Publications

This page lists publications by the LSST DESC, defined by our Publication Policy. You can also view this publication list on NASA ADS.

DESC members who wish to use materials from DESC publications (e.g., reproducing figures from Key Papers in other publications) should follow instructions on the Publication Board Confluence page. A thesis student may include in their thesis material from DESC publications for which they are a primary author without obtaining permission from DESC, provided attribution is given and all other conditions imposed by their University and the Journal are satisfied.

Submitted for Publication

DeepDISC-photoz: Deep Learning-Based Photometric Redshift Estimation for Rubin LSST, Merz, G., Liu, X., Schmidt, S., Malz, A. I., Zhang, T., Branton, D., Burke, C. J., Delucchi, M., Sai Ejjagiri, Y., Kubica, J., Liu, Y., Lynn, O., Oldag, D., and LSST Dark Energy Science Collaboration, arXiv:2411.18769 [ADS]

Galaxy Clustering with LSST: Effects of Number Count Bias from Blending, Levine, B., Sánchez, J., Chang, C., von der Linden, A., Collins, E., Gawiser, E., Krzyżańska, K., Leistedt, B., and LSST Dark Energy Science Collaboration, arXiv:2411.14564 [ADS]

A halo model approach for mock catalogs of time-variable strong gravitational lenses, Abe, K. T., Oguri, M., Birrer, S., Khadka, N., Marshall, P. J., Lemon, C., More, A., and LSST Dark Energy Science Collaboration, arXiv:2411.07509 [ADS]

StarDICE III: Characterization of the photometric instrument with a Collimated Beam Projector, Souverin, T., Neveu, J., Betoule, M., Bongard, S., Stubbs, C. W., Urbach, E., Brownsberger, S., Éric Blanc, P., Cohen Tanugi, J., Dagoret-Campagne, S., Feinstein, F., Hardin, D., Juramy, C., Le Guillou, L., Le Van Suu, A., Moniez, M., Plez, B., Regnault, N., Sepulveda, E., Sommer, K., and LSST Dark Energy Science Collaboration, arXiv:2410.24173 [ADS]

Lens Modeling of STRIDES Strongly Lensed Quasars using Neural Posterior Estimation, Erickson, S., Wagner-Carena, S., Marshall, P., Millon, M., Birrer, S., Roodman, A., Schmidt, T., Treu, T., Schuldt, S., Shajib, A., Venkatraman, P., and LSST Dark Energy Science Collaboration, arXiv:2410.10123 [ADS]

Simulation-Based Inference Benchmark for LSST Weak Lensing Cosmology, Zeghal, J., Lanzieri, D., Lanusse, F., Boucaud, A., Louppe, G., Aubourg, E., Bayer, A. E., and LSST Dark Energy Science Collaboration, arXiv:2409.17975 [ADS]

Impact of Large-Scale Structure Systematics on Cosmological Parameter Estimation, Awan, H., Gawiser, E., Sanchez, J., Sevilla-Noarbe, I., and LSST Dark Energy Science Collaboration, arXiv:2409.14265 [ADS]

The Blending ToolKit: A simulation framework for evaluation of galaxy detection and deblending, Mendoza, I., Torchylo, A., Sainrat, T., Guinot, A., Boucaud, A., Paillasa, M., Avestruz, C., Adari, P., Aubourg, E., Biswas, B., Buchanan, J., Burchat, P., Doux, C., Joseph, R., Kamath, S., Malz, A. I., Merz, G., Miyatake, H., Roucelle, C., Zhang, T., and LSST Dark Energy Science Collaboration, arXiv:2409.06986 [ADS]

YOLO-CL cluster detection in the Rubin/LSST DC2 simulation, Grishin, K., Mei, S., Ilic, S., Aguena, M., Boutigny, D., Paturel, M., and LSST Dark Energy Science Collaboration, arXiv:2409.03333 [ADS]

Modeling the 3-point correlation function of projected scalar fields on the sphere, Arvizu, A., Aviles, A., Hidalgo, J. C., Moreno, E., Niz, G., Rodriguez-Meza, M. A., Samario, S., and LSST Dark Energy Science Collaboration, arXiv:2408.16847 [ADS]

MADNESS Deblender: Maximum A posteriori with Deep NEural networks for Source Separation, Biswas, B., Aubourg, E., Boucaud, A., Guinot, A., Lao, J., Roucelle, C., and LSST Dark Energy Science Collaboration, arXiv:2408.15236 [ADS]

Analytical Weak Lensing Shear Inference for Precision Cosmology, Li, X., Mandelbaum, R., and LSST Dark Energy Science Collaboration, arXiv:2408.06337 [ADS]

The little coadd that could: Estimating shear from coadded images, Armstrong, R., Sheldon, E., Huff, E., Bosch, J., Rykoff, E., Mandelbaum, R., Kannawadi, A., Melchior, P., Lupton, R., Becker, M. R., Al-Sayyed, Y., and LSST Dark Energy Science Collaboration, arXiv:2407.01771 [ADS]

Joint Modelling of Astrophysical Systematics for Cosmology with LSST, Šarčević, N., Leonard, C. D., Rau, M. M., and LSST Dark Energy Science Collaboration, arXiv:2406.03352 [ADS]

Machine Learning LSST 3x2pt analyses – forecasting the impact of systematics on cosmological constraints using neural networks, Boruah, S. S., Eifler, T., Miranda, V., Farah, E., Motka, J., Krause, E., Fang, X., Rogozenski, P., and LSST Dark Energy Science Collaboration, arXiv:2403.11797 [ADS]

Cosmology with imaging galaxy surveys: the impact of evolving galaxy bias and magnification, Pandey, S., Sánchez, C., Jain, B., and LSST Dark Energy Science Collaboration, arXiv:2310.01315 [ADS]

Variational Inference for Deblending Crowded Starfields, Liu, R., McAuliffe, J. D., Regier, J., and LSST Dark Energy Science Collaboration, arXiv:2102.02409 [ADS]

Are classification metrics good proxies for SN Ia cosmological constraining power?, Malz, A. I., Dai, M., Ponder, K. A., Ishida, E. E. O., Gonzalez-Gaitain, S., Durgesh, R., Krone-Martins, A., de Souza, R. S., Kennamer, N., Sreejith, S., Galbany, L., LSST Dark Energy Science Collaboration, and Cosmostatistics Initiative, T., arXiv:2305.14421 [ADS]

