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The Impact of Magnification and Size Bias on Weak Lensing Power Spectrum and Peak Statistics

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arxiv 1310.7517 v1 pith:DVAFUHOO submitted 2013-10-28 astro-ph.CO

The Impact of Magnification and Size Bias on Weak Lensing Power Spectrum and Peak Statistics

classification astro-ph.CO
keywords powerspectrumcountspeaksigmalensingbiasescosmological
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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The weak lensing power spectrum is a powerful tool to probe cosmological parameters. Additionally, lensing peak counts contain cosmological information beyond the power spectrum. Both of these statistics can be affected by the preferential selection of source galaxies in patches of the sky with high magnification, as well as by the dilution in the source galaxy surface density in such regions. If not accounted for, these biases introduce systematic errors for cosmological measurements. Here we quantify these systematic errors, using convergence maps from a suite of ray-tracing N-body simulations. At the cut-off magnitude m of on-going and planned major weak lensing surveys, the logarithmic slope of the cumulative number counts s = dlog[n(>m)]/dlog(m) is in the range 0.1 < s < 0.5. At s = 0.2, expected in the I band for LSST, the inferred values of Omega_m, w and sigma_8 are biased by many sigma (where sigma denotes the marginalized error) and therefore the biases will need to be carefully modeled. We also find that the parameters are biased differently in the (Omega_m, w, sigma_8) parameter space when the power spectrum and when the peak counts are used. In particular, w derived from the power spectrum is less affected than w derived from peak counts, while the opposite is true for the best-constrained combination of [sigma_8 Omega_m^gamma] (with gamma=0.62 from the power spectrum and gamma = 0.48 from peak counts). This suggests that the combination of the power spectrum and peak counts can help mitigate the impact of magnification and size biases.

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Cited by 2 Pith papers

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  1. Cosmological constraining power of the redshifts, heights, and angular clustering of weak gravitational lensing peaks

    astro-ph.CO 2026-07 conditional novelty 5.0

    In an idealized Euclid-like simulation forecast, the combined redshift distribution, height distribution, and angular clustering of weak-lensing peaks constrain cosmology better than shear two-point correlation functi...

  2. Machine-learning applications for weak-lensing cosmology

    astro-ph.CO 2026-05 unverdicted novelty 2.0

    Machine learning techniques can mitigate limitations in traditional weak-lensing analyses and enhance extraction of cosmological information from galaxy imaging surveys.