KiDS-Legacy: Redshift distributions and their calibration

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Table 7.

Parameters and goodness of fit obtained from CC analyses.

Dataset	Fit model		Tomographic Bin
			1	2	3	4	5	6
		D_z	0.000 ± 0.007	0.028 ± 0.006	0.021 ± 0.006	0.035 ± 0.010	−0.018 ± 0.028	−0.145 ± 0.091
Data	SOM n(z)	f	0.06 ± 0.03	0.10 ± 0.03	0.08 ± 0.03	0.06 ± 0.03	0.07 ± 0.03	0.07 ± 0.04
Data	SOM n(z)	χ²_dof	1.44	1.04	1.11	1.03	1.04	1.14

		⟨D_z⟩	0.003 ± 0.005	0.002 ± 0.005	0.005 ± 0.005	−0.004 ± 0.007	−0.008 ± 0.017	−0.015 ± 0.044
	True n(z)	⟨f⟩	0.10 ± 0.02	0.12 ± 0.04	0.11 ± 0.03	0.09 ± 0.03	0.07 ± 0.03	0.09 ± 0.03
MICE2 realisations	True n(z)	⟨χ_dof²⟩	0.99 ± 0.08	1.01 ± 0.09	1.02 ± 0.10	1.04 ± 0.12	0.96 ± 0.14	0.98 ± 0.17

		⟨D_z⟩	0.014 ± 0.007	0.060 ± 0.006	0.056 ± 0.006	0.015 ± 0.006	−0.016 ± 0.019	−0.085 ± 0.071
	SOM n(z)	⟨f⟩	0.15 ± 0.02	0.13 ± 0.04	0.15 ± 0.03	0.10 ± 0.03	0.09 ± 0.03	0.11 ± 0.04
	SOM n(z)	⟨χ_dof²⟩	0.97 ± 0.06	0.98 ± 0.08	0.97 ± 0.07	1.01 ± 0.10	0.97 ± 0.10	1.05 ± 0.15

Notes. Results were computed from shift-fits on the data and the 100 MICE2 realisations with noise adaptation. The uncertainties quoted for MICE2 refer to the standard deviation of the realisations, not the error of the mean. D_z: N(z) shift parameter (see Eq. 5) f: additive error term (see Eq. 6).

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