Photometric Redshifts with the LSST: Evaluating Survey Observing Strategies
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In this paper we present and characterize a nearest-neighbors color-matching photometric redshift estimator that features a direct relationship between the precision and accuracy of the input magnitudes and the output photometric redshifts. This aspect makes our estimator an ideal tool for evaluating the impact of changes to LSST survey parameters that affect the measurement errors of the photometry, which is the main motivation of our work (i.e., it is not intended to provide the “best” photometric redshifts for LSST data). We show how the photometric redshifts will improve with time over the 10 year LSST survey and confirm that the nominal distribution of visits per filter provides the most accurate photo-z results. The LSST survey strategy naturally produces observations over a range of airmass, which offers the opportunity of using an SED- and z-dependent atmospheric affect on the observed photometry as a color-independent redshift indicator. We show that measuring this airmass effect and including it as a prior has the potential to improve the photometric redshifts and can ameliorate extreme outliers, but that it will only be adequately measured for the brightest galaxies, which limits its overall impact on LSST photometric redshifts. We furthermore demonstrate how this airmass effect can induce a bias in the photo-z results, and caution against survey strategies that prioritize high-airmass observations for the purpose of improving this prior. Ultimately, we intend for this work to serve as a guide for the expectations and preparations of the LSST science community with regard to the minimum quality of photo-z as the survey progresses.
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Requiring more training data than currently exists to define the template set degrades the expected σ/(1+z) to about 0.05, which is still within the expected range for a Stage IV dark energy experiment.
“The degradation in photometric redshift quality associated with requiring more training data than currently exists to de fi ne the template set increases the expected σ / ( 1 + z ) to ∼ 0.05 ( e.g., Newman et al. 2015; Graham et al. 2018 ) , which is still well within the expected range for a Stage IV dark energy experiment.”
From LSST: From Science Drivers to Reference Design and Anticipated Data Products (2019) · cites this paper as Graham et al. 2018
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Crenshaw, J. F., Leistedt, B., Graham, M. L., Payerne, C., Connolly, A. J., Gawiser, E., Karim, T., Malz, A. I., Newman, J. A., & Ricci, M. (2025) · The Astrophysical Journal Supplement Series · doi:10.3847/1538-4365/ae14f0 · Cited by 4 · see citing works
Self-citationHang, Q., Joachimi, B., Charles, E., Crenshaw, J. F., Larsen, P., Malz, A. I., Schmidt, S., Yan, Z., Zhang, T., Leistedt, B., et al. (2024) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stae2519 · Cited by 4 · see citing works
Self-citationOptimising the design of phased array feeds for survey speed
Chen, K., & Warnick, K. F. (2019) · Electronics Letters · doi:10.1049/el.2019.2591 · Cited by 4 · see citing works
The Impact of Host-galaxy Properties on Supernova Classification with Hierarchical Labels
Villar, V. A., Gómez, S., Berger, E., & Gagliano, A. T. (2024) · The Astrophysical Journal Supplement Series · doi:10.3847/1538-4365/ad8a5b · Cited by 3 · see citing works
Dennis, M. T., Hu, E. M., & Cowie, L. L. (2025) · The Astrophysical Journal · doi:10.3847/1538-4357/adbe62 · Cited by 3 · see citing works
