def calc():
## optimized basis set
b = STOs()
b.add(2, 0.9965751177 -0.0013743026j)
b.add(2, 1.0030366528 -0.2836728004j)
b.add(2, 0.8462928140 -0.6952686244j)
b.add(2, 0.4818046345 -1.0023929406j)
b.add(2, 0.1412093744 -1.0662761427j)
b.setup()
## velocity driven term
driv = LC_STOs()
driv.add(2.0, 2, 1.0)
## print claculation inputs
f.write("calculation of hydrogen atom photoionization in length form\n")
f.write("solve radial equation\n")
f.write("(H-E)psi=driv\n")
f.write("\n")
f.write(">>> INPUTS >>> \n")
f.write("L = {0}\n".format(L))
f.write("energy = {0}\n".format(ene))
f.write("driv = {0}\n".format(driv.str()))
f.write("basis = \n")
f.write("grid = ({0}, {1})".format(n, h))
f.write(b.str())
## calculation
lmat = ( b.calc_d2_mat()* (-0.5)
+ b.calc_rm_mat(-2)* (0.5*(L*(L+1)))
+ b.calc_rm_mat(-1) * (-1.0)
+ b.calc_rm_mat(0) * (-ene))
mvec = b.calc_vec(driv)
cs = solve(lmat, mvec)
alpha = np.dot(cs, mvec)
## calculate by CBF
rs = np.linspace(0, 100, 300)
ys = np.array(b.at_r(rs, cs))
df = pd.DataFrame([rs, ys.real, ys.imag]).T
df.columns = ["r", "re_y", "im_y"]
df.to_csv(psi_csv, index=False)
## calculate by grid
s = lambda r: driv.at_r([r])[0]
v = lambda r: L*(L+1)/(2.0*r*r) -1.0/r
(rs, ys) = solve_driv(v, ene, s, n, h)
df = pd.DataFrame([rs.real, ys.real, ys.imag]).T
df.columns = ["r", "re_y", "im_y"]
df.to_csv(grid_csv, index=False)
## print outpus
f.write("\n>>> RESULTS >>> \n")
f.write("psi_csv = {0}\n".format(psi_csv))
f.write("grid_csv = {0}\n".format(grid_csv))
f.write("cs = \n")
for c in cs:
f.write("{0}\n".format(c))
f.write("alpha = {0} {1}\n".format(alpha.real, alpha.imag))
def calc():
## optimized basis set
b = STOs()
b.add(2, 0.9965751177 - 0.0013743026j)
b.add(2, 1.0030366528 - 0.2836728004j)
b.add(2, 0.8462928140 - 0.6952686244j)
b.add(2, 0.4818046345 - 1.0023929406j)
b.add(2, 0.1412093744 - 1.0662761427j)
b.setup()
## velocity driven term
driv = LC_STOs()
driv.add(2.0, 2, 1.0)
## print claculation inputs
f.write("calculation of hydrogen atom photoionization in length form\n")
f.write("solve radial equation\n")
f.write("(H-E)psi=driv\n")
f.write("\n")
f.write(">>> INPUTS >>> \n")
f.write("L = {0}\n".format(L))
f.write("energy = {0}\n".format(ene))
f.write("driv = {0}\n".format(driv.str()))
f.write("basis = \n")
f.write("grid = ({0}, {1})".format(n, h))
f.write(b.str())
## calculation
lmat = (b.calc_d2_mat() * (-0.5) + b.calc_rm_mat(-2) * (0.5 * (L *
(L + 1))) +
b.calc_rm_mat(-1) * (-1.0) + b.calc_rm_mat(0) * (-ene))
mvec = b.calc_vec(driv)
cs = solve(lmat, mvec)
alpha = np.dot(cs, mvec)
## calculate by CBF
rs = np.linspace(0, 100, 300)
ys = np.array(b.at_r(rs, cs))
df = pd.DataFrame([rs, ys.real, ys.imag]).T
df.columns = ["r", "re_y", "im_y"]