A Modular Deep Learning Pipeline for Galaxy-Scale Strong Gravitational Lens Detection and Modeling, Madireddy, S., Ramachandra, N., Li, N., Butler, J., Balaprakash, P., Habib, S., Heitmann, K., and LSST Dark Energy Science Collaboration, arXiv:1911.03867 [ADS]

Published Journal Papers

2024

Impact of survey spatial variability on galaxy redshift distributions and the cosmological 3 × 2-point statistics for the Rubin Legacy Survey of Space and Time (LSST), Hang, Q., Joachimi, B., Charles, E., Crenshaw, J. F., Larsen, P., Malz, A. I., Schmidt, S., Yan, Z., Zhang, T., Leistedt, B., Rau, M., Bianco, F., Burchat, P., Hearin, A., Kovacs, E., Lahav, O., Mandelbaum, R., Nicola, A., Yoachim, P., and LSST Dark Energy Science Collaboration, MNRAS, 535, 2970 (2024) [arXiv][ADS]

A Cohesive Deep Drilling Field Strategy for LSST Cosmology, Gris, P., Awan, H., Becker, M. R., Lin, H., Gawiser, E., Jha, S. W., and LSST Dark Energy Science Collaboration, ApJS, 275, 21 (2024) [arXiv][ADS]

Astrometric Redshifts of Supernovae, Lee, J. (Jason) ., Sako, M., Kessler, R., Malz, A. I., and LSST Dark Energy Science Collaboration, ApJ, 977, 199 (2024) [arXiv][ADS]

The impact of environment on size: Galaxies are 50% smaller in the Fornax Cluster compared to the field, Chamba, N., Hayes, M. J., and LSST Dark Energy Science Collaboration, A&A, 689, A28 (2024) [arXiv][ADS]

Probabilistic Forward Modeling of Galaxy Catalogs with Normalizing Flows, Crenshaw, J. F., Kalmbach, J. B., Gagliano, A., Yan, Z., Connolly, A. J., Malz, A. I., Schmidt, S. J., and LSST Dark Energy Science Collaboration, AJ, 168, 80 (2024) [arXiv][ADS]

Detecting strongly lensed type Ia supernovae with LSST, Arendse, N., Dhawan, S., Sagués Carracedo, A., Peiris, H. V., Goobar, A., Wojtak, R., Alves, C., Biswas, R., Huber, S., Birrer, S., and LSST Dark Energy Science Collaboration, MNRAS, 531, 3509 (2024) [arXiv][ADS]

An Empirical Model For Intrinsic Alignments: Insights From Cosmological Simulations, Van Alfen, N., Campbell, D., Blazek, J., Leonard, C. D., Lanusse, F., Hearin, A., Mandelbaum, R., and LSST Dark Energy Science Collaboration, OJAp, 7, 45 (2024) [arXiv][ADS]

Recovered supernova Ia rate from simulated LSST images, Petrecca, V., Botticella, M. T., Cappellaro, E., Greggio, L., Sánchez, B. O., Möller, A., Sako, M., Graham, M. L., Paolillo, M., Bianco, F., and LSST Dark Energy Science Collaboration, A&A, 686, A11 (2024) [arXiv][ADS]

Impact of property covariance on cluster weak lensing scaling relations, Zhang, Z., Farahi, A., Nagai, D., Lau, E. T., Frieman, J., Ricci, M., von der Linden, A., Wu, H.-Y., and LSST Dark Energy Science Collaboration, MNRAS, 530, 3127 (2024) [arXiv][ADS]

Improving Photometric Redshift Estimates with Training Sample Augmentation, Moskowitz, I., Gawiser, E., Crenshaw, J. F., Andrews, B. H., Malz, A. I., Schmidt, S., and LSST Dark Energy Science Collaboration, ApJL, 967, L6 (2024) [arXiv][ADS]

Generation of realistic input parameters for simulating atmospheric point-spread functions at astronomical observatories, Hébert, C.-A., Meyers, J. E., Do, M. H., Burchat, P. R., and LSST Dark Energy Science Collaboration, OJAp, 7, 22 (2024) [arXiv][ADS]

Slitless spectrophotometry with forward modelling: Principles and application to measuring atmospheric transmission, Neveu, J., Brémaud, V., Antilogus, P., Barret, F., Bongard, S., Copin, Y., Dagoret-Campagne, S., Juramy, C., Le Guillou, L., Moniez, M., Sepulveda, E., and LSST Dark Energy Science Collaboration, A&A, 684, A21 (2024) [arXiv][ADS]

Galaxy bias in the era of LSST: perturbative bias expansions, Nicola, A., Hadzhiyska, B., Findlay, N., García-García, C., Alonso, D., Slosar, A., Guo, Z., Kokron, N., Angulo, R., Aviles, A., Blazek, J., Dunkley, J., Jain, B., Pellejero, M., Sullivan, J., Walter, C. W., Zennaro, M., and LSST Dark Energy Science Collaboration, JCAP, 2024, 015 (2024) [arXiv][ADS]

2023

Forecasting the power of higher order weak-lensing statistics with automatically differentiable simulations, Lanzieri, D., Lanusse, F., Modi, C., Horowitz, B., Harnois-Déraps, J., Starck, J.-L., and LSST Dark Energy Science Collaboration (LSST DESC), A&A, 679, A61 (2023) [arXiv][ADS]

What’s the Difference? The Potential for Convolutional Neural Networks for Transient Detection without Template Subtraction, Acero-Cuellar, T., Bianco, F., Dobler, G., Sako, M., Qu, H., and LSST Dark Energy Science Collaboration, AJ, 166, 115 (2023) [arXiv][ADS]

Results of the Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC), Hložek, R., Malz, A. I., Ponder, K. A., Dai, M., Narayan, G., Ishida, E. E. O., Allam, T., Bahmanyar, A., Bi, X., Biswas, R., Boone, K., Chen, S., Du, N., Erdem, A., Galbany, L., Garreta, A., Jha, S. W., Jones, D. O., Kessler, R., Lin, M., Liu, J., Lochner, M., Mahabal, A. A., Mandel, K. S., Margolis, P., Martínez-Galarza, J. R., McEwen, J. D., Muthukrishna, D., Nakatsuka, Y., Noumi, T., Oya, T., Peiris, H. V., Peters, C. M., Puget, J. F., Setzer, C. N., Siddhartha, Stefanov, S., Xie, T., Yan, L., Yeh, K.-H., and Zuo, W., ApJS, 267, 25 (2023) [arXiv][ADS]

