# Publicações

### Submetidos 43

2018

38
1. Dark Energy Survey Year 1 Results: Validation of Weak Lensing Cluster Member Contamination Estimates From P(z) Decomposition. Varga, T.N. et al. 2018, MNRAS. arXiv
2. Superluminous Supernovae from the Dark Energy Survey. Angus, C.R. et al. 2018, MNRAS. arXiv
3. Dark Energy Survey Year 1 results: Detection of Intra-cluster Light at Redshift \$\\sim\$ 0.25. Zhang, Y. 2018, . arXiv
4. A Search for Optical Emission from Binary-Black-Hole Merger GW170814 with the Dark Energy Camera. Doctor, Z. et al. 2018, . arXiv
5. Chemical Abundance Analysis of Tucana III, the Second \$r\$-process Enhanced Ultra-Faint Dwarf Galaxy. Marshall, J. et al. 2018, ApJ. arXiv
6. Astrometry and Occultation Predictions to Trans-Neptunian and Centaur Objects Observed Within the Dark Energy Survey. Banda-Huarca, M. et al. 2018, AJ. arXiv
7. First Cosmology Results Using Type Ia Supernovae From the Dark Energy Survey: Survey Overview and Supernova Spectroscopy. D´Andrea, C.B. et al. 2018, AJ. arXiv
8. More Out of Less: an Excess Integrated Sachs-Wolfe Signal from Supervoids Mapped out by the Dark Energy Survey. Kovács, A. et al. 2018, MNRAS. arXiv
9. Dark Energy Survey Year 1 Results: Constraints on Intrinsic Alignments and their Colour Dependence from Galaxy Clustering and Weak Lensing. Samuroff, S. et al. 2018, MNRAS. arXiv
10. Measurement of the Splashback Feature Around SZ-selected Galaxy Clusters with DES, SPT and ACT. Shin, T. et al. 2018, MNRAS. arXiv
11. Finding High-redshift Strong Lenses in DES Using Convolutional Neural Networks. Jacobs, C. et al. 2018, MNRAS. arXiv
12. Quasar Accretion Disk Sizes from Continuum Reverberation Mapping in the DES Standard Star Fields. Yu, Z. et al. 2018, . arXiv
13. Steve: A hierarchical Bayesian model for Supernova Cosmology. Hinton, S.R. et al. 2018, . arXiv
14. First Cosmology Results Using Type Ia Supernovae from the Dark Energy Survey: Effects of Chromatic Corrections to Supernova Photometry on Measurements of Cosmological Parameters. Lasker, J. et al. 2018, MNRAS. arXiv
15. First Cosmology Results using Type Ia Supernova from the Dark Energy Survey: Simulations to Correct Supernova Distance Biases. Kessler, R. et al. 2018, . arXiv
16. First Cosmology Results Using Type Ia Supernovae From the Dark Energy Survey: Photometric Pipeline and Light Curve Data Release. Brout, D. et al. 2018, ApJ. arXiv
17. First Cosmology Results Using Type Ia Supernovae From the Dark Energy Survey: Analysis, Systematic Uncertainties, and Validation. Brout, D. et al. 2018, ApJ. arXiv
18. First Cosmological Results using Type Ia Supernovae from the Dark Energy Survey: Measurement of the Hubble Constant. Macaulay, E. et al. 2018, MNRAS. arXiv
19. Cosmological Constraints from Multiple Probes in the Dark Energy Survey. T. M. C. Abbott et al. 2018, . arXiv
20. First Cosmology Results using Type Ia Supernovae from the Dark Energy Survey: Constraints on Cosmological Parameters. Abbott, T.M.C et al. 2018, . arXiv
21. Mass Calibration of Optically Selected DES clusters using a Measurement of CMB-Cluster Lensing with SPTpol Data. Raghunathan, S. et al. 2018, ApJ. arXiv
22. Dark Energy Survey Year 1 Results: Methods for Cluster Cosmology and Application to the SDSS. Costanzi, M. et al. 2018, MNRAS. arXiv
23. Dark Energy Survey Year 1 Results: Cross-correlation Between DES Y1 Galaxy Weak Lensing and SPT+Planck CMB Weak Lensing. Omori, Y. et al. 2018, PhRvD. arXiv
24. Dark Energy Survey Year 1 Results: Tomographic Cross-correlations Between DES Galaxies and CMB Lensing from SPT+Planck. Omori, Y. et al. 2018, PhRvD. arXiv
25. Dark Energy Survey Year 1 Results: Joint Analysis of Galaxy Clustering, Galaxy Lensing, and CMB Lensing Two-point Functions. Abbott, T.C. et al. 2018, . arXiv
26. Cosmological Lensing Ratios with DES Y1, SPT and Planck. Prat, J. et al. 2018, MNRAS. arXiv
27. The Morphology and Structure of Stellar Populations in the Fornax Dwarf Spheroidal Galaxy from Dark Energy Survey Data. Mei-Yu Wang et al. 2018, ApJ. arXiv
28. Dark Energy Survey Year 1 Results: The Effect of Intra-cluster Light on Photometric Redshifts for Weak Gravitational Lensing. Gruen, D. et al. 2018, MNRAS. arXiv
29. Measuring Linear and Non-linear Galaxy Bias Using Counts-in-Cells in the Dark Energy Survey Science Verification Data. Salvador, A.I. et al. 2018, MNRAS. arXiv
30. Dark Energy Survey Year 1 Results: Measurement of the Galaxy Angular Power Spectrum. Camacho, H. et al. 2018, MNRAS. arXiv
31. Is Every Strong Lens Model Unhappy in Its Own Way? Uniform Modelling of a Sample of 12 Quadruply+Iimaged Quasars. Shajib, A.J. et al. 2018, MNRAS. arXiv
32. The metal-rich halo component extended in z: a characterization with Gaia DR2 and APOGEE. Fernández-Alvar, E. et al. 2018, MNRAS. arXiv
33. Modeling projection effects in optically-selected cluster catalogues. Costanzi, M. et al. 2018, MNRAS. arXiv
34. On the Relative Bias of Void Tracers in the Dark Energy Survey. Pollina, G. et al. 2018, MNRAS. arXiv
35. Widespread star formation inside galactic Outflows. Gallagher, R. et al. 2018, MNRAS. arXiv
36. Dissecting Stellar Chemical Abundance Space with t-SNE. Anders, F. et al. 2018, A&A. arXiv
37. Dark Energy Survey Year 1 Results: Methodology and Projections for Joint Analysis of Galaxy Clustering, Galaxy Lensing, and CMB Lensing Two-point Functions. Baxter, E.J. et al. 2018, MNRAS. arXiv
38. Weak Lensing Analysis of SPT selected Galaxy Clusters using Dark Energy Survey Science Verification Data. Stern, C. et al. 2018, MNRAS. arXiv

