Impact of the Tikhonov regularisation used to suppress oscillating solutions f_δ(k, z). Shown are, for a noise-free mock data vector and the KiDS-1000 error covariance, the posterior constraints (68% credible regions) on f_δ averaged over the redshift bin Z₁ = [0, 0.3] (left), Z₂ = [0.3, 0.6] (middle), and Z₃ = [0.6, 2] (right) with and without regularisation (dark orange τ = 5.0 with median as dashed line or light orange τ = 0). To boost scale-dependence and evolution, f_δ(k, z) is here defined relative to the power spectrum at fixed redshift, probing the relative structure growth since z = 1. The solid line is the median posterior f_δ for 100× reduced measurement errors, providing a nearly noise-free reference (noise/100) that averages the growth over the redshift bin while still exhibiting artefacts near the edges. The dotted lines are the theoretical $P_{\delta }^{\mathrm{fid}}(k,\overline{z})/P_{\delta }^{\mathrm{fid}}(k,z=1)$ for one specific $\overline{z}$ chosen to most closely match the solid lines, indicating the redshift with highest weight in the average.