I have an implicitly defined function F(g1(x1),…,gn(xn))=0, on the n-th dimension euclidean space, bounded and continuous in its n arguments. gi are also real-valued bounded and continuous functions. What I'm trying to figure out is if I additionally need any conditions to guarantee that the implicit relation xi=fi(x1,…,xi−1,xi+1,…,xn) is continuous in its arguments. I know that if F was differentiable in all of its arguments, by the Implicit Function Theorem, the cross partial derivatives would exists and thus I would have continuity. However, in my case it is not necessarily true that F is differentiable in its arguments. My intuition says that as everything is compositions of continuous functions, the implicit relation among variables should also be, but I want to make sure.
Many thanks!
Answer
The standard version of the inverse function theorem (and the implicit function theorem), require that F is continuously differentiable and that its Jacobian at a point of interest is invertible.
There exist, however, generalizations that impose weaker assumptions on F.
For example, Theorem 1A.4 in [1] states that for a function Φ:Rm×Rn→Rn such that there is an Lp≥0 and Lx∈[0,1) such that
‖Φ(p,x′)−Φ(p,x)‖≤Lx‖x′−x‖
and
‖Φ(p′,x)−Φ(p,x)‖≤Lp‖p′−p‖
Then, the mapping p↦{x∈Rn:x=Φ(p,x)} is single-valed for all p and Lipschitz continuous.
You mentioned that since everything is a composition of continuous functions, the result will also be continuous. The issue, and what makes inverse problems very challenging, is that if f is only known to be continuous, f−1 is multi-valued. The study of the properties f−1 is one of the topics of set-valued analysis.
You can apply this theorem to Φ(p,x)=x−F(p,x). Assumption (1) might be a little restrictive because Lx must be in [0,1).
See also Theorem 1E.13 in [1]. Lastly, often a function is not differentiable, but it can be shown to be semidifferentiable, so you have a lot of results that allow you to derive Lipschitz continuous inverse functions.
[1] A.L. Dontchev, R.T. Rockafellar, Implicit Functions and Solution Mappings, A View From Variational Analysis, Springer pdf.
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