2017

03
1. Galaxies in X-ray Selected Clusters and Groups in Dark Energy Survey Data II: Hierarchical Bayesian Modeling of Red-Sequence Galaxy Luminosity Function. Zhang, Y. et al. 2017, . arXiv
2. Dark Energy Survey Year 1 Results: Cross-Correlation Redshifts in the DES -- Calibration of the Weak Lensing Source Redshift Distributions. Davis, C. et al. 2017, MNRAS. arXiv
3. Dark Energy Survey Year 1 Results: Multi-Probe Methodology and Simulated Likelihood Analyses. Krause, E. et al. 2017, . arXiv

2016

02
1. The DESI Experiment Part II: Instrument Design. Aghamousa, A. et al. 2016, . arXiv
2. The DESI Experiment Part I: Science,Targeting, and Survey Design. Aghamousa, A. et al. 2016, . arXiv

### Aceitos 05

2018

05
1. The Fifteenth Data Release of the Sloan Digital Sky Surveys: First Release of MaNGA Derived Quantities, Data Visualization Tools and Stellar Library. Aguado, D.S. et al. 2018, ApJSS. arXiv
2. Dark Energy Survey Year 1 Results: Constraints on Extended Cosmological Models from Galaxy Clustering and Weak Lensing. Abbott, T.M.C. et al. 2018, PhRvD. arXiv
3. Mildly Suppressed Star Formation in Central Regions of MaNGA Seyfert Galaxies. Bing, L. et al. 2018, MNRAS. arXiv
4. Knowledge Transfer of Deep Learning for Galaxy Morphology from one Survey to Another. Domínguez Sánchez, H. et al. 2018, MNRAS. arXiv
5. Dark Energy Survey Year 1 Results: Measurement of the Baryon Acoustic Oscillation Scale in the Distribution of Galaxies to Redshift 1. Abbott,T.M.C. et al. 2018, MNRAS. arXiv

2019

04
1. Evidence for Color Dichotomy in the Primordial Neptunian Trojan Population. Lin, H.W. et al. 2019, Icarus, 321, 426.
2. Candidate Massive Galaxies at z~ 4 in the Dark Energy Survey. Guarnieri, P. et al. 2019, MNRAS, 483, 3060.
3. Dark Energy Survey Year 1 Results: Galaxy Sample for BAO Measurement. Crocce,M. et al. 2019, MNRAS, 482, 2807.
4. Dark Energy Survey Year 1 Results: Weak Lensing Mass Calibration of redMaPPer Galaxy Clusters. McClintock, T. et al. 2019, MNRAS, 482, 1352.

