def linear_response(GS_obj, time_slice):
"""Compute MCTDHB-LR."""
if not isinstance(GS_obj, GS):
raise TypeError
LR = MCTDHB()
LR.set_par('T_FROM', time_slice)
LR.set_par('T_TILL', time_slice)
LR.unset_properties()
LR.set_par('GET_LR', True)
LR.set_par('DATA_PSI', True)
LR.set_par('DATA_CIC', True)
LR.set_par('LR_MAXSIL', 1000) #this seems to affect nothing
#run
LR.run_properties()
# 'MC_anlsplotALL.out' contains 100 LR roots:
# root -- i + 10 + 2*M [0]
# energies -- dE_i = E_i-E_0 [1], E_i [2]
# norm -- orbital-, CI-part [3:5]
# response amplitudes (RE, IM) -- f+=f-=x [5:7], x**2 [7:9]
dpath = 'DATA/getLR/'
state = GS_obj
GS_root = 10 + 2*GS_obj.get_pvalue('M')
for data in io.extract_data(dpath + 'MC_anlsplotALL.out'):
root = data[0] - GS_root
E = data[2]
norm = data[3:5]
uAmp = data[5:7]
gAmp = data[7:9]
if (root > 0) and (E > GS_obj.E):
new_state = ES(GS_obj, data)
state.set_pright('i', new_state)
new_state.set_pleft('i', state)
assert (new_state.get_pvalue('i')-1 == state.get_pvalue('i'))
assert (state is not new_state)
state = new_state
assert (state is new_state)
return GS_obj
def relax(obj, tolerance=1E-12, t_tau=.1, t_max=20,
backward=False, LR=False):
"""relax(mctdhb obj) -> GS object
Find system's GroundState (GS).
keyword arguments:
tolerance = 1E-12 -- tolerated energy error of relaxed state
t_tau = 0.1 -- working relaxation step (iteration step)
max_time = 20 -- maximal time allowed until convergance
backward = False -- backward relaxation
properties = True -- compute GS properties
"""
if (backward):
obj.set_par('JOB_PREFAC', complex(+1, 0))
else:
obj.set_par('JOB_PREFAC', complex(-1, 0))
if (t_tau <= 2):
obj.set_par('TIME_TAU', t_tau)
obj.set_par('TIME_PRINT_STEP', t_tau) #each iteration print data
else:
obj.set_par('TIME_TAU', .1)
obj.set_par('TIME_PRINT_STEP', .1)
obj.set_par('TIME_TOLERROR_TOTAL', tolerance)
obj.set_par('TIME_ICI_PRT', 1) #create as many coef data points as time data points
obj.set_par('PRINT_DATA', False) #no need to explicitly print *.dat
obj.set_par('STATE', 1) #relax to GS
# Iterating piecewise allows feeback of converge status
# and the internal storage binaries are kept small.
time = 0
time_step = 2
obj.set_par('GUESS', 'HAND') #first guess
obj.set_par('TIME_BGN', time)
obj.set_par('TIME_FNL', time_step + t_tau)
while True:
rm_output()
obj.run()
# Energy difference of last iteration step.
dE = io.extract_data('NO_PR.out')[-1][obj.get_M()+4]
print(dE)
if (dE < tolerance):
print('converged')
break
if (time >= t_max):
print('not converged')
raise RuntimeError
time += time_step
obj.set_par('GUESS', 'BINR') #next guess
obj.set_par('BINARY_START_POINT_T', time)
obj.set_par('TIME_BGN', time)
obj.set_par('TIME_FNL', time + time_step + t_tau)
# 'OP_PR.out' -- Operator values per particle per iteration:
# iteration time -- [0]
# energy constituents -- E, T, V, W [1:5]
# x-space (3D) -- x [5:8], xx [8:11], var_x [11:14]
# k-space (3D) -- k [14:17], kk [17:20], var_k [20:23]
# 'NO_PR.out' Natural Occupation and Errors per iteration:
# iteration time -- [0]
# occupation numbers -- [1:M+1]
# energy errors -- E, E_tolerance, dE/E_tolerance, abs(dE),
# abs(dE_ci), abs(dE) - abs(dE_ci)
data = []
for outfile in ['OP_PR.out', 'NO_PR.out']:
data.append(io.extract_data(outfile)[-1])
if (LR):
return linear_response(GS(obj, data), time + time_step)
else:
return GS(obj, data)
