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The effective number density of galaxies for weak lensing measurements in the LSST project
Open accessAbstract
Future weak lensing surveys potentially hold the highest statistical power for constraining cosmological parameters compared to other cosmological probes. The statistical power of a weak lensing survey is determined by the sky coverage, the inverse of the noise in shear measurements and the galaxy number density. The combination of the latter two factors is often expressed in terms of neff – the ‘effective number density of galaxies used for weak lensing measurements’. In this work, we estimate neff for the Large Synoptic Survey Telescope (LSST) project, the most powerful ground-based lensing survey planned for the next two decades. We investigate how the following factors affect the resulting neff of the survey with detailed simulations: (1) survey time, (2) shear measurement algorithm, (3) algorithm for combining multiple exposures, (4) inclusion of data from multiple filter bands, (5) redshift distribution of the galaxies and (6) masking and blending. For the first time, we quantify in a general weak lensing analysis pipeline the sensitivity of neff to the above factors. We find that with current weak lensing algorithms, expected distributions of observing parameters, and all lensing data (r and i band, covering 18 000 degree2 of sky) for LSST, neff ≈ 37 arcmin−2 before considering blending and masking, neff ≈ 31 arcmin−2 when rejecting seriously blended galaxies and neff ≈ 26 arcmin−2 when considering an additional 15 per cent loss of galaxies due to masking. With future improvements in weak lensing algorithms, these values could be expected to increase by up to 20 per cent. Throughout the paper, we also stress the ways in which neff depends on our ability to understand and control systematic effects in the measurements.
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Simulations of the formation, evolution and clustering of galaxies and quasars
Springel, V., White, S. D. M., Jenkins, A. R., Frenk, C. S., Yoshida, N., Gao, L., Navarro, J. F., Thacker, R. J., Croton, D., Helly, J. C., et al. (2005) · Nature · doi:10.1038/nature03597 · Cited by 5,060
LSST: from Science Drivers to Reference Design and Anticipated Data Products
Ivezić, Ž., Kahn, S. M., Tyson, J. A., Abel, B., Acosta, E., Allsman, R., Alonso, D., AlSayyad, Y., Anderson, S. F., Andrew, J., et al. (2008) · arXiv · doi:10.48550/arxiv.0805.2366 · Cited by 4,357
Self-citationBartelmann, M., & Schneider, P. (2001) · Physics Reports · doi:10.1016/s0370-1573(00)00082-x · Cited by 2,611
A Direct Empirical Proof of the Existence of Dark Matter
Clowe, D., Bradač, M., Gonzalez, A. H., Markevitch, M., Randall, S. W., Jones, C., & Zaritsky, D. (2006) · The Astrophysical Journal · doi:10.1086/508162 · Cited by 2,470
Photometry of a complete sample of faint galaxies
Kron, R. G. (1980) · The Astrophysical Journal Supplement Series · doi:10.1086/190669 · Cited by 1,054
The formation history of elliptical galaxies
Lucia, G. D., Springel, V., White, S. D. M., Croton, D., & Kauffmann, G. (2006) · Monthly Notices of the Royal Astronomical Society · doi:10.1111/j.1365-2966.2005.09879.x · Cited by 1,008
A Method for Weak Lensing Observations
Kaiser, N., Squires, G. K., & Broadhurst, T. J. (1995) · The Astrophysical Journal · doi:10.1086/176071 · Cited by 792
CFHTLenS: the Canada–France–Hawaii Telescope Lensing Survey
Heymans, C., Waerbeke, L. V., Miller, L., Erben, T., Hildebrandt, H., Hoekstra, H., Kitching, T., Mellier, Y., Simon, P., Bonnett, C., et al. (2012) · Monthly Notices of the Royal Astronomical Society · doi:10.1111/j.1365-2966.2012.21952.x · Cited by 718
Heymans, C., Grocutt, E., Heavens, A., Kilbinger, M., Kitching, T. D., Simpson, F., Benjamin, J., Erben, T., Hildebrandt, H., Hoekstra, H., et al. (2013) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stt601 · Cited by 649
The Milky Way Tomography with SDSS. II. Stellar Metallicity
Ivezić, Ž., Sesar, B., Jurić, M., Bond, N., Dalcanton, J., Rockosi, C. M., Yanny, B., Newberg, H. J., Beers, T. C., Allende Prieto, C., et al. (2008) · The Astrophysical Journal · doi:10.1086/589678 · Cited by 566
Research works printed but not linked: 2
- 1996, AAS, 117, 393
- 2008, J COSMOL ASTROPART PHYS, 1, 3
Cited by
