratio, in the signal-to-noise range $0<\mathcal S / \mathcal N<4$. To predict the peak counts as a function of cosmological parameters we use a suite of $N$-body simulations spanning 158 models with varying $Ω_{\rm m}$ and $σ_8$, fixing $w = -1$, $Ω_{\rm b} = 0.04$, $h = 0.7$ and $n_s=1$, to which we have applied the DES SV mask and redshift distribution. In our fiducial analysis we measure $σ_{8}(Ω_{\rm m}/0.3)^{0.6}=0.77 \pm 0.07$, after marginalising over the shear multiplicative bias and the error on the mean redshift of the galaxy sample. We introduce models of intrinsic alignments, blending, and source contamination by cluster members. These models indicate that peaks with $\mathcal S / \mathcal N>4$ would require significant corrections, which is why we do not include them in our analysis. We compare our results to the cosmological constraints from the two point analysis on the SV field and find them to be in good agreement in both the central value and its uncertainty. We discuss prospects for future peak statistics analysis with upcoming DES data.

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Assessment of Systematic Chromatic Errors that Impact Sub-1% Photometric Precision in Large-Area Sky Surveys

Meeting the science goals for many current and future ground-based optical large-area sky surveys requires that the calibrated broadband photometry is stable in time and uniform over the sky to 1% precision or better. Past surveys have achieved photometric precision of 1-2% by calibrating the survey's stellar photometry with repeated measurements of a large number of stars observed in multiple epochs. The calibration techniques employed by these surveys only consider the relative frame-by-frame photometric zeropoint offset and the focal plane position-dependent illumination corrections, which are independent of the source color. However, variations in the wavelength dependence of the atmospheric transmission and the instrumental throughput induce source color-dependent systematic errors. These systematic errors must also be considered to achieve the most precise photometric measurements. In this paper, we examine such systematic chromatic errors using photometry from the Dark Energy Survey (DES) as an example. We define a natural magnitude system for DES and calculate the systematic errors on stellar magnitudes, when the atmospheric transmission and instrumental throughput deviate from the natural system. We conclude that the systematic chromatic errors caused by the change of airmass in each exposure, the change of the precipitable water vapor and aerosol in the atmosphere over time, and the non-uniformity of instrumental throughput over the focal plane, can be up to 2% in some bandpasses. We compare the calculated systematic chromatic errors with the observed DES data. For the test sample data, we correct these errors using measurements of the atmospheric transmission and instrumental throughput. The residual after correction is less than 0.3%. We also find that the errors for non-stellar objects are redshift-dependent and can be larger than those for stars at certain redshifts.

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