Hierarchical Inference of the Lensing Convergence from Photometric Catalogs with Bayesian Graph Neural Networks, Park, J. W., Birrer, S., Ueland, M., Cranmer, M., Agnello, A., Wagner-Carena, S., Marshall, P. J., Roodman, A., and LSST Dark Energy Science Collaboration, ApJ, 953, 178 (2023) [arXiv][ADS]

A joint Roman Space Telescope and Rubin Observatory synthetic wide-field imaging survey, Troxel, M. A., Lin, C., Park, A., Hirata, C., Mandelbaum, R., Jarvis, M., Choi, A., Givans, J., Higgins, M., Sanchez, B., Yamamoto, M., Awan, H., Chiang, J., Doré, O., Walter, C. W., Zhang, T., Cohen-Tanugi, J., Gawiser, E., Hearin, A., Heitmann, K., Ishak, M., Kovacs, E., Mao, Y.-Y., Wood-Vasey, M., Becker, M., Meyers, J., Melchior, P., and LSST Dark Energy Science Collaboration, MNRAS, 522, 2801 (2023) [arXiv][ADS]

Improved Tomographic Binning of 3 × 2 pt Lens Samples: Neural Network Classifiers and Optimal Bin Assignments, Moskowitz, I., Gawiser, E., Bault, A., Broussard, A., Newman, J. A., Zuntz, J., and LSST Dark Energy Science Collaboration, ApJ, 950, 49 (2023) [arXiv][ADS]

Metadetection Weak Lensing for the Vera C. Rubin Observatory, Sheldon, E. S., Becker, M. R., Jarvis, M., Armstrong, R., and LSST Dark Energy Science Collaboration, OJAp, 6, 17 (2023) [arXiv][ADS]

The catalog-to-cosmology framework for weak lensing and galaxy clustering for LSST, Prat, J., Zuntz, J., Chang, C., Tröster, T., Pedersen, E., García-García, C., Phillips-Longley, E., Sanchez, J., Alonso, D., Fang, X., Gawiser, E., Heitmann, K., Ishak, M., Jarvis, M., Kovacs, E., Larsen, P., Mao, Y.-Y., Medina Varela, L., Paterno, M., Vitenti, S. D., Zhang, Z., and LSST Dark Energy Science Collaboration, OJAp, 6, 13 (2023) [arXiv][ADS]

A unified catalogue-level reanalysis of stage-III cosmic shear surveys, Longley, E. P., Chang, C., Walter, C. W., Zuntz, J., Ishak, M., Mandelbaum, R., Miyatake, H., Nicola, A., Pedersen, E. M., Pereira, M. E. S., Prat, J., Sánchez, J., Secco, L. F., Tröster, T., Troxel, M., Wright, A. H., and LSST Dark Energy Science Collaboration, MNRAS, 520, 5016 (2023) [arXiv][ADS]

The simulated catalogue of optical transients and correlated hosts (SCOTCH), Lokken, M., Gagliano, A., Narayan, G., Hložek, R., Kessler, R., Crenshaw, J. F., Salo, L., Alves, C. S., Chatterjee, D., Vincenzi, M., Malz, A. I., and LSST Dark Energy Science Collaboration, MNRAS, 520, 2887 (2023) [arXiv][ADS]

Impact of point spread function higher moments error on weak gravitational lensing - II. A comprehensive study, Zhang, T., Almoubayyed, H., Mandelbaum, R., Meyers, J. E., Jarvis, M., Kannawadi, A., Schmitz, M. A., Guinot, A., and LSST Dark Energy Science Collaboration, MNRAS, 520, 2328 (2023) [arXiv][ADS]

Fat cosmic ray tracks in charge-coupled devices, Grosson, T. A., Nomerotski, A., and LSST Dark Energy Science Collaboration, JATIS, 9, 028006 (2023) [arXiv][ADS]

Impact of Rubin Observatory Cadence Choices on Supernovae Photometric Classification, Alves, C. S., Peiris, H. V., Lochner, M., McEwen, J. D., Kessler, R., and LSST Dark Energy Science Collaboration, ApJS, 265, 43 (2023) [arXiv][ADS]

Measurement of Telescope Transmission Using a Collimated Beam Projector, Mondrik, N., Coughlin, M., Betoule, M., Bongard, S., Rice, J. P., Shaw, P.-S., Stubbs, C. W., Woodward, J. T., and LSST Dark Energy Science Collaboration, PASP, 135, 035001 (2023) [arXiv][ADS]

Fringing Analysis and Simulation for the Vera C. Rubin Observatory’s Legacy Survey of Space and Time, Guo, Z., Walter, C. W., Lage, C., Lupton, R. H., and LSST Dark Energy Science Collaboration, PASP, 135, 034503 (2023) [arXiv][ADS]

Hi-COLA: fast, approximate simulations of structure formation in Horndeski gravity, Wright, B. S., Sen Gupta, A., Baker, T., Valogiannis, G., Fiorini, B., and LSST Dark Energy Science Collaboration, JCAP, 2023, 040 (2023) [arXiv][ADS]

The N5K Challenge: Non-Limber Integration for LSST Cosmology, Leonard, C. D., Ferreira, T., Fang, X., Reischke, R., Schoeneberg, N., Tröster, T., Alonso, D., Campagne, J.-E., Lanusse, F., Slosar, A., and Ishak, M., OJAp, 6, 8 (2023) [arXiv][ADS]

PSFs of coadded images, Mandelbaum, R., Jarvis, M., Lupton, R. H., Bosch, J., Kannawadi, A., Murphy, M. D., Zhang, T., and LSST Dark Energy Science Collaboration, OJAp, 6, 5 (2023) [arXiv][ADS]

Optimizing the shape of photometric redshift distributions with clustering cross-correlations, Stölzner, B., Joachimi, B., Korn, A., and LSST Dark Energy Science Collaboration, MNRAS, 519, 2438 (2023) [arXiv][ADS]

Using Host Galaxy Photometric Redshifts to Improve Cosmological Constraints with Type Ia Supernovae in the LSST Era, Mitra, A., Kessler, R., More, S., Hložek, R., and LSST Dark Energy Science Collaboration, ApJ, 944, 212 (2023) [arXiv][ADS]

