qiskit/tools/qi/qi.py
def mutual_information(state, d0, d1=None):
    """
    Compute the mutual information of a bipartite state.

    Args:
        state (array_like): a bipartite state-vector or density-matrix.
        d0 (int): dimension of the first subsystem.
        d1 (int or None): dimension of the second subsystem.

    Returns:
        float: The mutual information S(rho_A) + S(rho_B) - S(rho_AB).
    """
    if d1 is None:
        d1 = int(len(state) / d0)
    mi = entropy(partial_trace(state, [0], dimensions=[d0, d1]))
    mi += entropy(partial_trace(state, [1], dimensions=[d0, d1]))
    mi -= entropy(state)
    return mi
def mutual_information(state, d0, d1=None):
    if d1 is None:
        d1 = int(len(state) / d0)
    mi = entropy(partial_trace(state, [0], dimensions=[d0, d1]))
    mi += entropy(partial_trace(state, [1], dimensions=[d0, d1]))
    mi -= entropy(state)
    return mi
def mutual_information ( state , d0 , d1 = None ) : if d1 is None : d1 = int ( len ( state ) / d0 ) mi = entropy ( partial_trace ( state , [ 0 ] , dimensions = [ d0 , d1 ] ) ) mi += entropy ( partial_trace ( state , [ 1 ] , dimensions = [ d0 , d1 ] ) ) mi -= entropy ( state ) return mi
Compute the mutual information of a bipartite state.

    Args:
        state (array_like): a bipartite state-vector or density-matrix.
        d0 (int): dimension of the first subsystem.
        d1 (int or None): dimension of the second subsystem.

    Returns:
        float: The mutual information S(rho_A) + S(rho_B) - S(rho_AB).
Compute the mutual information of a bipartite state .