N = 1000
# x domain
x_min = -50
x_max = 50
# starting point
t = 0
t_max = 6
# create list of all x points
x = np.linspace(x_min, x_max, N, endpoint=True)
# time step
dt = 0.1
# calculate initial state
# current_state = psi(x)
# create the Stepper which propagates times
stepper = Stepper(None, t, x, V)
stepper.t_max = t_max
time_shift = t_max / 2
energys, eigenstates = stepper.get_stationary_solutions(k=250)
iterations = 1000
diff = np.zeros((iterations, 5))
for i in range(iterations):
parameters = np.random.rand(len(max_parameters)) * max_parameters
if i == 0:
parameters = np.array([0.6591, 0.6819, 0.7859, 4.4431])
# frequencies = [(1, parameters[2]), (parameters[3], parameters[4])]
# stepper.set_electric_field(parameters[0], time_shift, parameters[1], frequencies)
stepper.set_electric_field2(parameters[0],
[(1, parameters[1]),
goal = ti.var(dt=ti.f64, shape=N, needs_grad=True) occupation = ti.var(dt=ti.f64, shape=(), needs_grad=True) projection = ti.Vector(2, dt=ti.f64, shape=(), needs_grad=True) left_main_diag = ti.Vector(2, dt=ti.f64, shape=N, needs_grad=True) left_upper_diag = ti.Vector(2, dt=ti.f64, shape=N - 1, needs_grad=True) left_lower_diag = ti.Vector(2, dt=ti.f64, shape=N - 1, needs_grad=True) right_main_diag = ti.Vector(2, dt=ti.f64, shape=N, needs_grad=True) right_upper_diag = ti.Vector(2, dt=ti.f64, shape=N - 1, needs_grad=True) right_lower_diag = ti.Vector(2, dt=ti.f64, shape=N - 1, needs_grad=True) right_side = ti.Vector(2, dt=ti.f64, shape=N, needs_grad=True) current = ti.Vector(2, dt=ti.f64, shape=N, needs_grad=True) stepper = Stepper(None, t, x, V) energys, eigenstates = stepper.get_stationary_solutions(k=250) parameters.from_numpy(p) space.from_numpy(x) initial.from_numpy(np.real(eigenstates[0])) goal.from_numpy(np.real(eigenstates[1])) harmonic_pot() # init() # while t < t_max: # step() # t += dt # get_occupation() # testing grad
N = 1000
# x domain
x_min = -50
x_max = 50
# starting point
t = 0
t_max = 6
# create list of all x points
x = np.linspace(x_min, x_max, N, endpoint=True)
# time step
dt = 0.1
# calculate initial state
# current_state = psi(x)
# create the Stepper which propagates times
stepper = Stepper(None, t, x, V)
stepper.t_max = t_max
energys, eigenstates = stepper.get_stationary_solutions(k=250)
target_freq = 4.
def spectrum(parameters):
time_shift = t_max / 2
stepper.set_time(0)
stepper.set_state(eigenstates[0], normalzie=False)
frequencies = [(1, parameters[2]), (parameters[3], parameters[4])]
stepper.set_electric_field(parameters[0], time_shift, parameters[1],
frequencies)
simulation = jit(simulate, static_argnums=6)
N = 1000
x_min = -50
x_max = 50
space = np.linspace(x_min, x_max, N, endpoint=True, dtype=np.float64)
dx = 0.1
dx2 = dx ** 2
# parameters = np.array([2.21, 1.59, 1.60, 3.14, 2.15], dtype=np.float64)
parameters = np.array([10., 1., 5., 1., 5.], dtype=np.float64)
t = 0.
t_h = 3.0
dt = 0.1
stepper = Stepper(None, 0, onp.array(space), harmonic_pot_np)
energys, eigenstates = stepper.get_stationary_solutions(k=250)
state = np.array(eigenstates[0], dtype='complex128')
target_freq = 1.
N_step = int(2 * t_h / dt)
freqs = np.fft.fftshift(np.fft.fftfreq(N_step, dt / (2 * np.pi)))
target_index = 0
for i in range(0, N_step):
if target_freq < freqs[i]:
target_index = i - 1
break
N = 1000
# x domain
x_min = -50
x_max = 50
# starting point
t = 0
t_max = 6
# create list of all x points
x = np.linspace(x_min, x_max, N, endpoint=True)
# time step
dt = 0.1
# calculate initial state
# current_state = psi(x)
# create the Stepper which propagates times
stepper = Stepper(None, t, x, V)
stepper.t_max = t_max
energys, eigenstates = stepper.get_stationary_solutions(k=250)
targets = []
goal = [i - 1 for i in max_indices]
try:
while indices[0] < max_indices[0]:
print(f'Current indicies = {indices}\n End = {goal}')
stepper.set_time(0)
stepper.set_state(eigenstates[0], normalzie=False)
stepper.set_electric_field(amplitudes[indices[0]], t_max / 2, time_widths[indices[1]],
[(1, freq1[indices[2]]),
(amp_freq2[indices[3]], freq2[indices[4]])])
stepper.step_to(t_max, dt)