2018

66
1. The DESI Instrument Control System: Status and Early Testing. Honscheid, K. et al. 2018, SPIE, 10707, 1.
2. Dark energy survey operations: years 4 and 5. Diehl, H.T. et al. 2018, Proceedings of SPIE, 10704, 10704D.
3. DES Science Portal: Computing Photometric Redshifts. Gschwend, J. et al. 2018, Astronomy & Computing, 25, 58.
4. DES Science Portal: Creating Science-Ready Catalogs. Fausti Neto, A. et al. 2018, Astronomy & Computing, 24, 52.
5. COSMOGRAIL: the COSmological MOnitoring of GRAvItational Lenses XVI. Time Delays for the Quadruply Imaged Quasar DES J0408?5354 with High-cadence Photometric Monitoring. Courbin, F. et al. 2018, A&A, 609, 71.
6. Dark Energy Survey Year 1 Results: Cosmological Constraints from Cosmic Shear. Troxel, M.A. et al. 2018, PhRvD, 98, 043528.
7. Dark Energy Survey Year 1 Results: Cosmological Constraints from Galaxy XClustering and Weak Lensing. Abbott, T.M.C. et al. 2018, PhRvD, 98, 043526.
8. Dark Energy Survey Year 1 Results: Galaxy Clustering for Combined Probes. Elvin-Poole, J. et al. 2018, PhRvD, 98, 042006.
9. Dark Energy Survey Year 1 Results: Galaxy-Galaxy Lensing. Prat, J. et al. 2018, PhRvD, 98, 042005.
10. Density Split Statistics: Joint Model of Counts and Lensing in Cells. Friedrich, O. et al. 2018, PhRvD, 98, 023508.
11. Density split statistics: Cosmological constraints from counts and lensing in cells in DES Y1 and SDSS. Gruen, D. et al. 2018, PhRvD, 98, 023507.
12. The First 62 AGN Observed With SDSS-IV MaNGA - II: Resolved stellar Populations. Mallmann, N.D. 2018, MNRAS, 478, 5491.
13. Morphology of AGN Emission Line Regions in SDSS-IV MaNGA Survey. He, Z. et al. 2018, MNRAS, 478, 3614.
14. Dark Energy Survey Year 1 Results: The Impact of Galaxy Neighbours on Weak Lensing Cosmology with im3shape. Samuroff, S. et al. 2018, MNRAS, 475, 4524.
15. Star-galaxy Classification in the Dark Energy Survey Y1 Dataset. Sevilla-Noarbe, I. et al. 2018, MNRAS, 481, 5451.
16. Chemo-kinematics of the Milky Way from the SDSS-III MARVELS Survey. Grieves, N. et al. 2018, MNRAS, 481, 3244.
17. Modelling the Tucana III Stream - a Close Passage With the LMC. Erkal, D. 2018, MNRAS, 481, 3148.
18. Dark Energy Survey Year 1 Results: Calibration of redMaGiC Redshift Distributions in DES and SDSS from Cross-Correlations. Cawthon, R. et al. 2018, MNRAS, 481, 2427.
19. A Catalogue of Structural and Morphological Measurements for DES Y1. Tarsitano, F. et al. 2018, MNRAS, 481, 2018.
20. Estimating Stellar Birth Radii and the Time Evolution of the Milky Way\\\'s ISM Metallicity Gradient. Minchev, I. et al. 2018, MNRAS, 481, 1645.
21. Forecasts for Warm Dark Matter from Photometric Galaxy Surveys. Martins, J.S. et al. 2018, MNRAS, 481, 1290.
22. Dark Energy Survey Year 1 Results: Weak Lensing Shape Catalogues. Zuntz, J. et al. 2018, MNRAS, 481, 1149.
23. The STRong lensing Insights into the Dark Energy Survey (STRIDES) 2016 follow-up campaign. I. Overview and classification of candidates selected by two techniques. Treu, T. et al. 2018, MNRAS, 481, 1041.
24. The STRong Lensing Insights into the Dark Energy Survey (STRIDES) 2016 Follow-up Campaign. II. New Quasar Lenses from Double Component Fitting. Anguita, T. et al. 2018, MNRAS, 480, 5017.
25. DES Y1 Results: Validating Cosmological Parameter Estimation Using Simulated Dark Energy Surveys. MacCrann, N. et al. 2018, MNRAS, 480, 4614.
26. Dark Energy Survey Year 1 Results: A Precise H0 Measurement from DES Y1, BAO, and D/H Data. Abbott, T.M.C. et al. 2018, MNRAS, 480, 3879.
27. BAO from Angular Clustering: Optimization and Mitigation of Theoretical Systematics. Chan, K.C. et al. 2018, MNRAS, 480, 3031.
28. Survey Geometry and the Internal Consistency of Recent Cosmic Shear Measurements. Troxel, M.A. et al. 2018, MNRAS, 479, 4998.
29. DES Meets Gaia: Discovery of Strongly Lensed Quasars From a Multiplet Search. Agnello, A. et al. 2018, MNRAS, 479, 4345.
30. Improving Weak Lensing Mass Map Reconstructions using Gaussian and Sparsity Priors: Application to DES SV. Jeffrey, N. et al. 2018, MNRAS, 479, 2871.
31. Dark Energy Survey Year 1 Results: Galaxy Mock Catalogues for BAO. Avila, S. et al. 2018, MNRAS, 479, 94.
32. Baryon Content in a Sample of 91 Galaxy Clusters Selected by the South Pole Telescope at 0.2 < z < 1.25. Chiu, I. et al. 2018, MNRAS, 478, 3072.
