I am trying to solve a particular system of non linear equations written as $F(x) = 0$ in an efficient way.
More specifically, $$F(x) = (I - \gamma A)x - g(x) + C$$ where $\gamma$ is a scalarconstant, $C$ is a vector constant, $A$ is a constant matrix, and $g$ is a non-linear function of $R^n \rightarrow R^n$. I am using Newton's method and I am relatively satisfied with it. It involves computing the Jacobian $F'(x) = I - \gamma A - g'(x)$ and solving a linear system at each Newton iteration of the form $ F'(x^k) \Delta x^k = -F(x^k)$ and then set $x^{k+1} = x^k + \Delta x^k $. In this specific case it converges quickly (2-3 iterations at most) and everything works well.
However, as the problem becomes more complex and the size of my system of equations increases, computing the Jacobian and solving that linear system becomes a bottleneck. To overcome this, I use a simplified Newton's method which keeps F' constant over the whole Newton iteration process, and some parallel computing since the Jacobian can be computed in parallel efficiently in my case. Unfortunately, solving the linear system still remains a bottleneck (despite use of diverse parallel linear algebra techniques).
My question is then: Is there a way to take advantage of the specific form of $F$ ($i.e$ the fact that it is the sum of a linear operator and a non linear operator) ? In particular, I am especially interested in methods which would require me to solve linear systems with either $A$ (or $I - \gamma A$) or $g'$, but not their sum. Indeed, I have specific algorithms to solve linear systems with these matrices, but solving linear system with the sum of $I - \gamma A$ and $g'$ is very inefficient ($g'$ turns out to be block diagonal so adding $I - \gamma A$ messes it up, and solving $(I - \gamma A)X = B$ by itself is not an issue thanks to the specific structure of A)
Thanks