Designing an Optimal LSST Deep Drilling Program for Cosmology with Type Ia Supernovae, Gris, P., Regnault, N., Awan, H., Hook, I., Jha, S. W., Lochner, M., Sanchez, B., Scolnic, D., Sullivan, M., Yoachim, P., and LSST Dark Energy Science Collaboration, ApJS, 264, 22 (2023) [arXiv][ADS]

2022

Galaxy blending effects in deep imaging cosmic shear probes of cosmology, Nourbakhsh, E., Tyson, J. A., Schmidt, S. J., Armstrong, B., Burchat, P., Sánchez, J., and LSST Dark Energy Science Collaboration, MNRAS, 514, 5905 (2022) [arXiv][ADS]

Transitioning from Stage-III to Stage-IV: cosmology from galaxy×CMB lensing and shear×CMB lensing, Zhang, Z. (Jackie) ., Chang, C., Larsen, P., Secco, L. F., Zuntz, J., and LSST Dark Energy Science Collaboration, MNRAS, 514, 2181 (2022) [arXiv][ADS]

SNIa Cosmology Analysis Results from Simulated LSST Images: From Difference Imaging to Constraints on Dark Energy, Sánchez, B. O., Kessler, R., Scolnic, D., Armstrong, R., Biswas, R., Bogart, J., Chiang, J., Cohen-Tanugi, J., Fouchez, D., Gris, P., Heitmann, K., Hložek, R., Jha, S., Kelly, H., Liu, S., Narayan, G., Racine, B., Rykoff, E., Sullivan, M., Walter, C. W., Wood-Vasey, W. M., and LSST Dark Energy Science Collaboration (DESC), ApJ, 934, 96 (2022) [arXiv][ADS]

Perturbation theory models for LSST-era galaxy clustering: Tests with subpercent mock catalog measurements in Fourier and configuration space, Goldstein, S., Pandey, S., Slosar, A., Blazek, J., Jain, B., and LSST Dark Energy Science Collaboration, PhRvD, 105, 123518 (2022) [arXiv][ADS]

Forecasting the potential of weak lensing magnification to enhance LSST large-scale structure analyses, Mahony, C., Fortuna, M. C., Joachimi, B., Korn, A., Hoekstra, H., Schmidt, S. J., Alonso, D., Singh, S., Ricci, M., Hildebrandt, H., Duncan, C., Johnston, H., and LSST Dark Energy Science Collaboration, MNRAS, 513, 1210 (2022) [arXiv][ADS]

The Impact of Observing Strategy on Cosmological Constraints with LSST, Lochner, M., Scolnic, D., Almoubayyed, H., Anguita, T., Awan, H., Gawiser, E., A Gontcho, S. G., Graham, M. L., Gris, P., Huber, S., Jha, S. W., Lynne Jones, R., Kim, A. G., Mandelbaum, R., Marshall, P., Petrushevska, T., Regnault, N., Setzer, C. N., Suyu, S. H., Yoachim, P., Biswas, R., Blaineau, T., Hook, I., Moniez, M., Neilsen, E., Peiris, H., Rothchild, D., Stubbs, C., and LSST Dark Energy Science Collaboration, ApJS, 259, 58 (2022) [arXiv][ADS]

Impact of point spread function higher moments error on weak gravitational lensing, Zhang, T., Mandelbaum, R., and LSST Dark Energy Science Collaboration, MNRAS, 510, 1978 (2022) [arXiv][ADS]

A composite likelihood approach for inference under photometric redshift uncertainty, Rau, M. M., Morrison, C. B., Schmidt, S. J., Wilson, S., Mandelbaum, R., Mao, Y.-Y., and LSST Dark Energy Science Collaboration, MNRAS, 509, 4886 (2022) [arXiv][ADS]

Considerations for Optimizing the Photometric Classification of Supernovae from the Rubin Observatory, Alves, C. S., Peiris, H. V., Lochner, M., McEwen, J. D., Allam, T., Biswas, R., and LSST Dark Energy Science Collaboration, ApJS, 258, 23 (2022) [arXiv][ADS]

Validating Synthetic Galaxy Catalogs for Dark Energy Science in the LSST Era, Kovacs, E., Mao, Y.-Y., Aguena, M., Bahmanyar, A., Broussard, A., Butler, J., Campbell, D., Chang, C., Fu, S., Heitmann, K., Korytov, D., Lanusse, F., Larsen, P., Mandelbaum, R., Morrison, C. B., Payerne, C., Ricci, M., Rykoff, E., Sánchez, F. J., Sevilla-Noarbe, I., Simet, M., To, C.-H., Vikraman, V., Zhou, R., Avestruz, C., Benoist, C., Benson, A. J., Bleem, L., Ćiprianović, A., Combet, C., Gawiser, E., He, S., Joseph, R., Newman, J. A., Prat, J., Schmidt, S., Slosar, A., and Zuntz, J., OJAp, 5, 1 (2022) [arXiv][ADS]

2021

CLMM: a LSST-DESC cluster weak lensing mass modeling library for cosmology, Aguena, M., Avestruz, C., Combet, C., Fu, S., Herbonnet, R., Malz, A. I., Penna-Lima, M., Ricci, M., Vitenti, S. D. P., Baumont, L., Fan, H., Fong, M., Ho, M., Kirby, M., Payerne, C., Boutigny, D., Lee, B., Liu, B., McClintock, T., Miyatake, H., Sifón, C., von der Linden, A., Wu, H., Yoon, M., and LSST Dark Energy Science Collaboration, MNRAS, 508, 6092 (2021) [arXiv][ADS]

Optimizing a magnitude-limited spectroscopic training sample for photometric classification of supernovae, Carrick, J. E., Hook, I. M., Swann, E., Boone, K., Frohmaier, C., Kim, A. G., Sullivan, M., and LSST Dark Energy Science Collaboration, MNRAS, 508, 1 (2021) [arXiv][ADS]

Simultaneous Estimation of Large-scale Structure and Milky Way Dust Extinction from Galaxy Surveys, Bravo, M., Gawiser, E., Padilla, N. D., DeRose, J., Wechsler, R. H., and LSST Dark Energy Science Collaboration, ApJ, 921, 108 (2021) [arXiv][ADS]