33. Deep SOAR Follow-up Photometry of two Milky Way outer-halo Companions Discovered with Dark Energy Survey. Luque, E. et al. 2018, MNRAS, 478, 2006.
34. Dark Energy Survey Year 1 Results: Redshift Distributions of the Weak Lensing Source Galaxies. Hoyle, B. et al. 2018, MNRAS, 478, 592.
35. Cross-Correlation Redshift Calibration Without Spectroscopic Calibration Samples in DES Science Verification Data. Davis, C. et al. 2018, MNRAS, 477, 2196.
36. Dark Energy Survey Year 1 Results: Cross-Correlation Redshifts - Methods and Systematics Characterization. Gatti, M. et al. 2018, MNRAS, 477, 1664.
37. A Measurement of CMB Cluster Lensing with SPT and DES Year 1 Data. Baxter, E.J. et al. 2018, MNRAS, 476, 2674.
38. StarHorse: A Bayesian Tool for Determining Stellar Masses, Ages, Distances, and Extinctions for Field Stars. Queiroz, A.B. et al. 2018, MNRAS, 476, 2556.
39. SDSS-IV MaNGA: Evidence of the Importance of AGN Feedback in Low-mass Galaxies. Penny, S.J. et al. 2018, MNRAS, 476, 979.
40. Magnification in the Dark Energy Survey Science Verification Data. Garcia-Fernandez, M. et al. 2018, MNRAS, 476, 1071.
41. Do Satellite Galaxies Trace Matter in Galaxy Clusters ? Wang, C. et al 2018, MNRAS, 475, 4020.
42. UV-Luminous, Star-Forming Hosts of z~2 Reddened Quasars in the Dark Energy Survey. Wethers, C.F. et al. 2018, MNRAS, 475, 3682.
43. Dark Energy Survey Year 1 Results: Curved-Sky Weak Lensing Mass Map. Chang, C. et al. 2018, MNRAS, 475, 3165.
44. SDSS-IV MaNGA: Identification of Active Galactic Nuclei in Optical Integral Field Unit Surveys. Wylezalek, D. et al. 2018, MNRAS, 474, 1499.
45. Galaxy Bias From Galaxy-galaxy Lensing in the DES Science Verification Data. Prat, J. et al. 2018, MNRAS, 473, 1667.
46. Cartography of Triangulum-Andromeda Using SDSS Stars. Perottoni, H.D. et al. 2018, MNRAS, 473, 1461.
47. A Multi-component Matched Filter Cluster Confirmation Tool for eROSITA: Initial Application to the RASS and DES-SV Datasets. Klein, M. et al. 2018, MNRAS, 474, 3324.
48. SSDSS IV MaNGA - Properties of AGN Host Galaxies. Sanchez, S.F. et al. 2018, RMxAA, 54, 217.
49. How Many Kilonovae Can Be Found in Past, Present, and Future Survey Datasets? Scolnic, D. et al. 2018, ApJL, 852, L3.
50. The Dark Energy Survey Data Release 1. Abbott, T.M.C. et al. 2018, ApJSS, 239, 18.
51. Dark Energy Survey Year 1 Results: Photometric Data Set for Cosmology. Drlica-Wagner, A. et al. 2018, ApJS, 235, 33.
52. The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Sky Survey and from the second phase of the Apache Point Observatory Galactic Abolfathi, B. et al. 2018, ApJS, 235, 42.
53. The First Tidally Disrupted Ultra-Faint Dwarf Galaxy? - Spectroscopic Analysis of the Tucana III Stream. Li, T. et al. 2018, ApJ, 866, 22.
54. The Splashback Feature around DES Galaxy Clusters: Galaxy Density and Weak Lensing Profiles. Chang, C. et al. 2018, ApJ, 864, 83.
55. Stellar Streams Discovered in the Dark Energy Survey. Shipp, N. et al. 2018, ApJ, 862, 114.
56. Quasar Accretion Disk Sizes With Continuum Reverberation Mapping From the Dark Energy Survey. Mudd, D. et al. 2018, ApJ, 862,123.
57. SDSS-IV MaNGA: Star Formation Cessation in Low-redshift Galaxies I. Dependence on Stellar Mass and Structural Properties. Wang, E., et al. 2018, ApJ, 856, 137.
58. Extreme variability quasars from the Sloan Digital Sky Survey and the Dark Energy Survey. Rumbaugh, N. et al. 2018, ApJ, 854, 160.
59. Studying the Ultraviolet Spectrum of the First Spectroscopically Confirmed Supernova at redshift two. Smith, M. et al. 2018, ApJ, 854, 37.
60. Chemical Abundance Analysis of Three alpha-Poor, Metal-Poor Stars in the Ultra-Faint Dwarf Galaxy Horologium I. Nagasawa, D.Q. et al. 2018, ApJ, 852, 99.
61. The Bulge Metallicity Distribution from the APOGEE Survey. Garcia Perez, A.E. et al. 2018, ApJ, 852, 91.
62. The Clustering of Luminous Red Galaxies at z ~ 0.7 from eBOSS Data. Zhai, Z. et al. 2018, ApJ, 848, 76.
63. Dynamical Analysis of Three Distant Trans-Neptunian Objects with Similar Orbits. Khain, T. et al. 2018, AJ, 156, 273.
64. Discovery and Dynamical Analysis of an Extreme Trans-Neptunian Object with a High Orbital Inclination. Becker, J.C. et al. 2018, AJ, 156, 81.
65. Forward Global Photometric Calibration of the Dark Energy Survey. Burke, D. et al. 2018, AJ, 155, 41.
66. The Dark Energy Survey Image Processing Pipeline. Morganson, E. et al. 2018, PASP, 130, 4501.

