def plotRF():
"""plot the RF amplitude"""
xrng = np.linspace(centerxRange[0], centerxRange[1], 10)
yrng = np.linspace(centeryRange[0], centeryRange[1], 10)
print xrng
print yrng
[X, Y] = np.meshgrid(xrng, yrng, indexing='ij')
z = 10 * u
xlist = np.ravel(X)
ylist = np.ravel(Y)
V = np.empty(xlist.shape)
FTrapWorld.set_omega_rf(30E6)
for i in range(len(xlist)):
print i
r = (xlist[i], ylist[i], z)
print r
V[i] = FTrapWorld.compute_pseudopot(r)
V = V.reshape(X.shape)
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.plot_surface(X, Y, V)
plt.show()
def plotRF():
"""plot the RF amplitude"""
xrng = np.linspace(centerxRange[0], centerxRange[1], 10)
yrng = np.linspace(centeryRange[0], centeryRange[1], 10)
print xrng
print yrng
[X, Y] = np.meshgrid(xrng, yrng, indexing='ij')
z = 10*u
xlist = np.ravel(X)
ylist = np.ravel(Y)
V = np.empty(xlist.shape)
FTrapWorld.set_omega_rf(30E6)
for i in range(len(xlist)):
print i
r = (xlist[i], ylist[i], z)
print r
V[i] = FTrapWorld.compute_pseudopot(r)
V = V.reshape(X.shape)
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.plot_surface(X, Y, V)
plt.show()
def getMinimumPseudopot(N):
""" return approximate minimum of the trap pseudopotential
in the dumbest way possible
sample N^3 points in a cube about the geometric trap center.
the saddle point is chosen as that with the minimum magnitude of
gradient"""
x0 = 0.5 * (centerxRange[0] + centerxRange[1])
y0 = 0.5 * (centeryRange[0] + centeryRange[1])
z0 = 200*u
width = 2*z0
gv = np.linspace(-width/2, width/2, N)
xrng = gv.copy() + x0
yrng = gv.copy() + y0
zrng = gv.copy() + z0
V = np.empty([N, N, N])
for i in range(N):
for j in range(N):
for k in range(N):
#print i, j, k
r = (xrng[i], yrng[j], zrng[k])
V[i,j,k] = FTrapWorld.compute_pseudopot(r)
dV = np.abs(np.gradient(V))
dVmin = np.amin(dV)
mn = np.where(dV == dVmin)
imin = mn[0][0]
jmin = mn[1][0]
kmin = mn[2][0]
rmin = (xrng[imin], yrng[jmin], zrng[kmin])
return rmin
def getMinimumPseudopot(N):
""" return approximate minimum of the trap pseudopotential
in the dumbest way possible
sample N^3 points in a cube about the geometric trap center.
the saddle point is chosen as that with the minimum magnitude of
gradient"""
x0 = 0.5 * (centerxRange[0] + centerxRange[1])
y0 = 0.5 * (centeryRange[0] + centeryRange[1])
z0 = 200 * u
width = 2 * z0
gv = np.linspace(-width / 2, width / 2, N)
xrng = gv.copy() + x0
yrng = gv.copy() + y0
zrng = gv.copy() + z0
V = np.empty([N, N, N])
for i in range(N):
for j in range(N):
for k in range(N):
#print i, j, k
r = (xrng[i], yrng[j], zrng[k])
V[i, j, k] = FTrapWorld.compute_pseudopot(r)
dV = np.abs(np.gradient(V))
dVmin = np.amin(dV)
mn = np.where(dV == dVmin)
imin = mn[0][0]
jmin = mn[1][0]
kmin = mn[2][0]
rmin = (xrng[imin], yrng[jmin], zrng[kmin])
return rmin