Weak lensing mass-richness relation of redMaPPer clusters in LSST DESC DC2 simulations
Payerne, C., Zhang, Z., Aguena, M., Combet, C., Guillemin, T., Ricci, M., Amouroux, N., Avestruz, C., Barroso, E. J., Farahi, A., et al. (2025) · Astronomy and Astrophysics · doi:10.1051/0004-6361/202554107 · Cited by 3 · see citing works
Self-citationWood‐Vasey, W. M., Perrefort, D., & Baker, A. (2022) · The Astronomical Journal · doi:10.3847/1538-3881/ac63bb · Cited by 3 · see citing works
Inhomogeneous Dust Biases Photometric Redshifts and Stellar Masses for LSST
Hahn, C., & Melchior, P. (2025) · The Astrophysical Journal Letters · doi:10.3847/2041-8213/adbe5e · Cited by 3 · see citing works
Conceptual Design for Deflecting a Potentially Hazardous Asteroid with a Space Duster
Santos, R., Xu, M., Zheng, Y., He, X., & Ge, J. (2021) · Journal of Spacecraft and Rockets · doi:10.2514/1.a34903 · Cited by 3 · see citing works
Photometric Redshift Forecast for the 7-Dimensional Sky Survey
고, E. 은. K., Im, M., Yang, Y., Kim, J. H., Lee, S.-K., & Paek, G. S. H. (2025) · The Astrophysical Journal · doi:10.3847/1538-4357/ae0cb8 · Cited by 2 · see citing works
Euclid : Field-level inference of primordial non-Gaussianity and cosmic initial conditions
Andrews, A. A., Jasche, J., Lavaux, G., Leclercq, F., Finelli, F., Akrami, Y., Ballardini, M., Karagiannis, D., Väliviita, J., Bartolo, N., et al. (2026) · Astronomy and Astrophysics · doi:10.1051/0004-6361/202553802 · Cited by 2 · see citing works
AMPEL workflows for LSST: Modular and reproducible real-time photometric classification
Nordin, J., Brinnel, V., Santen, J. V., Reusch, S., & Kowalski, M. P. (2025) · Astronomy and Astrophysics · doi:10.1051/0004-6361/202452481 · Cited by 2 · see citing works
Scott, B. R., Malz, A. I., & Sorba, R. (2025) · The Astrophysical Journal · doi:10.3847/1538-4357/adc995 · Cited by 2 · see citing works
Photometric redshift estimation with a convolutional neural network: NetZ
Schuldt, S., Suyu, S. H., Cañameras, R., Taubenberger, S., Meinhardt, T., Leal-Taixé, L., & Hsieh, B.-C. (2021) · Springer Link (Chiba Institute of Technology) · doi:10.1051/0004-6361/202039945/pdf · Cited by 2 · see citing works
William, A. J., Jalan, P., Bilicki, M., Hellwing, W. A., Thuruthipilly, H., & Nakoneczny, S. J. (2025) · Astronomy and Astrophysics · doi:10.1051/0004-6361/202453576 · Cited by 1 · see citing works
Imaging systematics induced by galaxy subsample fluctuation: New systematics at second order
Kong, H., Chisari, N. E., Leistedt, B., Gawiser, E., Rodríguez-Monroy, M., & Weaverdyck, N. (2026) · Physical review. D/Physical review. D. · doi:10.1103/7n6p-t5nh · Cited by 1 · see citing works
Yoo, J., Gyure, C., Agarwal, V., Singal, J., & Silverman, G. (2026) · The Astrophysical Journal · doi:10.3847/1538-4357/ae317b · Cited by 1 · see citing works
Wide-field Multi-object Spectroscopy to Enhance Dark Energy Science from LSSTPreprint
Newman, J. A., Blazek, J., Chisari, N. E., Clowe, D., Dell’Antonio, I., Gawiser, E., Hložek, R., Kim, A., von der Linden, A., Lochner, M., et al. (2019) · arXiv (Cornell University) · Cited by 1 · see citing works
Self-citationMini-survey of the northern sky to DecPreprint
Capak, P. L., Sconlic, D., Cuillandre, J., Castander, F. J., Bolton, A. S., Bowler, R. A. A., Chang, C., Dey, A., Eifler, T. F., Eisenstein, D. J., et al. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1904.10438 · Cited by 1 · see citing works
Ivezić, Ž. (2016) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.44697
Self-citationLarge Synoptic Survey Telescope Town Hall
