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Forecasting the potential of weak lensing magnification to enhance LSST large-scale structure analyses.
- Source :
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Monthly Notices of the Royal Astronomical Society . 6/15/2022, Vol. 513 Issue 1, p1210-1228. 19p. - Publication Year :
- 2022
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Abstract
- Recent works have shown that weak lensing magnification must be included in upcoming large-scale structure analyses, such as for the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), to avoid biasing the cosmological results. In this work, we investigate whether including magnification has a positive impact on the precision of the cosmological constraints, as well as being necessary to avoid bias. We forecast this using an LSST mock catalogue and a halo model to calculate the galaxy power spectra. We find that including magnification has little effect on the precision of the cosmological parameter constraints for an LSST galaxy clustering analysis, where the halo model parameters are additionally constrained by the galaxy luminosity function. In particular, we find that for the LSST gold sample (i < 25.3) including weak lensing magnification only improves the galaxy clustering constraint on Ωm by a factor of 1.03, and when using a very deep LSST mock sample (i < 26.5) by a factor of 1.3. Since magnification predominantly contributes to the clustering measurement and provides similar information to that of cosmic shear, this improvement would be reduced for a combined galaxy clustering and shear analysis. We also confirm that not modelling weak lensing magnification will catastrophically bias the cosmological results from LSST. Magnification must therefore be included in LSST large-scale structure analyses even though it does not significantly enhance the precision of the cosmological constraints. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00358711
- Volume :
- 513
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- Monthly Notices of the Royal Astronomical Society
- Publication Type :
- Academic Journal
- Accession number :
- 156800794
- Full Text :
- https://doi.org/10.1093/mnras/stac872