CVXPY can't maximize function

Question

I'm trying to maximize the value of a function based on qutip to find the hermitian positive semidefinite matrix of trace equal 1 that maximized this function, but CVXPY always returns the value 0.0 and a diagonal matrix, do I have to do something for the solver to allow complex values on the matrix?

My code below:

import numpy as np
from qutip import *
import matplotlib.pyplot as plt
import cvxpy as cp


def Coherence(density_matrix):
    rho = Qobj(density_matrix)
    diag = rho.diag()
    matrix_diag = np.diag(diag)
    rho_diag = Qobj(matrix_diag)
    coherence = entropy_vn(rho_diag, 2) - entropy_vn(rho, 2)
    return coherence

n = 2**7

density_matrix = cp.Variable((n,n), hermitian=True)
constraints = [cp.trace(density_matrix) == 1]

prob = cp.Problem(cp.Maximize(Coherence(density_matrix.value)),constraints)
prob.solve()

# Print result.
print("The optimal value is", prob.value)
print("A solution density matrix is")
print(density_matrix.value)

always returns this results:

The optimal value is -0.0
A solution density matrix is
[[0.0078125+0.j 0.       +0.j 0.       +0.j ... 0.       +0.j
  0.       +0.j 0.       +0.j]
 [0.       +0.j 0.0078125+0.j 0.       +0.j ... 0.       +0.j
  0.       +0.j 0.       +0.j]
 [0.       +0.j 0.       +0.j 0.0078125+0.j ... 0.       +0.j
  0.       +0.j 0.       +0.j]
 ...
 [0.       +0.j 0.       +0.j 0.       +0.j ... 0.0078125+0.j
  0.       +0.j 0.       +0.j]
 [0.       +0.j 0.       +0.j 0.       +0.j ... 0.       +0.j
  0.0078125+0.j 0.       +0.j]
 [0.       +0.j 0.       +0.j 0.       +0.j ... 0.       +0.j
  0.       +0.j 0.0078125+0.j]]