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(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(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

WeightedPauliOperator

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