Let $n,N \in \mathbb{N}$ with $N \ge n^{2}$.

Let $F[i] = \square[i]$ refer to the cube which has vertices from $\{-1,0,1\}^{n^{i}}$ ($n^{i}$ tuple of alphabets from $\{-1,0,1\} = \square[0] = F[0]$)

Let $\{Q_{i}\}_{i=1}^{n^{2}}$ and $\{P_{j}\}$$_{j=1}^{N}$ be points over $F[4]$ and $F[2] \otimes F[2]$ respectively.

Let $Q, P$ and $\Lambda$ be matrices of size $n^{2} \times n^{4}, N \times n^{4}$ and $n^{2} \times N$ respectively with entries from $F[0]$.

The rows of $Q$ and $P$ be the points $\{Q_{i}\}_{i=1}^{n^{2}}$ and $\{P_{j}\}$$_{j=1}^{N}$ respectively.

Let $Q$ be known ($P$ and $\Lambda$ are unknowns) in the following equation:

$\Lambda P = Q$

What is the minimal size of $N$ so that one can expect a compatible $\Lambda$ and $P$ for a generic $Q$? Are there good lower and upper bounds for $N$?

What tools could be useful to study this problem?

With respect to Yemon Choi's comment: Regarding algortihms, a naive algorithm would run in worst case $3^{2Nn^{2}}$ complexity since it has to iterate over all possible values of of $F[0]$ as candidate entries of $\Lambda$ and $P$ for each given $N$ to check if there is a compatible solution. Even for $n=3$, this is formidable. Is there a faster algorithm to decide existence of compatibility for a given $N$? Could the cube to sphere relaxation help reduce complexity while giving something satisfactory?

Are there any textbooks or papers that handle something similar to this?