qiskit.optimization.applications.ising.max_cut
Convert max-cut instances into Pauli list Deal with Gset format. See https://web.stanford.edu/~yyye/yyye/Gset/ Design the max-cut object w as a two-dimensional np.array e.g., w[i, j] = x means that the weight of a edge between i and j is x Note that the weights are symmetric, i.e., w[j, i] = x always holds.
Functions
get_graph_solution(x) | Get graph solution from binary string. |
get_operator(weight_matrix) | Generate Hamiltonian for the max-cut problem of a graph. |
max_cut_value(x, w) | Compute the value of a cut. |
get_graph_solution
get_graph_solution(x)
Get graph solution from binary string.
Parameters
x (numpy.ndarray) – binary string as numpy array.
Returns
graph solution as binary numpy array.
Return type
numpy.ndarray
get_operator
get_operator(weight_matrix)
Generate Hamiltonian for the max-cut problem of a graph.
Parameters
weight_matrix (numpy.ndarray) – adjacency matrix.
Returns
operator for the Hamiltonian float: a constant shift for the obj function.
Return type
max_cut_value
max_cut_value(x, w)
Compute the value of a cut.
Parameters
- x (numpy.ndarray) – binary string as numpy array.
- w (numpy.ndarray) – adjacency matrix.
Returns
value of the cut.
Return type
float