SS
Samuel Schmidt
astro-ph.COastro-ph.IMastro-ph.GAastro-phastro-ph.EPastro-ph.SR
On Valency
published · living versionsW_qpybb2aj·v1 · currentpublished
Science-Driven Optimization of the LSST Observing Strategy
with LSST Science Collaboration, Phil Marshall, Timo Anguita, Federica B. Bianco +100
1 version
W_abqvzdsw·v1published
W_h5sfkehb·v1published
W_tgdkrgdv·v1published
W_uvncea8u·v1published
Preprints & journals
40 papers in the corpus · 2006–2026The Vera C. Rubin Observatory Data Preview 12603.23786v1 · Tatiana Acero Cuellar, Emily Acosta, Christina L Adair et al.2026 · 5 citationsarXiv
Diagnosing the Effects of Spectroscopic Training Set Imperfection on Photometric Redshift Performance2601.10797v1 · Alice Crafford, Alex I. Malz, Tianqing Zhang et al.2026 · 0 citationsarXiv
Photometric Redshift Estimation for Rubin Observatory Data Preview 1 with Redshift Assessment Infrastructure Layers (RAIL)2510.07370v1 · T. Zhang, E. Charles, J.F. Crenshaw et al.2025 · 2 citationsMon Not R Astron Soc (2026)
NSF-DOE Vera C. Rubin Observatory Observations of Interstellar Comet 3I/ATLAS (C/2025 N1)2507.13409v3 · Colin Orion Chandler, Pedro H. Bernardinelli, Mario Juri'c et al.2025 · 9 citationsarXiv
Redshift Assessment Infrastructure Layers (RAIL): Rubin-era photometric redshift stress-testing and at-scale production2505.02928v5 · The RAIL Team, Jan Luca van den Busch, Eric Charles et al.2025 · 4 citationsarXiv
Weak lensing mass-richness relation of redMaPPer clusters in the LSST DESC DC2 simulations2502.08444v2 · Constantin Payerne, Zhuowen Zhang, Michel Aguena et al.2025 · 3 citationsA&A 700, A34 (2025)
DeepDISC-photoz: Deep Learning-Based Photometric Redshift Estimation for Rubin LSST2411.18769v2 · Grant Merz, Xin Liu, Samuel Schmidt et al.2024 · 7 citationsarXiv
Probabilistic Forward Modeling of Galaxy Catalogs with Normalizing Flows2405.04740v1 · John Franklin Crenshaw, J. Bryce Kalmbach, Alexander Gagliano et al.2024 · 22 citationsAJ 168 80 (2024)
Improving Photometric Redshift Estimates with Training Sample Augmentation2402.15551v2 · Irene Moskowitz, Eric Gawiser, John Franklin Crenshaw et al.2024 · 12 citationsApJL 967 L6 (2024)
Galaxy blending effects in deep imaging cosmic shear probes of cosmology2112.07659v2 · Erfan Nourbakhsh, J. Anthony Tyson, Samuel J. Schmidt2021 · 13 citationsMNRAS, 514, 5905 (2022)
Forecasting the potential of weak lensing magnification to enhance LSST large-scale structure analyses2112.01545v2 · Constance Mahony, Maria Cristina Fortuna, Benjamin Joachimi et al.2021 · 18 citationsarXiv
Validating Synthetic Galaxy Catalogs for Dark Energy Science in the LSST Era2110.03769v2 · Eve Kovacs, Yao-Yuan Mao, Michel Aguena et al.2021 · 19 citationsarXiv
The Impact of Tomographic Redshift Bin Width Errors on Cosmological Probes2104.03407v1 · Imran Hasan, Samuel J. Schmidt, Michael D. Schneider et al.2021 · 6 citationsarXiv
DESC DC2 Data Release Note2101.04855v5 · Bela Abolfathi, Robert Armstrong, Humna Awan et al.2021 · 8 citationsarXiv
A Composite Likelihood Approach for Inference under Photometric Redshift Uncertainty2101.01184v2 · M. M. Rau, C. B. Morrison, S. J. Schmidt et al.2021 · 18 citationsarXiv
Recommended Target Fields for Commissioning the Vera C. Rubin Observatory2010.15318v1 · A. Amon, K. Bechtol, A.J. Connolly et al.2020 · 1 citationarXiv
Blending and obscuration in weak lensing magnification2003.01047v2 · E.Gaztanaga, S.J.Schmidt, M.D.Schneider et al.2020 · 4 citationsarXiv
Evaluation of probabilistic photometric redshift estimation approaches for The Rubin Observatory Legacy Survey of Space and Time (LSST)2001.03621v2 · S.J. Schmidt, A.I. Malz, J.Y.H. Soo et al.2020 · 78 citationsMNRAS 499 2 1587 (2020)
Wide-field Multi-object Spectroscopy to Enhance Dark Energy Science from LSST1903.09323v1 · Rachel Mandelbaum, Jonathan Blazek, Nora Elisa Chisari et al.2019 · 5 citationsarXiv