2017

60
1. A Gravitational-wave Standard Siren Measurement of the Hubble Constant. Abbott, B.P. et al. 2017, Nature, 551, 85.
2. The Size, Shape, Density and Ring of the Dwarf Planet Haumea From a Stellar Occultation. Ortiz, J.L. et al. 2017, Nature, 550, 219.
3. Results from a triple chord stellar occultation and far-infrared photometry of the trans-Neptunian object (229762) 2007 UK126. Schindler, K. et al. 2017, A&A, 600, 12.
4. The First 62 AGN Observed with SDSS-IV MaNGA - I: their Characterization and Definition of a Control Sample. Rembold, S. et al. 2017, MNRAS, 472, 4382.
5. Models of the Strongly Lensed Quasar DES J0408-5354. Agnello, A. et al. 2017, MNRAS, 472, 4038.
6. Galaxy Populations in Massive Galaxy Clusters to z=1.1: Color Distribution, Concentration, Halo Occupation Number and Red Sequence Fraction. Hennig, C. et al. 2017, MNRAS, 467, 4015.
7. SDSS-IV MaNGA: Spatially Resolved Star Formation Histories in Galaxies as a Function of Galaxy Mass and Type. Goddard, D. et al. 2017, MNRAS, 466, 4731.
8. The Evolution of Active Galactic Nuclei in Clusters of Galaxies from the Dark Energy Survey. Bufanda, E. et al. 2017, MNRAS, 465, 2531.
9. DES15E2mlf: a Spectroscopically Confirmed Superluminous Supernova that Exploded 3.5 Gyr After the Big Bang. Pan, Y.-C et al. 2017, MNRAS, 470, 4241.
10. Photometric Redshifts and Clustering of Emission Line Galaxies Selected Jointly by DES and eBOSS. Jouvel, S. et al. 2017, MNRAS, 469, 2771.
11. Testing the Lognormality of the Galaxy and Weak Lensing Convergence Distributions from Dark Energy Survey Maps. Clerkin, L. et al. 2017, MNRAS, 466, 1444.
12. Eight New Luminous z > 6 Quasars Selected via SED Model Fitting of VISTA, WISE and Dark Energy Survey Year 1 Observations. Reed, S.L. et al. 2017, MNRAS, 468, 4702.
13. Discovery of a z=0.65 Post-Starburst BAL Quasar in the DES Supernova Fields. Mudd, D. et al. 2017, MNRAS, 468, 3682.
14. Optical-SZE Scaling Relations for DES Optically Selected Clusters within the SPT-SZ Survey. Saro, A. et al. 2017, MNRAS, 468, 3347.
15. A Stellar Over-density Associated with the Small Magellanic Cloud. Pieres, A. et al. 2017, MNRAS, 468, 1349.
16. The Dark Energy Survey View of the Sagittarius Stream: Discovery of Two Faint Stellar System Candidates. Luque, E. et al. 2017, MNRAS, 468, 97.
17. Exploring the Brown Dwarf Desert: New Substellar Companions from the SDSS-III MARVELS Survey. Grieves, N. 2017, MNRAS, 467, 4262.
18. Zooming Into Local Active Galactic Nuclei: The power of combining SDSS-IV MaNGA With Higher Resolution Integral Field Unit Observations. Wylezalek, D. et al. 2017, MNRAS, 467, 2612.
19. OzDES Multifibre Spectroscopy for the Dark Energy Survey: Three Year Results and First Data Release. Childress, M.J. et al. 2017, MNRAS, 472, 273.
20. Weak-lensing Mass Calibration of redMaPPer Galaxy Clusters in Dark Energy Survey Science Verification Data. Melchior, P. et al. 2017, MNRAS, 469, 4899.
21. Cardinal kinematics: I. Rotation Fields of the APOGEE Survey. Kordopatis, G. et al. 2017, MNRAS, 467, 469.
22. SDSS-IV MaNGA: The Impact of Diffuse Ionized Gas on Emission-line Ratios, Interpretation of Diagnostic Diagrams, and Gas Metallicity Measurements. Zhang, K. et al. 2017, MNRAS, 466, 3217.
23. Environmental Dependence of the Galaxy Stellar Mass Function in the Dark Energy Survey Science Verification Data. Etherington, J. et al. 2017, MNRAS, 466, 228.
24. SDSS-IV MaNGA: Environmental Dependence of Stellar Age and Metallicity Gradients in Nearby Galaxies. Zheng, Z. et al. 2017, MNRAS, 465, 4572.
25. Galaxy-Galaxy Lensing in the DES Science Verification Data. Clampitt, J. et al. 2017, MNRAS, 465, 4204.
26. Imprint of DES Super-structures on the Cosmic Microwave Background. Kovács, A. et al. 2017, MNRAS, 465, 4166.
27. VDES J2325-5229 a z=2.7 Gravitationally Lensed Quasar Discovered Using Morphology Independent Supervised Machine Learning. Ostrovski, F. et al. 2017, MNRAS, 465, 4325.
28. Inference From the Small Scales of Cosmic Shear With Current and Future Dark Energy Survey Data. MacCrann, N. et al. 2017, MNRAS, 465, 2567.
29. Red Giants Observed by CoRoT and APOGEE: The Evolution of the Milky Way\'s Radial Metallicity Gradient. Anders, F. et al. 2017, A&A, 600, 70.
30. SDSS-IV MaNGA: Deep Observations of Extra-planar, Diffuse Ionized Gas Around Late-type Galaxies From Stacked IFU Spectra. Jones, A. et al. 2017, A&A, 599, 141.
31. Galactic Archaeology with Asteroseismology and Spectroscopy: Red Giants Observed by CoRoT and APOGEE. Anders, F. et al. 2017, A&A, 597, 30.
32. Chemical trends in the Galactic Halo from APOGEE data. Fernández-Alvar, E. 2017, MNRAS, 465, 1586.
33. Cosmic Voids and Void Lensing in the Dark Energy Survey Science Verification Data. Sánchez, C. et al. 2017, MNRAS, 465,746.
34. SDSS-IV MaNGA: Stellar Population Gradients as a Function of Galaxy Environment. Goddard, D. et al. 2017, MNRAS, 465, 688.
35. Cosmology From Large Scale Galaxy Clustering and Galaxy-Galaxy Lensing With Dark Energy Survey Science Verification data. Kwan, J. et al. 2017, MNRAS, 464, 4045.
36. SDSS-IV MANGA: Spatially Resolved Star Formation Main Sequence and LI(N)ER Sequence. Hsieh, B.C et al. 2017, ApJL, 851, L24.
37. DECam and DES Perspective of the GW170817 Host, NGC 4993: Indication for Dynamically-driven Formation of Binary Neutron Star in Early Type Galaxies. Palmese, A. et al. 2017, ApJL, 849, L34.
38. Multi-messenger Observations of a Binary Neutron Star Merger. Abbott, B.P. et al. 2017, ApJL, 848, L12.
39. The Electromagnetic Counterpart of the Binary Neutron Star Merger LIGO/Virgo GW170817. I. Discovery of the Optical Counterpart Using the Dark Energy Camera. Soares-Santos, M. et al. 2017, ApJL, 848, L16.
40. The Electromagnetic Counterpart of the Binary Neutron Star Merger LIGO/Virgo GW170817. II. UV, Optical, and Near-infrared Light Curves and Comparison to Kilonova Models. Cowperthwaite, P.S. et al. 2017, ApJL, 848, L17.
41. Atypical Mg-poor Milky Way Field Stars With Globular Cluster Second-generation Like Chemical Patterns. Fernández-Trincado, J.G. et al. 2017, ApJL, 846, 2.
42. Discovery and Physical Characterization of a Large Scattered Disk Object at 92 AU. Gerdes, D. et al. 2017, ApJL, 939L, 15.
43. Discovery of the Lensed Quasar System DES J0408-5354. Lin, H. et al. 2017, ApJL, 838, L15.
44. The Thirteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the SDSS-IV Survey MApping Nearby Galaxies at Apache Point Observatory. Albareti, F.D. et al. 2017, ApJS, 233, 25.
45. The DES Bright Arcs Survey: Hundreds of Candidate Strongly Lensed Galaxy Systems from the Dark Energy Survey Science Verification and Year 1 Observations. Diehl, H.T. et al. 2017, ApJS, 232, 15.
46. Core or Cusps: The Central Dark Matter Profile of a Redshift One Strong Lensing Cluster With a Bright Central Image. Collett, T.F. et al. 2017, ApJ, 843, 148.
47. SDSS IV MaNGA - Rotation Velocity Lags in the Extraplanar Ionized Gas from MaNGA Observations of Edge-on Galaxies. Bizyaev, D. et al. 2017, MNRAS, 839, 87.
48. An R-process enhanced star in the dwarf galaxy Tucana III. Hansen, T.T. et al. 2017, ApJ, 838, 44.
49. Farthest Neighbor: The Distant Milky Way Satellite Eridanus II. Li, T.S. et al. 2017, ApJ, 838, 8.
50. A Search for Kilonovae in the Dark Energy Survey. Doctor, Z. et al. 2017, ApJ, 837, 57.
51. Nearest Neighbor: The Low-Mass Milky Way Satellite Tucana III. Simon, J.D. et al. 2017, ApJ, 838,11.
52. Searching for Dark Matter Annihilation in Recently Discovered Milky Way Satellites with Fermi-LAT. Albert, A. et al. 2017, ApJ, 834, 110.
53. Size and Shape of Chariklo from Multi-epoch Stellar Occultations. Leiva, R. et al. 2017, AJ, 154, 159.
54. The Structure of Chariklo’s Rings from Stellar Occultations. Bérad, D. et al. 2017, AJ, 154, 144.
55. The Apache Point Observatory Galactic Evolution Experiment (APOGEE). Majewski, S.R. et al. 2017, AJ, 154, 94.
56. Sloan Digital Sky Survey IV: Mapping the Milky Way, Nearby Galaxies and the Distant Universe. Blanton, M.R. et al. 2017, AJ, 154, 28.
57. Study of the Plutino Object (208996) 2003 AZ84 from Stellar Occultations: Size, Shape, and Topographic Features. Dias-Oliveira, A. et al. 2017, AJ, 154, 22.
58. A Study of Quasar Selection in the Supernova Fields of the Dark Energy Survey. Tie, S.S. et al. 2017, ApJ, 153, 107.
59. Redshift Measurement and Spectral Classification for eBOSS Galaxies with the Redmonster Software. Hutchinson, T. et al. 2017, AJ, 152, 205.
60. Astrometric Calibration and Performance of the Dark Energy Camera. Bernstein, G. M. et al. 2017, PASP, 129, 4503.