Willman, B. (2016) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.44768
The Lsst Data Processing Software Stack
Jenness, T. (2016) · American Astronomical Society Meeting Abstracts #227 · doi:10.5281/zenodo.44634
Protocluster Detection in Mock Photometric Surveys
Araya, P. A. A. (2020) · doi:10.11606/d.14.2020.tde-22062022-153622
GLASS: Generator for Large Scale Structure
Tessore, N., Loureiro, A., Joachimi, B., von Wietersheim-Kramsta, M., & Jeffrey, N. (2023) · The Open Journal of Astrophysics · doi:10.21105/astro.23002.01942
Recovered supernova Ia rate from simulated LSST images
Petrecca, V., Botticella, M. T., Cappellaro, E., Greggio, L., Sánchez, B., Möller, A., Sako, M., Graham, M. L., Paolillo, M., & Bianco, F. B. (2024) · Springer Link (Chiba Institute of Technology) · doi:10.1051/0004-6361/202349012/pdf
Self-citationGarcia-Fernandez, M. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-08462-0_6
SITCOMTN-154: Initial studies of photometric redshifts with LSSTComCam from DP1
Charles, E., Crenshaw, J. F., Zhang, T., Schmidt, S. J., Adari, P., Cohen-Tanugi, J., Graham, M. L., Gschwend, J., Kalmbach, J. B., Kannawadi, A., et al. (2025) · DOE SLAC National Accelerator Laboratory Repository · doi:10.71929/rubin/2571480
Self-citationMalz, A. I., Lanusse, F., Crenshaw, J. F., Scott, B. R., & Graham, M. L. (2026) · The Astrophysical Journal Supplement Series · doi:10.3847/1538-4365/ad7d07
Self-citationOptimizing Deep Learning Photometric Redshifts for the Roman Space Telescope with HST/CANDELS
Khederlarian, A., Andrews, B. H., Newman, J. A., Zhang, T., & Dey, B. (2026) · The Astronomical Journal · doi:10.3847/1538-3881/ae5dc4
Simulation-based cosmological inference from optically selected galaxy clusters with Capish
Payerne, C., Murray, C., & Simon, H. (2026) · Astronomy and Astrophysics · doi:10.1051/0004-6361/202659338
Enhancing photometric redshift estimation for LSST with a hybrid LSTM-mixture density network
Luo, Z., Li, Y., Luo, X., Xiao, H., Fang, W., Pei, W., Zhang, S., & Shu, C. (2026) · Astronomy and Astrophysics · doi:10.1051/0004-6361/202660374
- Authors
- Graham, M. L., Connolly, A. J., Ivezić, Ž., Schmidt, S. J., Jones, R. L., Jurić, M., Daniel, S. F., & Yoachim, P.
- Affiliations
- University of Washington (US)
- University of California, Davis (US)
- Venue
- The Astronomical Journal
- Publisher
- American Astronomical Society
- Published
- 2017-12-07
- Volume
- 155
- Issue
- 1
- Pages
- 1
- ISSN
- 0004-6256 (ISSN-L)
- 1538-3881
- OpenAlex
- W2732984264
- Cited by
- 95
- References
- 11
- Citations by year
- 2026: 7 · 2025: 11 · 2024: 10 · 2023: 10 · 2022: 7 · 2021: 14 · 2020: 16 · 2019: 14 · 2018: 3 · 2016: 3
- FWCI
- 4.94
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- The Astronomical Journal (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- National Science Foundation (1258333, DE-AC02-76SF00515)
- U.S. Department of Energy (76SF00515, DE–AC02–76SF00515, AC02‐76SF00515, DESC0011635, DE-AC02-)
- Washington Research Foundation
- University of Washington
- Office of Science (AC02-76SF00515, DE-AC02, 76SF00515)
- SLAC National Accelerator Laboratory (DEAC02−76SF00515, AC02‐76SF00515)
- Topics
- Physical Sciences › Physics and Astronomy › Astronomy and Astrophysics › Galaxies: Formation, Evolution, Phenomena
- Physical Sciences › Physics and Astronomy › Instrumentation › Astronomy and Astrophysical Research
- Physical Sciences › Physics and Astronomy › Astronomy and Astrophysics › Stellar, planetary, and galactic studies
- Keywords
- photometric redshifts, spectral energy distribution, photometric redshift bias
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