Deep Multi-object Spectroscopy to Enhance Dark Energy Science from LSST1903.09325v1 · Jeffrey A. Newman, Jonathan Blazek, Nora Elisa Chisari et al.2019 · 4 citationsarXiv
Constraints on Cosmology and Baryonic Feedback with the Deep Lens Survey Using Galaxy-Galaxy and Galaxy-Mass Power Spectra1807.09195v4 · Mijin Yoon, M. James Jee, J. Anthony Tyson et al.2018 · 26 citationsarXiv
Estimating Sky Level1805.06711v3 · Inchan Ji, Imran Hasan, Samuel J. Schmidt et al.2018 · 13 citationsarXiv
Science-Driven Optimization of the LSST Observing Strategy1708.04058v1 · LSST Science Collaborations: Phil Marshall, Timo Anguita, Federica B. Bianco et al.2017 · 115 citationsarXivon Valency
Large Synoptic Survey Telescope Galaxies Science Roadmap1708.01617v1 · Brant E. Robertson, Manda Banerji, Michael C. Cooper et al.2017 · 14 citationsarXivon Valency
Star Formation In The Cluster Merger DLSCL J0916.2+29531611.07040v1 · A. S. Mansheim, B. C. Lemaux, W. A. Dawson et al.2016 · 10 citationsarXiv
The-wiZZ: Clustering redshift estimation for everyone1609.09085v2 · Christopher B. Morrison, Hendrik Hildebrandt, Samuel J. Schmidt et al.2016 · 72 citationsarXiv
Exploring the SDSS Photometric Galaxies with Clustering Redshifts1512.03057v2 · Mubdi Rahman, Alexander J. Mendez, Brice M'enard et al.2015 · 39 citationsarXiv
Mapping the Galaxy Color-Redshift Relation: Optimal Photometric Redshift Calibration Strategies for Cosmology Surveys1509.03318v1 · Daniel Masters, Peter Capak, Daniel Stern et al.2015 · 204 citationsarXiv
Spectroscopic Needs for Training of LSST Photometric Redshifts1410.4498v1 · Alexandra Abate, Jeffrey A. Newman, Samuel J. Schmidt et al.2014 · 0 citationsarXiv
Spectroscopic Needs for Calibration of LSST Photometric Redshifts1410.4506v1 · Samuel J. Schmidt, Jeffrey A. Newman, Alexandra Abate et al.2014 · 2 citationsarXiv
Clustering-based Redshift Estimation: Comparison to Spectroscopic Redshifts1407.7860v1 · Mubdi Rahman, Brice M'enard, Ryan Scranton et al.2014 · 65 citationsarXivon Valency
Inferring the Redshift Distribution of the Cosmic Infrared Background1407.0031v2 · Samuel J. Schmidt, Brice M'enard, Ryan Scranton et al.2014 · 52 citationsMonthly Notices of the Royal Astronomical Society 2014 446 (1): 2696-2708
Spectroscopic Needs for Imaging Dark Energy Experiments: Photometric Redshift Training and Calibration1309.5384v1 · J. Newman, A. Abate, F. Abdalla et al.2013 · 95 citationsarXiv
Clustering-based redshift estimation: method and application to data1303.4722v2 · Brice M'enard, Ryan Scranton, Samuel Schmidt et al.2013 · 93 citationsarXiv
Recovering Redshift Distributions with Cross-Correlations: Pushing The Boundaries1303.0292v1 · Samuel Schmidt, Brice M'enard, Ryan Scranton et al.2013 · 98 citationsarXiv
Galaxy-Mass Correlations on 10 Mpc Scales in the Deep Lens Survey1208.3904v1 · Ami Choi, J. Anthony Tyson, Chris B. Morrison et al.2012 · 23 citationsarXiv
Discovery of a Dissociative Galaxy Cluster Merger with Large Physical Separation1110.4391v2 · William A. Dawson, David Wittman, Myungkook Jee et al.2011 · 135 citations2012 ApJ 747 L42on Valency
Exploring Dark Energy with Next-Generation Photometric Redshift Surveys0902.2599v1 · Hu Zhan, Andreas Albrecht, Asantha Cooray et al.2009 · 1 citationarXiv
The Phoenix Deep Survey: Extremely Red Galaxies and Cluster Candidates0804.3866v1 · Anthony G. Smith, Andrew M. Hopkins, Richard W. Hunstead et al.2008 · 2 citationsAstron.J. 136 (2008) 358-366
The DRaGONS Survey: A Search for High Redshift Radio Galaxies And Heavily Obscured AGNsastro-ph/0606323v1 · S. J. Schmidt, A. J. Connolly, A. M. Hopkins2006 · 14 citationsAstrophys.J.649:63-78,2006
Career total: 66 works. 40 are in this corpus.
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