对于审稿意见：此外重要的是要考虑到CIE模型的非线性程度取决于beta的值。在数值部分1和6中选择的beta值允许降低非线性程度吗该如何写审稿意见回复？beta的设置是遵循第5页由其他文献总结的具体的设置原则：beta在第一轮中设置的较大然后随着轮数的增加而减小。在本文中beta=1都符合降低非线性的要求因为R的范数小于1本文考虑的chi的范数=16I+Abeta的范数约等于Abeta的范数所以R

Thank you for your valuable comments on our manuscript. Regarding your concern about the nonlinearity of the CIE model, we would like to clarify that the choice of \beta values in our numerical experiments (Sections 1 and 6) follows the specific setting principles summarized by other literature on page 5. As mentioned in the manuscript, \beta is initially set to a larger value and then gradually decreases with each iteration. In our case, all \beta values used in the experiments are greater than or equal to 1, which satisfies the requirement of reducing nonlinearity. Moreover, the norm of R*(I+A/beta) is smaller than the norm of chi*A, and the norm of (I+A/beta) is approximately equal to the norm of A/beta, which further ensures a lower degree of nonlinearity. We hope this explanation addresses your concern and we appreciate your attention to our work