Table 2.
Calibration parameters with their priors for the Monte Carlo marginalization of the WL bias and scatter determination.
| Cluster member contamination (Sect. 3.3.1) | |
|---|---|
| log10c = 4.83 ± 0.22 | Bcl = 0.467 ± 0.017 |
| lnσreg = −0.61 ± 0.43 | A0 = −4.75 ± 0.11 |
| A1 = −4.38 ± 0.05 | A2 = −3.68 ± 0.04 |
| A3 = −3.25 ± 0.04 | A4 = −3.04 ± 0.04 |
| Mis-centering parameters (Sect. 4.2) | |
| σ0[arcsec] = 4.83 ± 0.22 | k = 0.308 ± 0.007 |
| α = 0.443 ± 0.012 | lnf = −0.76 ± 0.11 |
| lnβ = −0.18 ± 0.04 | σintr = 0.104 ± 0.016 |
| lnλ = −0.18 ± 0.04 | |
| Richness mass relation (Chiu et al. 2022, Appendix A) | |
| Aλ = 36.2 ± 3.6 | Bλ = 0.881 ± 0.083 |
| Cλ = −0.46 ± 0.52 | σλ = 0.274 ± 0.066 |
| Photo-z and shape calibrations | |
| ℋ ∼ Int(0, 999) ( * ) | αNL = 0.6 ± 0.4 ( † ) |
| Hydrodynamical modeling uncertainties | |
| Δb = 0.02, ΔbM = 0.018 | Δs = 0.25, ΔsM = 0.59 |
Notes. Note that the parameters for the cluster member contamination and the mis-centering are actually drawn from the respective posterior fits to conserve correlations among the parameters. ( * )Int(a, b) is a uniform distribution over the integers a ≤ i ≤ b (cf. Sect. 3.3.2); ( † )nonlinear multiplicative shear bias (Grandis et al. 2021a, Sect. 2.1.7).
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