A decomposition of a function $f:\mathbb{R}^2\rightarrow \mathbb{R}$ is a sum of products of single-value functions: $f(x,y)=\sum_{i=1}^n u_i(x)\cdot v_i(y)$. If a function has at least one decomposition, it is called decomposable; otherwise, it is undecomposable.
It is straightforward to show that sums and products of decomposable functions are likewise decomposable. I do not know of specific undecomposable functions, but my intuition is that they exist and that most functions are undecomposable.
Question. I'd like to know: given $f\cdot g$ is decomposable and $g$ is decomposable, [when] is $f$ decomposable?
If that's hard, I'd appreciate any additional results about when products and sums involving undecomposable functions can result in decomposable functions.
So far, my intuition is that decomposable functions and undecomposable functions will have similar arithmetic closure properties to rational and irrational numbers.
I have been looking for a provably undecompsable function—besides functions like $x^y$, I've thought about using an infinite sequence of linearly-independent functions, because I've shown that if a function has a decomposition, it has a minimal decomposition where all the $u_i$ are linearly independent and all the $v_i$ are linearly independent. If a function were somehow an irreducibly infinite sum of pairs $u_iv_i$ where the $u_i$ are all linearly independent as are the $v_i$, it would not be decomposable.
I've also been looking into function spaces where these functions and their decompositions live. Based on what I've learned, I believe the space of decomposable functions is the tensor space $\mathscr{F}_X \otimes \mathscr{F}_Y$, consisting of linear combinations of pairs of functions of $x$ and of $y$, and this can be embedded in the vector space $\mathscr{F}_{X\times Y}$ of two-variable functions. But I have not yet found a way to prove my desired result by arguing generally about vector/tensor spaces.