2016

52
1. DESAlert: Enabling Real-Time Transient Follow-Up with Dark Energy Survey Data. Poci, A. et al. 2016, PASA, 33, 49.
2. Crowdsourcing Quality Control for Dark Energy Survey Images. Melchior, P. et al. 2016, Astronomy & Computing, 16, 99.
3. The Growth of the Central Region by Acquisition of Counter-rotating Gas in Star-forming Galaxies. Chen, Y. et al. 2016, Nature Communications, 7:13269.
4. Red Clump Stars. Girardi, L. 2016, ARA&Ap, 54, 95.
5. The SDSS-IV eBOSS Emission-line Galaxy Pilot Survey. Comparat, J. et al. 2016, A&A, 592, A121.
6. Spectrophotometric Distances: a Bayesian Approach for Optical and NIR data. Santiago, B. X. et al. 2016, A&A, 585, 42.
7. Galactic Archaeology with CoRoT and APOGEE: Creating Mock Observations From a Chemodynamical Model. Anders, F. et al. 2016, Astron. Nachr., 337, 926.
8. Milky Way populations with TRILEGAL. Girardi, L. et al. 2016, Astron. Nachr., 337, 871.
9. Cosmology Constraints From Shear Peak Statistics in Dark Energy Survey Science Verification Data. Kacprzak, T. et al. 2016, MNRAS, 463, 3653.
10. Comparing Dark Energy Survey and HST-CLASH Observations of the Galaxy Cluster RXC J2248.7-4431: Implications for Stellar Mass Versus Dark Matter. Palmese, A. et al. 2016, MNRAS, 463, 1486.
11. SDSS-IV MaNGA: Properties of Galaxies with Kinematically Decoupled Stellar and Gaseous Components. Jin, Y. et al. 2016, MNRAS, 463, 913.
12. The XMM Cluster Survey: Evolution of the Velocity Dispersion - Temperature Relation Over Half a Hubble Time. Wilson, S. et al. 2016, MNRAS, 463, 413.
13. New Orbits of Irregular Satellites Designed for the Predictions of Stellar Occultations up to 2020, Based on Thousands of New Observations. Gomes-Júnior, A.R. et al. 2016, MNRAS, 462, 1351.
14. Detection of the Kinematic Sunyaev-Zel\'dovich Effect with DES Year 1 and SPT. Soergel, B. et al. 2016, MNRAS, 461, 3172.
15. Physical Properties of Star Clusters in the Outer LMC as Observed by the Dark Energy Survey. Pieres et al. 2016, MNRAS, 461,519.
16. The DES Science Verification Weak Lensing Shear Catalogs. Jarvis, M. et al. 2016, MNRAS, 460, 2245.
17. The Dark Energy Survey: More Than Dark Energy - An Overview. Dark Energy Survey Collaboration: Abbott, T. et al. 2016, MNRAS, 460, 1270.
18. Galaxy Bias From the DES Science Verification Data: Combining Galaxy Density Maps and Weak Lensing Maps. Chang, C. et al. 2016, MNRAS, 459, 3203.
19. Cross-correlation of Gravitational Lensing From DES Science Verification Data With SPT and Planck Lensing. Kirk, D. et al. 2016, MNRAS, 459, 21.
20. Digging Deeper Into the Southern Skies: A Compact Milky-Way Companion Discovered in First-year Dark Energy Survey Data. Luque, E. et al. 2016, MNRAS, 458, 603.
21. No Galaxy Left Behind: Accurate Measurements with the Faintest Objects in the Dark Energy Survey. Suchyta, E. et al. 2016, MNRAS, 457, 786.
22. CMB Lensing Tomography with the DES Science Verification Galaxies. Giannantonio, T. et al. 2016, MNRAS, 456, 3213.
23. The SDSS-III BOSS Quasar Lens Survey: Discovery of Thirteen Gravitationally Lensed Quasars. More, A. et al. 2016, MNRAS, 456, 1595.
24. Galaxy Clustering, Photometric Redshifts and Diagnosis of Systematics in the DES Science Verification Data. Crocce, M. et al. 2016, MNRAS, 455, 4301.
25. Weak Lensing by Galaxy Troughs in DES Science Verification Data. Gruen, D. et al. 2016, MNRAS, 455, 3367.
26. Joint Analysis of Galaxy-Galaxy Lensing and Galaxy Clustering: Methodology and Forecasts for DES. Park, Y. et al. 2016, PhRvD, 94, 063533.
27. Redshift Distributions of Galaxies in the DES Science Verification Shear Catalogue and Implications for Weak Lensing. Bonnett, C. et al. 2016, PhRvD, 94, 042005.
28. Cosmic Shear Measurements with DES Science Verification Data. Becker, M.R. et al. 2016, PhRvD, 94, 022002.
29. Cosmology from Cosmic Shear with DES Science Verification Data. Abbott, T. et al. 2016, PhRvD, D94, 022001.
30. An Ultra-Faint Galaxy Candidate Discovered in Early Data from the Magellanic Satellites Survey. Drlica-Wagner, A. et al. 2016, ApJL, 833, L5.
31. A DECam Search for an Optical Counterpart to the LIGO Gravitational Wave Event GW151226. Cowperthwaite, P. et al. 2016, ApJL, 826, L29.
32. Localization and Broadband Follow-up of the Gravitational-wave Transient GW150914. Abbott, B.P. et al. 2016, ApJL, 826, L13.
33. A Dark Energy Camera Search for Missing Supergiants in the LMC After the Advanced LIGO Gravitational Wave Event GW150914. Annis, J. et al. 2016, ApJ, 823L, 34.
34. A Dark Energy Camera Search for an Optical Counterpart to the First Advanced LIGO Gravitational Wave Event GW150914. Soares-Santos, M. et al. 2016, ApJ, 823L, 33.
35. Pluto’s Atmosphere form the 2015 June 29 Ground-based Stellar Occultation at the Time of The New Horizons Flyby. Sicardy, B. et al. 2016, ApJL, 819, L38.
36. DES14X3taz: A Type I Superluminous Supernova Showing a Luminous, Rapidly Cooling Initial Pre-Peak Bump. Smith, M. et al. 2016, ApJL, 818, 8.
37. On the Dependence of the Type Ia SNe Luminosities on the Metallicity of Their Host Galaxies. Moreno-Raya, M.E. et al. 2016, ApJL, 818, L19.
38. Discovery of a Metal-Poor Field Giant with a Globular Cluster Second- Generation Abundance Pattern. Fernandez-Trincado, J.G. et al. 2016, ApJ, 833, 132.
39. Mapping and Simulating Systematics due to Spatially-varying Observing Conditions in the Dark Energy Survey. Leistedt, B. et al. 2016, MNRAS, 226, 24.
40. Supplement: Localization and Broadband Follow-up of the Gravitational-wave Transient GW150914. Abbott, B.P. et al. 2016, ApJS, 225, 8.
41. The SDSS-IV extended Baryonic Oscillation Spectroscopic Survey: Luminous Red Galaxy Target Selection. Prakash, A. et al. 2016, ApJS, 224, 34.
42. The RedMaPPer Galaxy Cluster Catalog From DES Science Verification Data. Rykoff, E.S. et al. 2016, ApJS, 224S, 1.
43. SDSS-IV MaNGA: A Serendipitous Observation of Warm Gas Accretion. Cheung, E. et al. 2016, ApJL, 832, 182.
44. Discovery of a Stellar Overdensity in Eridanus-Phoenix in the Dark Energy Survey. Li, T.S. et al. 2016, ApJ, 817, 135.
45. Determining Ages of APOGEE Giants with Known Distances. Feuillet, D. et al. 2016, ApJ, 817, 40.
46. Galaxies in X-ray Selected Clusters and Groups in Dark Energy Survey Data: Stellar Mass Growth of Bright Central Galaxies Since z~1.2. Zhang, Y. et al. 2016, ApJ, 816, 98.
47. Host Galaxy Identification for Supernova Surveys. Gupta, R. et al. 2016, AJ, 152, 154.
48. Very Low-Mass Stellar and Substellar Companions to Solar-like Stars From MARVELS VI: A Giant Planet and a Brown Dwarf Candidate in a Close Binary System HD 87646. Ma, B. et al. 2016, AJ, 152, 112.
49. Assessment of Systematic Chromatic Errors that Impact Sub-1% Photometric Precision in Large-Area Sky Surveys. Li, T.S. et al. 2016, AJ, 151, 157.
50. The SDSS-IV extended Baryon Oscillation Spectroscopic Survey: Overview and Early Data. Dawson, K.S. et al. 2016, AJ, 151, 44.
51. Observation of Two New L4 Neptune Trojans in the Dark Energy Survey Supernova Fields. Gerdes, D.W. et al. 2016, AJ, 151, 39.
52. Joint Measurement of Lensing-Galaxy Correlations Using SPT and DES SV Data. Baxter, E.J. et al. 2016, MNRAS, 461, 4099.