The LSST-DESC 3x2pt Tomography Optimization Challenge, Zuntz, J., Lanusse, F., Malz, A. I., Wright, A. H., Slosar, A., Abolfathi, B., Alonso, D., Bault, A., Bom, C. R., Brescia, M., Broussard, A., Campagne, J.-E., Cavuoti, S., Cypriano, E. S., Fraga, B. M. O., Gawiser, E., Gonzalez, E. J., Green, D., Hatfield, P., Iyer, K., Kirkby, D., Nicola, A., Nourbakhsh, E., Park, A., Teixeira, G., Heitmann, K., Kovacs, E., Mao, Y.-Y., and LSST Dark Energy Science Collaboration, OJAp, 4, 13 (2021) [arXiv][ADS]

A transmission hologram for slitless spectrophotometry on a convergent telescope beam. 1. Focus and resolution, Moniez, M., Neveu, J., Dagoret-Campagne, S., Gentet, Y., Le Guillou, L., and LSST Dark Energy Science Collaboration, MNRAS, 506, 5589 (2021) [arXiv][ADS]

Poisson_CCD: A dedicated simulator for modeling CCDs, Lage, C., Bradshaw, A., Anthony Tyson, J., and LSST Dark Energy Science Collaboration, JAP, 130, 164502 (2021) [arXiv][ADS]

Sparse Bayesian mass mapping with uncertainties: hypothesis testing of structure, Price, M. A., McEwen, J. D., Cai, X., Kitching, T. D., Wallis, C. G. R., and LSST Dark Energy Science Collaboration, MNRAS, 506, 3678 (2021) [arXiv][ADS]

Effects of overlapping sources on cosmic shear estimation: Statistical sensitivity and pixel-noise bias, Sanchez, J., Mendoza, I., Kirkby, D. P., Burchat, P. R., and LSST Dark Energy Science Collaboration, JCAP, 2021, 043 (2021) [arXiv][ADS]

Matter power spectrum emulator for f (R ) modified gravity cosmologies, Ramachandra, N., Valogiannis, G., Ishak, M., Heitmann, K., and LSST Dark Energy Science Collaboration, PhRvD, 103, 123525 (2021) [arXiv][ADS][Zenodo]

Data compression and covariance matrix inspection: Cosmic shear, Ferreira, T., Zhang, T., Chen, N., Dodelson, S., and LSST Dark Energy Science Collaboration, PhRvD, 103, 103535 (2021) [arXiv][ADS]

The LSST DESC DC2 Simulated Sky Survey, LSST Dark Energy Science Collaboration (LSST DESC), Abolfathi, B., Alonso, D., Armstrong, R., Aubourg, É., Awan, H., Babuji, Y. N., Bauer, F. E., Bean, R., Beckett, G., Biswas, R., Bogart, J. R., Boutigny, D., Chard, K., Chiang, J., Claver, C. F., Cohen-Tanugi, J., Combet, C., Connolly, A. J., Daniel, S. F., Digel, S. W., Drlica-Wagner, A., Dubois, R., Gangler, E., Gawiser, E., Glanzman, T., Gris, P., Habib, S., Hearin, A. P., Heitmann, K., Hernandez, F., Hložek, R., Hollowed, J., Ishak, M., Ivezić, Ž., Jarvis, M., Jha, S. W., Kahn, S. M., Kalmbach, J. B., Kelly, H. M., Kovacs, E., Korytov, D., Krughoff, K. S., Lage, C. S., Lanusse, F., Larsen, P., Le Guillou, L., Li, N., Longley, E. P., Lupton, R. H., Mandelbaum, R., Mao, Y.-Y., Marshall, P., Meyers, J. E., Moniez, M., Morrison, C. B., Nomerotski, A., O’Connor, P., Park, H., Park, J. W., Peloton, J., Perrefort, D., Perry, J., Plaszczynski, S., Pope, A., Rasmussen, A., Reil, K., Roodman, A. J., Rykoff, E. S., Sánchez, F. J., Schmidt, S. J., Scolnic, D., Stubbs, C. W., Tyson, J. A., Uram, T. D., Villarreal, A. S., Walter, C. W., Wiesner, M. P., Wood-Vasey, W. M., and Zuntz, J., ApJS, 253, 31 (2021) [arXiv][ADS]

Large-scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant, Park, J. W., Wagner-Carena, S., Birrer, S., Marshall, P. J., Lin, J. Y.-Y., Roodman, A., and LSST Dark Energy Science Collaboration, ApJ, 910, 39 (2021) [arXiv][ADS]

Hierarchical Inference with Bayesian Neural Networks: An Application to Strong Gravitational Lensing, Wagner-Carena, S., Park, J. W., Birrer, S., Marshall, P. J., Roodman, A., Wechsler, R. H., and LSST Dark Energy Science Collaboration, ApJ, 909, 187 (2021) [arXiv][ADS][Zenodo]

Characterizing the Sample Selection for Supernova Cosmology, Kim, A. G. and LSST Dark Energy Science Consortium, OJAp, 4, 2 (2021) [arXiv][ADS]

GHOST: Using Only Host Galaxy Information to Accurately Associate and Distinguish Supernovae, Gagliano, A., Narayan, G., Engel, A., Carrasco Kind, M., and LSST Dark Energy Science Collaboration, ApJ, 908, 170 (2021) [arXiv][ADS]

Deblending galaxies with variational autoencoders: A joint multiband, multi-instrument approach, Arcelin, B., Doux, C., Aubourg, E., Roucelle, C., and LSST Dark Energy Science Collaboration, MNRAS, 500, 531 (2021) [arXiv][ADS]

2020

Non-Gaussianity in the weak lensing correlation function likelihood - implications for cosmological parameter biases, Lin, C.-H., Harnois-Déraps, J., Eifler, T., Pospisil, T., Mandelbaum, R., Lee, A. B., Singh, S., and LSST Dark Energy Science Collaboration, MNRAS, 499, 2977 (2020) [arXiv][ADS]

Evaluation of probabilistic photometric redshift estimation approaches for The Rubin Observatory Legacy Survey of Space and Time (LSST), Schmidt, S. J., Malz, A. I., Soo, J. Y. H., Almosallam, I. A., Brescia, M., Cavuoti, S., Cohen-Tanugi, J., Connolly, A. J., DeRose, J., Freeman, P. E., Graham, M. L., Iyer, K. G., Jarvis, M. J., Kalmbach, J. B., Kovacs, E., Lee, A. B., Longo, G., Morrison, C. B., Newman, J. A., Nourbakhsh, E., Nuss, E., Pospisil, T., Tranin, H., Wechsler, R. H., Zhou, R., Izbicki, R., and LSST Dark Energy Science Collaboration, MNRAS, 499, 1587 (2020) [arXiv][ADS]

