2 * g * rho_max /
(m * R**2)) # Trap frequency corresponding to desired density and radius
mu = g * rho_max # Desired chemical potential of the groundstate
N_2D = pi * rho_max * R**2 / 2 # Thomas Fermi estimate of atom number for given chemical potential.
healing_length = 1 / np.sqrt(8 * pi * a * rho_max)
# Total spatial region over all MPI processes:
x_min = -5
x_max = 5
# Number of DVR basis functions per element:
N = 10
# Finite elements:
n_elements = 5
elements = FiniteElements1D(N, n_elements, x_min, x_max)
x = elements.points
alpha = 30
N_interp = 10000
x_interp = np.linspace(x_min, x_max, N_interp * n_elements)
def plot_vector(vector, *args, **kwargs):
x_interp, vec_interp = elements.interpolate_vector(vector, N_interp)
plt.plot(x_interp, vec_interp, *args, **kwargs)
for j in range(n_elements):
for i, point in enumerate(elements.points[j, :]):
if 0 < i < N - 1:
}
# Convert to float colours:
colors = {
name: [chan / 255 for chan in value]
for name, value in colors_rgb.items()
}
from FEDVR import FiniteElements1D
pi = np.pi
N = 10
n_elements = 2
x_max = 18
elements = FiniteElements1D(N, n_elements, 0, x_max)
FIG_WIDTH = 4.25
FIG_HEIGHT = 2.25
fig = plt.figure(figsize=(FIG_WIDTH, FIG_HEIGHT))
# gs = gridspec.GridSpec(1, 1, left=0.2, bottom=0.1,
# right=0.8, top=0.95, wspace=0.2, hspace=0.075)
# ax = plt.axes()
dx_av = x_max / (n_elements * (N - 1))
for i in range(n_elements):
for j in range(N):
psi = np.zeros((n_elements, N), dtype=complex)
psi[i, j] = 1 # np.sqrt(element.weights[i])