2015

33
1. Evidence for a Metal-poor Population in the Inner Galactic Bulge. Schultheis, M. et al. 2015, A&A, 584, 45.
2. Young [alpha/Fe]-enhanced stars discovered by CoRoT and APOGEE: What is their origin? Chiappini, C. et al. 2015, A&A, 576, 12.
3. Baryon Acoustic Oscillations in the Ly-alpha forest of BOSS DR11 quasars. Delubac, T. et al. 2015, A&A, 574.
4. redMaGiC: Selecting Luminous Red Galaxies from the DES Science Verification Data. Rozo, E. et al. 2015, MNRAS, 461, 1431.
5. Constraints on the Richness-Mass Relation and the Optical-SZE Positional Offset Distribution for SZE-Selected Clusters. Saro, A. et al. 2015, MNRAS, 454, 2305.
6. Discovery of two gravitationally lensed quasars in the Dark Energy Survey. Agnello, A. et al. 2015, MNRAS, 454, 1260.
7. OzDES multi-fibre spectroscopy for the Dark Energy Survey: First-year operation and results. Yuan, F. et al. 2015, MNRAS, 452, 3047.
8. Young alpha-enriched Giant Stars in the Solar Neighbourhood. Martig, M. et al. 2015, MNRAS, 451, 2230.
9. Star/galaxy Separation at Faint Magnitudes: Application to a Simulated Dark Energy Survey. Soumagnac, M.T. et al. 2015, MNRAS, 450, 666.
10. A New Method for Estimating the Pattern Speed of Spiral Structure in the Milky Way. Junqueira, T.C. et al. 2015, MNRAS, 449, 2336.
11. Mass and Galaxy Distributions of Four Massive Galaxy Clusters from Dark Energy Survey Science Verification Data. Melchior, P. et al. 2015, MNRAS, 449, 2219.
12. DES13S2cmm: The First Superluminous Supernova from the Dark Energy Survey. Papadopoulos, A. et al. 2015, MNRAS, 449, 1215.
13. The LMC geometry and outer stellar populations from early DES data. Balbinot, E. et al. 2015, MNRAS, 449, 1129.
14. Combining Dark Energy Survey Science Verification Data with Near Infrared Data from the ESO VISTA Hemisphere Survey. Banerji, M. et al. 2015, MNRAS, 446, 2523.
15. Wide-Field Lensing Mass Maps from DES Science Verification Data. Vikram, V. et al. 2015, PRD, 92, 022006.
16. Cosmological implications of baryon acoustic oscillation (BAO) measurements. Aubourg, E. et al. 2015, PRD, 9213516.
17. Observation and Confirmation of Six Strong Lensing Systems in The Dark Energy Survey Science Verification Data. Nord, B. et al. 2015, ApJ, 827, 51.
18. The Phoenix Stream: a Cold Stream in the Southern Hemisphere. Balbinot, E. et al. 2015, ApJ, 820, 58.
19. Broadband Distortion Modeling in Lyman-alpha Forest BAO Fitting. Blomquist, M. et al. 2015, JCAP, 11, 034.
20. Eight Ultra-faint Galaxy Candidates Discovered in Year Two of the Dark Energy Survey. Drlica-Wagner, A. et al. 2015, ApJ, 813, 109.
21. Chemical Cartography with APOGEE: Metallicity Distribution Functions and the Chemical Structure of the Milky Way Disk. Hayden, M.R. et al. 2015, ApJ, 808, 132.
22. The Difference Imaging Pipeline for the Transient Search in the Dark Energy Survey. Kessler, R. et al. 2015, AJ, 150, 172.
23. The Dark Energy Camera. Flaugher, B. et al. 2015, AJ, 150, 150.
24. Search for Gamma-Ray Emission from DES Dwarf Spheroidal Galaxy Candidates with Fermi-LAT Data. Drlica-Wagner, A. et al. 2015, ApJL, 809, 4.
25. Automated Transient Identification in the Dark Energy Survey. Goldstein, D. A. et al. 2015, AJ, 150, 82.
26. Mock Quasar-Lyman-alpha Forest Data-sets for the SDSS-III Baryon Oscillation Spectroscopic Survey. Bautista, J. et al. 2015, JCAP, 5, 60.
27. The Eleventh and Twelfth Data Releases of the Sloan Digital Sky Survey: Final Data from SDSS-III. Alam, S. et al. 2015, ApJS, 219, 12.
28. The APOKASC Catalog: An Asteroseismic and Spectroscopic Joint Survey of Targets in the Kepler Fields. Pinsonneault, M.H. et al. 2015, ApJS, 215, 19.
29. Stellar Kinematics and Metallicities in the Ultra-faint Dwarf Galaxy Reticulum II. Simon, J.D. et al. 2015, ApJ, 808, 95.
30. Eight New Milky Way Companions Discovered in First-Year Dark Energy Survey Data. Bechtol, K. et al. 2015, ApJ, 807, 50.
31. Globular Cluster Streams as Galactic High-Precision Scales - The Poster Child od Palomar 5. Kupper, A.H.W. et al. 2015, ApJ, 803, 80.
32. Modelling the Transfer Function for the Dark Energy Survey. C.Chang et al. 2015, ApJ, 801, 73.
33. DES J0454-4448: Discovery of the First Luminous z > 6 Quasar from the Dark Energy Survey. Reed, S. L. et al. 2015, MNRAS, 454, 3952.

2014

12
1. Chemo-dynamics with the First Year of APOGEE Data. Anders, F. et al. 2014, A&A, 564, 115.
2. The Sloan Digital Sky Survey Quasar Catalog: Tenth Data Release. Paris, I. et al. 2014, A&A, 536, 54.
3. The Dark Energy Survey and operations: Year 1. Diehl, H. T. et al. 2014, SPIE, 9149, 91490V.
4. The DECam DAQ System: lessons learned after one year of operations. Honscheid, K et al. 2014, SPIE, 9152, 91520G.
5. Bayesian Distances and Extinctions for Giants Observed by Kepler and APOGEE. Rodrigues, T.S. et al. 2014, MNRAS, 445, 2758.
6. Photometric Redshift Analysis in the Dark Energy Survey Science Verification Data. Sánchez, C. et al. 2014, MNRAS, 445, 1482.
7. Orientation Bias of Optically Selected Galaxy Clusters and Its Impact on Stacked Weak Lensing Analyses. Dietrich, J.P. et al. 2014, MNRAS, 443, 1713.
8. On the effect of the ionising background on the Ly{alpha} forest autocorrelation function. Gontcho, S. et al. 2014, MNRAS, 442, 187.
9. The Clustering of Galaxies in the SDSS-III DR10 Baryon Oscillation Spectroscopic Survey: No Detectable Colour Dependence of Distance Scale or Growth Rate Measurements. Ross, A.J. et al. 2014, MNRAS, 437, 1109.
10. Accurate Atmospheric Parameters at Moderate Spectral Resolution: Preliminary Application to the MARVELS Survey. Ghezzi, L. et al. 2014, AJ, 148, 105.
11. Quasar-Lyman-alpha Forest Cross-Correlation from BOSS DR11: Baryon Acoustic Oscillations. Font-Ribera, A. et al. 2014, JC&AP, 05, 027.
12. The Tenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the SDSS-III Apache Point Observatory Galactic Evolution Experiment. Ahn, C.P. et al. 2014, ApJS, 211, 17.