Optimizing LSST observing strategy for weak lensing systematics, Almoubayyed, H., Mandelbaum, R., Awan, H., Gawiser, E., Jones, R. L., Meyers, J., Tyson, J. A., Yoachim, P., and LSST Dark Energy Science Collaboration, MNRAS, 499, 1140 (2020) [arXiv][ADS]

The LSST DESC data challenge 1: generation and analysis of synthetic images for next-generation surveys, Sánchez, J., Walter, C. W., Awan, H., Chiang, J., Daniel, S. F., Gawiser, E., Glanzman, T., Kirkby, D., Mandelbaum, R., Slosar, A., Wood-Vasey, W. M., AlSayyad, Y., Burke, C. J., Digel, S. W., Jarvis, M., Johnson, T., Kelly, H., Krughoff, S., Lupton, R. H., Marshall, P. J., Peterson, J. R., Price, P. A., Sembroski, G., Van Klaveren, B., Wiesner, M. P., Xin, B., and LSST Dark Energy Science Collaboration, MNRAS, 497, 210 (2020) [arXiv][ADS]

Generating synthetic cosmological data with GalSampler, Hearin, A., Korytov, D., Kovacs, E., Benson, A., Aung, H., Bradshaw, C., Campbell, D., and LSST Dark Energy Science Collaboration, MNRAS, 495, 5040 (2020) [arXiv][ADS]

Enabling Catalog Simulations of Transient and Variable Sources Based on LSST Cadence Strategies, Biswas, R., Daniel, S. F., Hložek, R., Kim, A. G., Yoachim, P., and LSST Dark Energy Science Collaboration, ApJS, 247, 60 (2020) [arXiv][ADS][Zenodo]

Tomographic galaxy clustering with the Subaru Hyper Suprime-Cam first year public data release, Nicola, A., Alonso, D., Sánchez, J., Slosar, A., Awan, H., Broussard, A., Dunkley, J., Gawiser, E., Gomes, Z., Mandelbaum, R., Miyatake, H., Newman, J. A., Sevilla-Noarbe, I., Skinner, S., and Wagoner, E. L., JCAP, 2020, 044 (2020) [arXiv][ADS]

Sparse Bayesian mass mapping with uncertainties: local credible intervals, Price, M. A., Cai, X., McEwen, J. D., Pereyra, M., Kitching, T. D., and LSST Dark Energy Science Collaboration, MNRAS, 492, 394 (2020) [arXiv][ADS]

Shear Measurement Bias Due to Spatially Varying Spectral Energy Distributions in Galaxies, Kamath, S., Meyers, J. E., Burchat, P. R., and LSST Dark Energy Science Collaboration, ApJ, 888, 23 (2020) [arXiv][ADS]

2019

CosmoDC2: A Synthetic Sky Catalog for Dark Energy Science with LSST, Korytov, D., Hearin, A., Kovacs, E., Larsen, P., Rangel, E., Hollowed, J., Benson, A. J., Heitmann, K., Mao, Y.-Y., Bahmanyar, A., Chang, C., Campbell, D., DeRose, J., Finkel, H., Frontiere, N., Gawiser, E., Habib, S., Joachimi, B., Lanusse, F., Li, N., Mandelbaum, R., Morrison, C., Newman, J. A., Pope, A., Rykoff, E., Simet, M., To, C.-H., Vikraman, V., Wechsler, R. H., White, M., and LSST Dark Energy Science Collaboration, ApJS, 245, 26 (2019) [arXiv][ADS]

Sparse Bayesian mass mapping with uncertainties: peak statistics and feature locations, Price, M. A., McEwen, J. D., Cai, X., Kitching, T. D., and LSST Dark Energy Science Collaboration, MNRAS, 489, 3236 (2019) [arXiv][ADS]

The Photometric LSST Astronomical Time-series Classification Challenge PLAsTiCC: Selection of a Performance Metric for Classification Probabilities Balancing Diverse Science Goals, Malz, A. I., Hložek, R., Allam, T., Bahmanyar, A., Biswas, R., Dai, M., Galbany, L., Ishida, E. E. O., Jha, S. W., Jones, D. O., Kessler, R., Lochner, M., Mahabal, A. A., Mandel, K. S., Martínez-Galarza, J. R., McEwen, J. D., Muthukrishna, D., Narayan, G., Peiris, H., Peters, C. M., Ponder, K., Setzer, C. N., LSST Dark Energy Science Collaboration, LSST Transients and Variable Stars Science Collaboration, AJ, 158, 171 (2019) [arXiv][ADS]

Strongly lensed SNe Ia in the era of LSST: observing cadence for lens discoveries and time-delay measurements, Huber, S., Suyu, S. H., Noebauer, U. M., Bonvin, V., Rothchild, D., Chan, J. H. H., Awan, H., Courbin, F., Kromer, M., Marshall, P., Oguri, M., Ribeiro, T., and LSST Dark Energy Science Collaboration, A&A, 631, A161 (2019) [arXiv][ADS]

Models and Simulations for the Photometric LSST Astronomical Time Series Classification Challenge (PLAsTiCC), Kessler, R., Narayan, G., Avelino, A., Bachelet, E., Biswas, R., Brown, P. J., Chernoff, D. F., Connolly, A. J., Dai, M., Daniel, S., Di Stefano, R., Drout, M. R., Galbany, L., González-Gaitán, S., Graham, M. L., Hložek, R., Ishida, E. E. O., Guillochon, J., Jha, S. W., Jones, D. O., Mandel, K. S., Muthukrishna, D., O’Grady, A., Peters, C. M., Pierel, J. R., Ponder, K. A., Prša, A., Rodney, S., Villar, V. A., LSST Dark Energy Science Collaboration, and Transient and Variable Stars Science Collaboration, PASP, 131, 094501 (2019) [arXiv][ADS][Zenodo-1][Zenodo-2]

The shape of the photon transfer curve of CCD sensors, Astier, P., Antilogus, P., Juramy, C., Le Breton, R., Le Guillou, L., and Sepulveda, E., A&A, 629, A36 (2019) [arXiv][ADS]

