Benchmarking Separability-Entanglement Classifier
The dataset of our paper is available here. Both qubit and qutrit cases are included. You may test it, or even try to further improve our result with any other machine learning method you want.
We provide program in MATLAB for you to generate data and test for youself. You may download it here. Explanations are available below.
List of Functions
RandomState is a function that generates a random density matrix.
state = RandomState(dim, lambda)
dim: the number of rows (columns) the density matrix will have.
lambda: The parameter . When generating an density matrix, we first pick on the simplex under the Dirichlet distribution where is the normalization constant.
DMtoVector is a function that transform a density matrix to a generalized bloch vector.
vector = DMToVector(rho)
rho: the density matrix that we wish to transform.
Given a point and a set of extreme points of a convex hull such that , Alpha computes the maximum such that .
alpha = Alpha(p, extreme)
p: the point , which is a -by- matrix.
extreme: the points , which is an matrix.