Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Separable and non-separable data representation for pattern
  discrimination   We provide a complete work-flow, based on the language of quantum information
theory, suitable for processing data for the purpose of pattern recognition.
The main advantage of the introduced scheme is that it can be easily
implemented and applied to process real-world data using modest computation
resources. At the same time it can be used to investigate the difference in the
pattern recognition resulting from the utilization of the tensor product
structure of the space of quantum states. We illustrate this difference by
providing a simple example based on the classification of 2D data.

34
The categories of this paper are: chem-ph
20
The categories of this paper are: acc-phys
25
The categories of this paper are: patt-sol
11
The categories of this paper are: hep-lat
37
The categories of this paper are: supr-con
10
The categories of this paper are: q-bio
29
The categories of this paper are: funct-an
35
The categories of this paper are: mtrl-th
32
The categories of this paper are: atom-ph
33
The categories of this paper are: plasm-ph
19
The categories of this paper are: eess
18
The categories of this paper are: econ
0
The categories of this paper are: hep-ph
36
The categories of this paper are: cmp-lg
2
The categories of this paper are: math
3
The categories of this paper are: physics