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Secco, L. F., Samuroff, S., Krause, E., Jain, B., Blazek, J., Raveri, M., Campos, A., Amon, A., Chen, A., Doux, C., et al. (2022) · Physical review. D/Physical review. D. · doi:10.1103/physrevd.105.023515 · Cited by 388
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Cosmological constraints from noisy convergence maps through deep learning
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Li, X., Miyatake, H., Luo, W., More, S., Oguri, M., Hamana, T., Mandelbaum, R., Shirasaki, M., Takada, M., Armstrong, R., et al. (2022) · Publications of the Astronomical Society of Japan · doi:10.1093/pasj/psac006 · Cited by 83
Harnois-Déraps, J., Martinet, N., Castro, T., Dolag, K., Giblin, B., Heymans, C., Hildebrandt, H., & Xia, Q. (2020) · Monthly notices of the Royal Astronomical Society · doi:10.1093/mnras/stab1623 · Cited by 38
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Harnois-Déraps, J., Amon, A., Choi, A., Demchenko, V., Heymans, C., Kannawadi, A., Nakajima, R., Sirks, E., Waerbeke, L. V., Cai, Y.-C., et al. (2018) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/sty2319 · Cited by 77
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Sifón, C., Cacciato, M., Hoekstra, H., Brouwer, M. M., van Uitert, E., Viola, M. G., Baldry, I. K., Brough, S., Brown, M. J. I., Choi, A., et al. (2015) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stv2051 · Cited by 60
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Marques, G. A., Liu, J., Shirasaki, M., Thiele, L., Grandón, D., Huffenberger, K. M., Cheng, S., Harnois-Déraps, J., Osato, K., & Coulton, W. R. (2024) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stae098 · Cited by 39
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Moriwaki, K., Nishimichi, T., & Yoshida, N. (2023) · Reports on Progress in Physics · doi:10.1088/1361-6633/acd2ea · Cited by 52
Strongly lensed gravitational waves and electromagnetic signals as powerful cosmic rulers
Wei, J.-J., & Wu, X.-F. (2017) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stx2210 · Cited by 35
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Amon, A., Heymans, C., Klaes, D., Erben, T., Blake, C., Hildebrandt, H., Hoekstra, H., Kuijken, K. H., Miller, L., Morrison, C., et al. (2018) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/sty859 · Cited by 33
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Joseph, R., Courbin, F., & Starck, J.-L. (2016) · Astronomy and Astrophysics · doi:10.1051/0004-6361/201527923 · Cited by 31
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Joseph, R., Courbin, F., & Starck, J. (2016) · Springer Link (Chiba Institute of Technology) · doi:10.1051/0004-6361/201527923/pdf · Cited by 26
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Metadata
- Authors
- Chang, C., Jarvis, M., Jain, B., Kahn, S. M., Kirkby, D., Connolly, A., Krughoff, S., Peng, E. H., & Peterson, J. R.
- Affiliations
- Kavli Institute for Particle Astrophysics and Cosmology (US)
- University of Pennsylvania (US)
- University of California, Irvine (US)
- University of Washington (US)
- Purdue University West Lafayette (US)
- Venue
- Monthly Notices of the Royal Astronomical Society
- Publisher
- Oxford University Press (OUP)
- Published
- 2013-07-19
- Volume
- 434
- Issue
- 3
- Pages
- 2121-2135
- ISSN
- 0035-8711 (ISSN-L)
- 1365-2966
- OpenAlex
- W2023217969
- Cited by
- 164
- References
- 49
- Citations by year
- 2026: 11 · 2025: 14 · 2024: 13 · 2023: 10 · 2022: 13 · 2021: 11 · 2020: 12 · 2019: 16 · 2018: 22 · 2017: 8 · 2016: 15 · 2015: 14 · 2014: 5
- FWCI
- 6.12
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Monthly Notices of the Royal Astronomical Society (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- National Science Foundation (DE-SC0007901, 0809409)
- U.S. Department of Energy (DE-AC02-76-SFO0515, DESC0007901, DE-AC02-)
- SLAC National Accelerator Laboratory
- Topics
- Physical Sciences › Physics and Astronomy › Astronomy and Astrophysics › Cosmology and Gravitation Theories
- Physical Sciences › Physics and Astronomy › Astronomy and Astrophysics › Galaxies: Formation, Evolution, Phenomena
- Physical Sciences › Physics and Astronomy › Instrumentation › Astronomy and Astrophysical Research
- Keywords
- weak gravitational lensing, LSST, shear measurement, galaxy blending, redshift distribution, multi-band imaging, cosmological parameter constraints, statistical power, systematic effects
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