2013

18
1. PreCam, a Precursor Observational Campaign for Calibration of the Dark Energy Survey. Kuehn, K. et al. 2013, PASP, 125, 409.
2. A Simple Prescription for Simulating and Characterizing Gravitational Arcs. Furlanetto, C. et al. 2013, A&A, 549, A80.
3. Large-scale Analysis of the SDSS-III DR8 Photometric Luminous Galaxies Angular Correlation Function. Simoni, F. et al. 2013, MNRAS, 435, 3017.
4. Detecting Massive Galaxies at High Redshift Using the Dark Energy Survey. Davis, L.M.J. et al. 2013, MNRAS, 434, 296.
5. On the Accuracy of the Perturbative Approach for Strong Lensing: Local Distortion for Pseudo-elliptical Models. Dumet-Montoya, H. et al. 2013, MNRAS, 433, 2975.
6. The Soar Gravitational Arc Survey I: Survey Overview and Photometric Catalogs. Furlanetto, C. et al. 2013, MNRAS, 432, 73.
7. The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: the low-redshift sample. Parejko, J. et al. 2013, MNRAS, 429, 98.
8. The Clustering of Galaxies in SDSS-III DR9 Baryon Oscillation Spectroscopic Survey: Constraints on Primordial Non-Gaussianity. Ross, A. et al. 2013, MNRAS, 428, 1116.
9. Target Selection for the Apache Point Observatory Galactic Evolution Experiment (APOGEE). Zasowski, G. et al. 2013, AJ, 146, 81.
10. Very Low Mass Stellar and Substellar Companions to Solar-like Stars From MARVELS IV: A Candidate Brown Dwarf or Low-Mass Stellar Companion to HIP 67526. Jiang, P. et al. 2013, AJ, 146, 65.
11. Very Low Mass Stellar and Substellar Companions to Solar-Like Stars from MARVELS. V. A Low Eccentricity Brown Dwarf from the Driest Part of the Desert, MARVELS-6b. De Lee, N. et al. 2013, AJ, 145, 155.
12. A Cautionary Tale: MARVELS Brown Dwarf Candidate Reveals Itself To Be a Very Long Period, Highly Eccentric Spectroscopic Stellar Binary. Mack III, C.E. et al. 2013, AJ, 145, 139.
13. Very Low-mass Stellar and Substellar Companions to Solar-like Stars from MARVELS III: An Unsynchronyzed, Short-Period Brown Dwarf Candidate Around an Active Subgiant. Ma, B. et al. 2013, AJ, 145, 20.
14. The Baryon Oscillation Spectroscopic Survey of SDSS-III. Dawson, K.S. et al. 2013, AJ, 145, 10.
15. MARVELS-1: A Face-on Double-lined Binary Masquerading as a Resonant Planetary System and Consideration of Rare False Positives in Radial Velocity Planet Searches. Wright, J. et al. 2013, ApJ, 770, 119.
16. The Homogeneous Study of Transiting Systems (HoSTS) I. The Pilot Study of WASP-13. Gómez Maqueo Chew, Y. et al. 2013, ApJ, 768, 79.
17. The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: Luminosity and Color Dependence and Redshift Evolution. Guo, H et al. 2013, ApJ, 767, 122.
18. A New Milky Way Satellite in the Southern Galactic Sky. Balbinot, E. et al. 2013, ApJ, 767, 101.

2012

10
1. Domain of validity for pseudo-elliptical NFW lens models. Mass distribution, mapping to elliptical models, and arc cross section. Dümet-Montoya, H.S. et al. 2012, A&A, 544, A83.
2. The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: Baryon Acoustic Oscillations in the Data Release 9 Spectroscopic Galaxy Sample. Anderson, L. et al. 2012, MNRAS, 427, 3435.
3. The XMM Cluster Survey: Optical analysis methodology and the first data release. Mehrtens, N. et al. 2012, MNRAS, 423, 1024.
4. Very Low-mass Stellar and Substellar Companions to Solar-like Stars from MARVELS II: A Short-period Companion Orbiting an F Star with Evidence of a Stellar Tertiary And Significant Mutual Inclination. Fleming, S.W. et al. 2012, AJ, 144, 72.
5. Very Low-Mass Stellar and Substellar Companions to Solar-Like Stars from MARVELS I: A Low Mass Ratio Stellar Companion to TYC 4110-01037-1 in a 79-day Orbit. Wisniewski, J. et al. 2012, AJ, 143, 107.
6. The Ninth Data Release of The Sloan Digital Sky Survey: First Spectroscopic Data From The SDSS-III Baryon Oscillation Spectroscopic Survey. Ahn, C.P. et al. 2012, ApJS, 203, 21.
7. The Metallicity Distribution Functions of SEGUE G and K dwarfs: Constraints for Disk Chemical Evolution and Formation. Schlesinger, K.J. et al. 2012, ApJ, 761, 160.
8. Clustering of Sloan Digital Sky Survey III Photometric Luminous Galaxies: The Measurement, Systematics and Cosmological Implications. Ho, S. et al. 2012, ApJ, 761, 14.
9. Acoustic scale from the angular power spectra of SDSS-III DR8 photometric luminous galaxies. Seo, H. et al. 2012, ApJ, 761, 13.
10. The Milky Way Circular Velocity Curve Between 4 and 14 kpc from APOGEE Data. Bovy, J. et al. 2012, ApJ, 759, 131.

2011

13
1. Ameliorating Systematic Uncertainties in the Angular Clustering of Galaxies: A Study using SDSS-III. Ross, A. et al. 2011, MNRAS, 417, 1350.
2. The Tidal Tails of NGC 2298. Balbinot, E. et al. 2011, MNRAS, 416, 393.
3. Tracing the sound horizon scale with photometric redshift surveys. Sánchez, E. et al. 2011, MNRAS, 411, 277.
4. Cosmological forecasts from photometric measurements of the angular correlation function. Sobreira, F. et al. 2011, PRD, 84, 103001.
5. Detailed Abundances of the Solar Twins 16 Cygni A and B: Constraining Planet Formation Models. Schuler, S. et al. 2011, ApJ, 737, L32.
6. SDSS-III: Massive Spectroscopic Surveys of the Distant Universe, the Milky Way Galaxy, and Extra-Solar Planetary Systems. Eisenstein, D.J. et al. 2011, AJ, 142, 72.
7. Eclipsing Binary Science Via the Merging of Transit and Doppler Exoplanet Survey Data - A Case Study With the MARVELS Pilot Project and SuperWASP. Fleming, S.W. et al. 2011, AJ, 142, 50.
8. Evolution of Galaxy Luminosity Function Using Photometric Redshifts. Ramos, B. et al. 2011, AJ, 142, 41.
9. The Dark Energy Survey: Prospects for Resolved Stellar Populations. Rossetto, B. et al. 2011, AJ, 141, 185.
10. The Eighth Data Release of the Sloan Digital Sky Survey: First Data from SDSS-III. Aihara, H. et al. 2011, ApJS, 193, 29.
11. Abundances of Stars with Planets: Trends with Condensation Temperature. Schuler, S.C. et al. 2011, ApJ, 732, 55.
12. The clustering of massive galaxies at z~0.5 from the first semester of BOSS data. White, M. et al. 2011, ApJ, 728, 126.
13. MARVELS-1b: A Short-Period, Brown Dwarf Desert Candidate from the SDSS-III MARVELS Planet Search. Lee, B.L. et al. 2011, ApJ, 728, 32.

2010

03
1. The DECam data acquisition and control system. Honscheid, K. et al. 2010, Proceedings of the SPIE, 7740, 53.
2. Status of the dark energy survey camera (DECam) project. Flaugher, B.L. et al. 2010, Proceedings of the SPIE, 7735, 12.
3. The Dark Energy Survey: perspectives for resolved stellar population studies. Santiago et al. 2010, Stellar Populations - Planning for the Next Decade, 262, 265.

2009

02
1. The Dark Energy Survey Data Management System: The Coaddition Pipeline and PSF Homogenization. Darnell, T. et al. 2009, ASPC, 411, 18.
2. The Dark Energy Survey Data-Management System: The Processing Framework. Gower, M. et al. 2009, PASP, 411, 14.

2008

01
1. The Dark Energy Survey data management system. Mohr, J. et al. 2008, Proceedings of the SPIE, 7016, 70160L.