Serendipitous discoveries of kilonovae in the LSST main survey: maximizing detections of sub-threshold gravitational wave events, Setzer, C. N., Biswas, R., Peiris, H. V., Rosswog, S., Korobkin, O., Wollaeger, R. T., and LSST Dark Energy Science Collaboration, MNRAS, 485, 4260 (2019) [arXiv][ADS]

Core Cosmology Library: Precision Cosmological Predictions for LSST, Chisari, N. E., Alonso, D., Krause, E., Leonard, C. D., Bull, P., Neveu, J., Villarreal, A. S., Singh, S., McClintock, T., Ellison, J., Du, Z., Zuntz, J., Mead, A., Joudaki, S., Lorenz, C. S., Tröster, T., Sanchez, J., Lanusse, F., Ishak, M., Hložek, R., Blazek, J., Campagne, J.-E., Almoubayyed, H., Eifler, T., Kirby, M., Kirkby, D., Plaszczynski, S., Slosar, A., Vrastil, M., Wagoner, E. L., and LSST Dark Energy Science Collaboration, ApJS, 242, 2 (2019) [arXiv][ADS][Zenodo]

A unified pseudo-Cℓ framework, Alonso, D., Sanchez, J., Slosar, A., and LSST Dark Energy Science Collaboration, MNRAS, 484, 4127 (2019) [arXiv][ADS]

Self-calibration method for II and GI types of intrinsic alignments of galaxies, Yao, J., Ishak, M., Troxel, M. A., and LSST Dark Energy Science Collaboration, MNRAS, 483, 276 (2019) [arXiv][ADS]

A unified analysis of four cosmic shear surveys, Chang, C., Wang, M., Dodelson, S., Eifler, T., Heymans, C., Jarvis, M., Jee, M. J., Joudaki, S., Krause, E., Malz, A., Mandelbaum, R., Mohammed, I., Schneider, M., Simet, M., Troxel, M. A., Zuntz, J., and LSST Dark Energy Science Collaboration, MNRAS, 482, 3696 (2019) [arXiv][ADS][Zenodo]

2018

Measuring the scale dependence of intrinsic alignments using multiple shear estimates, Leonard, C. D., Mandelbaum, R., and LSST Dark Energy Science Collaboration, MNRAS, 479, 1412 (2018) [arXiv][ADS]

Approximating Photo-z PDFs for Large Surveys, Malz, A. I., Marshall, P. J., DeRose, J., Graham, M. L., Schmidt, S. J., Wechsler, R., and LSST Dark Energy Science Collaboration, AJ, 156, 35 (2018) [arXiv][ADS]

DESCQA: An Automated Validation Framework for Synthetic Sky Catalogs, Mao, Y.-Y., Kovacs, E., Heitmann, K., Uram, T. D., Benson, A. J., Campbell, D., Cora, S. A., DeRose, J., Di Matteo, T., Habib, S., Hearin, A. P., Bryce Kalmbach, J., Krughoff, K. S., Lanusse, F., Lukić, Z., Mandelbaum, R., Newman, J. A., Padilla, N., Paillas, E., Pope, A., Ricker, P. M., Ruiz, A. N., Tenneti, A., Vega-Martínez, C. A., Wechsler, R. H., Zhou, R., Zu, Y., and LSST Dark Energy Science Collaboration, ApJS, 234, 36 (2018) [arXiv][ADS][Zenodo]

Released DESC Notes and White Papers

2021

DESC DC2 Data Release Note, LSST Dark Energy Science Collaboration, Abolfathi, B., Armstrong, R., Awan, H., Babuji, Y. N., Bauer, F. E., Beckett, G., Biswas, R., Bogart, J. R., Boutigny, D., Chard, K., Chiang, J., Cohen-Tanugi, J., Connolly, A. J., Daniel, S. F., Digel, S. W., Drlica-Wagner, A., Dubois, R., Gawiser, E., Glanzman, T., Habib, S., Hearin, A. P., Heitmann, K., Hernandez, F., Hložek, R., Hollowed, J., Jarvis, M., Jha, S. W., Bryce Kalmbach, J., Kelly, H. M., Kovacs, E., Korytov, D., Krughoff, K. S., Lage, C. S., Lanusse, F., Larsen, P., Li, N., Longley, E. P., Lupton, R. H., Mandelbaum, R., Mao, Y.-Y., Marshall, P., Meyers, J. E., Park, J. W., Peloton, J., Perrefort, D., Perry, J., Plaszczynski, S., Pope, A., Rykoff, E. S., Sánchez, F. J., Schmidt, S. J., Uram, T. D., Villarreal, A., Walter, C. W., Wiesner, M. P., and Wood-Vasey, W. M., arXiv:2101.04855 [ADS]

2020

Recommended Target Fields for Commissioning the Vera C. Rubin Observatory, Amon, A., Bechtol, K., Connolly, A. J., Digel, S. W., Drlica-Wagner, A., Gawiser, E., Jarvis, M., Jha, S. W., von der Linden, A., Moniez, M., Narayan, G., Regnault, N., Sevilla-Noarbe, I., Schmidt, S. J., Suyu, S. H., and Walter, C. W., arXiv:2010.15318 [ADS][Zenodo]

2019

Modified Gravity and Dark Energy models Beyond $w(z)$CDM Testable by LSST, Ishak, M., Baker, T., Bull, P., Pedersen, E. M., Blazek, J., Ferreira, P. G., Leonard, C. D., Lin, W., Linder, E., Pardo, K., and Valogiannis, G., arXiv:1905.09687 [ADS]

Single-object Imaging and Spectroscopy to Enhance Dark Energy Science from LSST, Hložek, R., Collett, T., Galbany, L., Goldstein, D. A., Jha, S. W., Kim, A. G., Newman, J. A., Perlmutter, S., Perrefort, D. J., Sullivan, M., Verma, A., and LSST Dark Energy Science Collaboration, arXiv:1903.09324 [ADS]

Wide-field Multi-object Spectroscopy to Enhance Dark Energy Science from LSST, Mandelbaum, R., Blazek, J., Chisari, N. E., Collett, T., Galbany, L., Gawiser, E., Hložek, R. A., Kim, A. G., Leonard, C. D., Lochner, M., Mandelbaum, R., Newman, J. A., Perrefort, D. J., Schmidt, S. J., Singh, S., Sullivan, M., and LSST Dark Energy Science Collaboration, arXiv:1903.09323 [ADS]

