My question is based on the structure of the NP-hardness proof in section 6 (page 17) of this paper, http://arxiv.org/pdf/quant-ph/0303055v1.pdf
Mathematically one can think of being given a positive semi-definite linear map $\rho : \mathbb{C}^n \otimes \mathbb{C}^m \rightarrow \mathbb{C}^n \otimes \mathbb{C}^m$ such that its trace is $1$ and one wants to determine if there exists some $k$ (column) vectors $x_i \in \mathbb{C}^n$ and another $k$ (column) vectors $y_i \in \mathbb{C}^m$ such that $\rho = \sum_{i=1}^{k} x_i x_i ^{\dagger} \otimes y_i y_i^{\dagger}$
If I understand right then this linked paper is proving the decision version of the above question to be NP-hard. (please correct me if my reading is wrong!)
- But I am curious to know as to what would be even a brute-force algorithm to solve this! (in my limited experience for all NP-hard questions there is a trivial brute force solution that is always obvious - but not here!)
[Expanding the questions formulated in the comments]
Trivially it seems that there is no hope of being able to check this unless one allows for some finite precision error. But if with such a discretization the question is redefined then is the corresponding decision question still NP-Hard?
So is there a difference between the decision question that is being shown to be NP-Hard and the actual entanglement question that needs to be solved?
EDIT [$4^{th}$ August 2015]
I found this presentation by Aram Harrow which explains many of the issues that I was trying to get to but couldn't explain properly : http://simons.berkeley.edu/talks/aram-harrow-2014-09-25 (he explains pretty much this exact same question inside his lecture!)