df.to_csv(psi_csv, index=False)
## calculate by grid
s = lambda r: driv.at_r([r])[0]
v = lambda r: L * (L + 1) / (2.0 * r * r) - 1.0 / r
(rs, ys) = solve_driv(v, ene, s, n, h)
df = pd.DataFrame([rs.real, ys.real, ys.imag]).T
df.columns = ["r", "re_y", "im_y"]
df.to_csv(grid_csv, index=False)
## print outpus
f.write("\n>>> RESULTS >>> \n")
f.write("psi_csv = {0}\n".format(psi_csv))
f.write("grid_csv = {0}\n".format(grid_csv))
f.write("cs = \n")
for c in cs:
f.write("{0}\n".format(c))
f.write("alpha = {0} {1}\n".format(alpha.real, alpha.imag))
import sys
import numpy as np
sys.path.append("../../")
from driv_grid import solve_driv
## system
L = 1.0
ene = 0.5
## driven term
s = lambda r: 2.0 * r * r * np.exp(-r)
## potential
v = lambda r: -1.0/r + L*(L+1)/(2.0*r*r)
## grid points
n = 1000
h = 0.1
## calculate
(rs, ys) = solve_driv(v, ene, s, n, h)
## write
with open("h_length.csv", "w") as f:
for (r, y) in zip(rs, ys):
f.write("{0},{1},{2}\n".format(r, y.real, y.imag))
import sys
sys.path.append("../../../src_py/driv_grid")
from driv_grid import solve_driv
sys.path.append("../../../r1basis")
from opt_green import *
grid_csv = "grid.csv"
channel = '1s->kp'
dipole = 'length'
h_pi = H_Photoionization(channel, dipole)
L = h_pi.L1
w0 = 1.0
n = 1000
h = 0.1
s = lambda r: h_pi.driv.at_r([r])[0]
v = lambda r: L * (L + 1) / (2.0 * r * r) - 1.0 / r
(rs, ys) = solve_driv(v, w0 + h_pi.E0, s, n, h)
df = pd.DataFrame([rs.real, -ys.real, -ys.imag]).T
df.columns = ["r", "re_y", "im_y"]
df.to_csv(grid_csv, index=False)
## system
L = 1.0
ene = 0.5
## driven term
s = lambda r: 2.0 * r * r * np.exp(-r)
## potential
v = lambda r: -1.0/r + L*(L+1)/(2.0*r*r)
## grid points
n = 10000
h = 0.1
## calculate
(rs, ys) = solve_driv(v, ene, s, n, h)
## write
with open("h_length.csv", "w") as f:
for (r, y) in zip(rs, ys):
f.write("{0},{1},{2}\n".format(r, y.real, y.imag))
## compute dipole, written as M in the paper
k = np.sqrt(2.0 * ene)
y = ys[-2]
r = rs[-2]
print "dip = ", abs(y*k / (4*np.exp(complex(0, k*r - np.pi*L/2.0 + 1.0/k * np.log(2*k*r) ))))
## compute dipole from matrix element of Green's operator
xs = np.array([(i+1)*h for i in range(n)])
ss = np.array([s(x) for x in xs])
import sys
sys.path.append("../../../src_py/driv_grid")
from driv_grid import solve_driv
sys.path.append("../../../r1basis")
from opt_green import *
grid_csv = "grid.csv"
channel = '1s->kp'
dipole = 'length'
h_pi = H_Photoionization(channel, dipole)
L = h_pi.L1
w0 = 1.0
n = 1000
h = 0.1
s = lambda r: h_pi.driv.at_r([r])[0]
v = lambda r: L*(L+1)/(2.0*r*r) -1.0/r
(rs, ys) = solve_driv(v, w0+h_pi.E0, s, n, h)
df = pd.DataFrame([rs.real, -ys.real, -ys.imag]).T
df.columns = ["r", "re_y", "im_y"]
df.to_csv(grid_csv, index=False)
