Convergence rates analysis of Tikhonov regularization for nonlinear ill-posed problems with noisy operators

We investigate convergence rates of Tikhonov regularization for nonlinear ill-posed problems when both the right-hand side and the operator are corrupted by noise. Two models of operator noise are considered, namely uniform noise bounds and point-wise noise bounds. We derive convergence rates for both noise models in Hilbert and in Banach spaces. These results extend existing results where the forward operator is mostly assumed to be linear.