def __init__(self, f1, f2):
self.f_qubit1 = f1
self.f_qubit2 = f2
# define hamiltonian for two qubits (zeeman on qubit 1, zeeman on qubit 2, exchange between qubits) -- convert from qutip to numpy (brackets)
self.B1 = qt.tensor(qt.sigmaz() / 2, qt.qeye(2))[:, :]
self.B2 = qt.tensor(qt.qeye(2), qt.sigmaz() / 2)[:, :]
self.J = (qt.tensor(qt.sigmax(), qt.sigmax()) +
qt.tensor(qt.sigmay(), qt.sigmay()) +
qt.tensor(qt.sigmaz(), qt.sigmaz()))[:, :] / 4
self.my_Hamiltonian = 2 * np.pi * (f1 * self.B1 + f2 * self.B2)
# Create the solver
self.solver_obj = ME.VonNeumann(4)
# Add the init hamiltonian
self.solver_obj.add_H0(self.my_Hamiltonian)
def __init__(self, f1, f2): self.f_qubit1 = f1 self.f_qubit2 = f2 self.H_mw_qubit_1 = np.array(list(basis(4,0)*basis(4,2).dag() + basis(4,1)*basis(4,3).dag()))[:,0] self.H_mw_qubit_2 = np.array(list(basis(4,0)*basis(4,1).dag() + basis(4,2)*basis(4,3).dag()))[:,0] # define hamiltonian for two qubits (zeeman on qubit 1, zeeman on qubit 2, exchange between qubits) -- convert from qutip to numpy (brackets) self.B1 = qt.tensor(qt.sigmaz()/2, qt.qeye(2))[:,:] self.B2 = qt.tensor(qt.qeye(2), qt.sigmaz()/2)[:,:] # transformed into rotating frame, so energy is 0 self.my_Hamiltonian = 0*self.B1 # Create the solver self.solver_obj = ME.VonNeumann(4) # Add the init hamiltonian self.solver_obj.add_H0(self.my_Hamiltonian)
X, noise_ampl**2
) # produces the same results of a white noise, but takes as second input the noise variance instead of the amplitude (var = ampl^2)
lindmid = time.time()
s.calculate_evolution(Z0, 0, total_t, evo_steps)
lindend = time.time()
s.plot_expectation(*pop, 1)
# VonNeumann calculation and plotting
vnstart = time.time()
v = me.VonNeumann(2)
v.add_H0(Z)
white = me.noise_py()
white.init_white(X, noise_ampl)
v.add_noise_obj(white)
v.set_number_of_evalutions(vn_samples)
vnmid = time.time()
v.calculate_evolution(Z0, 0, total_t, evo_steps)
vnend = time.time()
v.plot_expectation(*pop, 2)
print('\n Measuring the time of the script:')
def __init__(self, B_1, B_2, chargingE1, chargingE2, tunnel_coupling):
# Generate static part of hamiltonian (using numpy/qutip stuff)
# All energy's should be expressed in Hz
# H_bar = 1
self.H_charg1 = np.array(list(qt.basis(6, 4) *
qt.basis(6, 4).dag()))[:, 0]
self.H_charg2 = np.array(list(qt.basis(6, 5) *
qt.basis(6, 5).dag()))[:, 0]
self.H_B_field1 = np.array(
list(-qt.basis(6, 0) * qt.basis(6, 0).dag() - qt.basis(6, 1) *
qt.basis(6, 1).dag() + qt.basis(6, 2) * qt.basis(6, 2).dag() +
qt.basis(6, 3) * qt.basis(6, 3).dag()))[:, 0] / 2
self.H_B_field2 = np.array(
list(-qt.basis(6, 0) * qt.basis(6, 0).dag() + qt.basis(6, 1) *
qt.basis(6, 1).dag() - qt.basis(6, 2) * qt.basis(6, 2).dag() +
qt.basis(6, 3) * qt.basis(6, 3).dag()))[:, 0] / 2
self.H_exchange = np.array(
list(-qt.basis(6, 1) * qt.basis(6, 1).dag() - qt.basis(6, 2) *
qt.basis(6, 2).dag() + qt.basis(6, 1) * qt.basis(6, 2).dag() +
qt.basis(6, 2) * qt.basis(6, 1).dag()))[:, 0] / 2
self.H_tunnel = np.array(
list(
qt.basis(6, 1) * qt.basis(6, 4).dag() -
qt.basis(6, 2) * qt.basis(6, 4).dag() +
qt.basis(6, 1) * qt.basis(6, 5).dag() -
qt.basis(6, 2) * qt.basis(6, 5).dag() +
qt.basis(6, 4) * qt.basis(6, 1).dag() -
qt.basis(6, 4) * qt.basis(6, 2).dag() +
qt.basis(6, 5) * qt.basis(6, 1).dag() -
qt.basis(6, 5) * qt.basis(6, 2).dag()))[:, 0]
self.B_1 = B_1
self.B_2 = B_2
self.chargingE1 = chargingE1
self.chargingE2 = chargingE2
self.tunnel_coupling = tunnel_coupling
self.my_Hamiltonian = 2 * np.pi * (self.H_charg1 * chargingE1 +
self.H_charg2 * chargingE2 +
self.H_tunnel * tunnel_coupling)
self.h_raw = self.my_Hamiltonian / 2 / np.pi + self.H_B_field1 * B_1 + self.H_B_field2 * B_2
# Clock of rotating frame
self.f_qubit1 = B_1
self.f_qubit2 = B_2
# Init params
self.amp_noise_1 = 0
self.amp_noise_2 = 0
self.number_of_samples = 1
self.one_f_noise = 0
# Create the solver
self.solver_obj = ME.VonNeumann(6)
# Add the init hamiltonian
self.solver_obj.add_H0(self.my_Hamiltonian)
if self.f_qubit1 - self.f_qubit2 != 0:
# add time dependent tunnelcouplings (see presentation)
locations_1 = np.array([[1, 4], [1, 5]], dtype=np.int32)
self.solver_obj.add_cexp_time_dep(
locations_1, (self.f_qubit1 - self.f_qubit2) / 2)
locations_1 = np.array([[2, 4], [2, 5]], dtype=np.int32)
self.solver_obj.add_cexp_time_dep(
locations_1, (self.f_qubit2 - self.f_qubit1) / 2)
