Question

I have written a function using a quantum simulation class QuTIP that returns a float. Next, I called scipy.optimize.fmin_cg on the function. I keep getting the error:

AttributeError: 'numpy.ndarray' object has no attribute 'expm'

on the line:

U_sq = H_sq.expm

But H_sq is an instance of Qobj, not an ndarray. If I run the function outside of scipy.optimize.fmin_cg, it returns the type as ‘instance’; when it runs inside of fmin_cg it returns the type as ‘ndarray’.

Why does it do this? Is there a optimization function in python that will respect using instances like this?

Here is the code:

from qutip import *
from numpy import *
import scipy.optimize


def sq_fidelity(eps,N=7):
    H_sq = squeez(N,eps);
    print type(H_sq);
    one_ph = basis(N,1);
    U_sq = H_sq.expm();
    squ = U_sq*one_ph;
    fidelity = expect(fock_dm(N,1),squ);
    return float(fidelity) 

if __name__=='__main__':
    print sq_fidelity(0.2);
    eps = scipy.optimize.fmin_cg(sq_fidelity, x0=0.2, args=(7,));

Answer 1

The issue here is that fmin_cg is passing an ndarray (of length 1) to your objective function. You can extract the scalar value by just changing the first line of sq_fidelity to:

H_sq = squeez(N, float(eps))