Deep Multi-object Spectroscopy to Enhance Dark Energy Science from LSST, Newman, J., Blazek, J., Chisari, N. E., Clowe, D., Dell’Antonio, I., Gawiser, E., Hložek, R. A., Kim, A. G., von der Linden, A., Lochner, M., Mandelbaum, R., Medezinski, E., Melchior, P., Newman, J. A., Sánchez, F. J., Schmidt, S. J., Singh, S., and LSST Dark Energy Science Collaboration, arXiv:1903.09325 [ADS]

Cosmological Synergies Enabled by Joint Analysis of Multi-probe data from WFIRST, Euclid, and LSST, Rhodes, J., Alonso, D., Ansarinejad, B., Armstrong, R., Asorey, J., Avelino, A., Blazek, J., Castander, F. J., Chary, R. R., Chen, X., Choi, A., Clowe, D., Cohen-Tanugi, J., Comparat, J., Croft, R. A. C., Doré, O., Escoffier, S., Foley, R., Fosalba, P., Gruen, D., Gupta, N., Guzzo, L., Hawken, A. J., Hemmati, S., Heitmann, K., Hernquist, L., Heymans, C., Hirata, C. M., Hoekstra, H., Huterer, D., Iliev, I. T., Jain, B., Jha, S. W., Keeley, R. E., Kiessling, A., Kitching, T., Koekemoer, A., Koushiappas, S. M., Kovetz, E. D., Kruk, J., L’Huillier, B., Lahav, O., Lemos, P., Macorra, A. de . la ., Malagón, A. P., Mandelbaum, R., Masters, D., McQuinn, M., Melchior, P., Miyatake, H., Newman, J. A., Nichol, R., Niz, G., O’Connor, P., Penna-Lima, M., Percival, W. J., Perlmutter, S., Pisani, A., Rigault, M., Rossi, G., Schmittfull, M., Schuhmann, R., Scolnic, D., Sereno, M., Shan, H., Shirasaki, M., Simon, S., Slosar, A., Spergel, D., Sridhar, S., Takada, M., Troxel, M. A., Wang, Y., Weinberg, D., Yoshida, N., Zhang, Y., and LSST Dark Energy Science Collaboration [ADS]

2018

Optimizing the LSST Observing Strategy for Dark Energy Science: DESC Recommendations for the Deep Drilling Fields and other Special Programs, Scolnic, D. M., Lochner, M., Gris, P., Regnault, N., Hložek, R., Aldering, G., Allam, T., Awan, H., Biswas, R., Blazek, J., Chang, C., Gawiser, E., Goobar, A., Hook, I. M., Jha, S. W., McEwen, J. D., Mandelbaum, R., Marshall, P., Neilsen, E., Rhodes, J., Rothchild, D., Sevilla Noarbe, I., Slosar, A., and Yoachim, P., arXiv:1812.00516 [ADS]

Optimizing the LSST Observing Strategy for Dark Energy Science: DESC Recommendations for the Wide-Fast-Deep Survey, Lochner, M., Scolnic, D. M., Awan, H., Regnault, N., Gris, P., Mandelbaum, R., Gawiser, E., Almoubayyed, H., Setzer, C. N., Huber, S., Graham, M. L., Hložek, R., Biswas, R., Eifler, T., Rothchild, D., Allam, T., Blazek, J., Chang, C., Collett, T., Goobar, A., Hook, I. M., Jarvis, M., Jha, S. W., Kim, A. G., Marshall, P., McEwen, J. D., Moniez, M., Newman, J. A., Peiris, H. V., Petrushevska, T., Rhodes, J., Sevilla-Noarbe, I., Slosar, A., Suyu, S. H., Tyson, J. A., and Yoachim, P., arXiv:1812.00515 [ADS]

The Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC): Data set, The PLAsTiCC team, Allam, T., Bahmanyar, A., Biswas, R., Dai, M., Galbany, L., Hložek, R., Ishida, E. E. O., Jha, S. W., Jones, D. O., Kessler, R., Lochner, M., Mahabal, A. A., Malz, A. I., Mandel, K. S., Martínez-Galarza, J. R., McEwen, J. D., Muthukrishna, D., Narayan, G., Peiris, H., Peters, C. M., Ponder, K., Setzer, C. N., LSST Dark Energy Science Collaboration, LSST Transients and Variable Stars Science Collaboration, arXiv:1810.00001 [ADS]

The LSST Dark Energy Science Collaboration (DESC) Science Requirements Document, The LSST Dark Energy Science Collaboration, Mandelbaum, R., Eifler, T., Hložek, R., Collett, T., Gawiser, E., Scolnic, D., Alonso, D., Awan, H., Biswas, R., Blazek, J., Burchat, P., Chisari, N. E., Dell’Antonio, I., Digel, S., Frieman, J., Goldstein, D. A., Hook, I., Ivezić, Ž., Kahn, S. M., Kamath, S., Kirkby, D., Kitching, T., Krause, E., Leget, P.-F., Marshall, P. J., Meyers, J., Miyatake, H., Newman, J. A., Nichol, R., Rykoff, E., Sanchez, F. J., Slosar, A., Sullivan, M., and Troxel, M. A., arXiv:1809.01669 [ADS][Zenodo]

2012

Large Synoptic Survey Telescope: Dark Energy Science Collaboration, LSST Dark Energy Science Collaboration, arXiv:1211.0310 [ADS]

PhD Theses by DESC Students

Below are PhD theses written by students in DESC and based at least partially on their work in DESC. The listed entries are self-reported by the authoring students and have been indexed by the ADS (instructions for member students).

2023

Building a comprehensive picture of stellar death for the era of synoptic surveys, Gagliano, A. [ADS]

Enabling Supernovae Cosmology with large time-domain surveys, Alves, C. S. [ADS]

2020

Cosmoparticle Constraints with Large-Scale Structure, Mahony, C. [ADS]

Probing Dark Energy with Large Galaxy Surveys: Systematics Quantification & Mitigation, Awan, H. [ADS]

Challenges for Dark Energy Science: Color Gradients and Blended Objects, Kamath, S. [ADS]

Released DESC Data Products

Released products are collected in the following sites.

Also, some DESC publications may release software and/or data products from locations (e.g., GitHub) specified directly in the paper text.