def setup_output(self):
self.woutp = WriteOutputMD_TSH()
if self.restart: self.woutp.restart(self)
else: self.woutp.start(self)
def setup_output(self):
self.woutp = WriteOutputMD_TSH()
if self.restart: self.woutp.restart(self)
else: self.woutp.start(self)
class TullySurfaceHopping(MolecularDynamics):
"""
Tully Surface Hopping method
is for dealng with non adiabatic transition process during classical MD simulation.
J. C. Tully, J. Chem. Phys. 93, 1061 (1990).
"""
def __init__(self, mol, pot, dt, nstep, tsh_times = 5, restart = False,\
tsh_ediff_thresh=0.1, tsh_ediff_factor=0.25, check_mdstop_dispersion = False,\
limit_dispersion = 10.0, tlim = float('inf')):
MolecularDynamics.__init__(self, mol, pot, dt, nstep, restart,\
check_mdstop_dispersion, limit_dispersion, tlim)
self.now_state = self.pot.get_now_state()
self.nrange = self.pot.get_nrange()
self.m_root = np.sqrt(self.mol.get_masses())
self.tsh_times = tsh_times
self.delta_st = 0.5 * self.dt / self.tsh_times
self.dt_bak = self.dt
self.tsh_ediff_thresh = tsh_ediff_thresh
self.tsh_ediff_factor = tsh_ediff_factor
self.c = np.zeros(self.nrange)
self.c[self.now_state] = 1.0
self.count = 0
self.count_tsh = 0
self.setup_output()
def setup_output(self):
self.woutp = WriteOutputMD_TSH()
if self.restart: self.woutp.restart(self)
else: self.woutp.start(self)
def run(self):
self.prepare()
self.woutp.logging(self)
while self.count < self.nstep:
self.count += 1
self.judge_tsh()
self.step()
self.pre_judge_tsh()
self.check_ediff()
self.judge_tsh()
self.count_tsh = 0
self.woutp.logging(self)
if self.mdstop_time_trans(): break
if self.check_mdstop_dispersion and self.mdstop_atom_dispersion():
break
self.woutp.finalize(self)
def set_coefficients(self, coefficients):
self.c = np.array(coefficients)
def prepare(self):
#self.pot.calc(self.count)
self.pot.calc()
self.pre_judge_tsh()
self.check_ediff()
def step(self):
dt = self.dt
get_accelerations_save = self.mol.get_accelerations()
self.mol.set_positions(self.mol.get_positions() + \
self.mol.get_velocities() * dt + 0.5 * \
get_accelerations_save * dt * dt)
#self.pot.calc(self.count)
self.pot.calc()
self.mol.set_velocities(self.mol.get_velocities() + \
0.5 * (self.mol.get_accelerations() + \
get_accelerations_save) * dt)
self.elaptime += dt
def pre_judge_tsh(self):
self.pot_multi = self.pot.get_potential_energy_multi()
#print self.pot.get_inner_v_d()
#self.nac = np.diag(self.pot_multi) - 1.j*self.vd
self.nac = np.diag(self.pot_multi) - 1.j * self.pot.get_inner_v_d()
self.eig, self.trans = linalg.eigh(self.nac)
self.woutp.write_transition_prob(
"Time: {}, Count: {}, Current: {}\n".format(
self.elaptime * tau2fs, self.count, self.now_state))
def judge_tsh(self):
#print self.c
while self.count_tsh < self.tsh_times:
# solving eq.8 in the reference papaer
# for getting the expansion coordinate
# exponential expansion
c = np.dot(np.conjugate(self.trans).T, self.c)
c = np.dot(np.diag(np.exp(-1j * self.eig * self.delta_st)), c)
self.c = np.dot(self.trans, c)
print self.count_tsh, self.c
#print self.delta_st
# calculation of the swithing probability
# bkl =-2Re(akl*VDkl)
# gkj = deltat*bjk/akk
a = np.outer(self.c, np.conjugate(self.c))
b = -np.real(np.conjugate(a) * self.nac * 2.j)
#b = -2.0 * np.real(np.conjugate(a)*self.vd)
#print b
#print b2
# judgement
rand = random()
tot = 0.0
self.woutp.write_transition_prob("step{}: ".format(self.count_tsh))
for i in xrange(self.nrange):
self.woutp.write_transition_prob("a{}:{:5.3f} ".format(
i, a[i, i].real))
self.woutp.write_transition_prob(
"| rand:{:8.5f}\n Prob ".format(rand))
for i in xrange(self.nrange):
if i < self.now_state - 1 or i == self.now_state or i > self.now_state + 1:
continue
g = self.delta_st*b[i,self.now_state] / \
a[self.now_state,self.now_state].real
# log the hopping probability
self.woutp.write_transition_prob(" {}->{}:{:5.3f}".format(
self.now_state, i, g))
if tot < rand < tot + g:
self.woutp.write_transition_prob("\nHopping Starts\n")
self.woutp.write_trj_message(
"Hopping Starts [Probability Ocuuracne] \n")
if self.velocity_adjustment(i): return
tot += g
self.count_tsh += 1
self.woutp.write_transition_prob("\n")
def velocity_adjustment(self, cand_state):
# unit vector alog the mass-weighted coordinate
d = self.pot.get_velocity_adjustment_vecotr()[self.now_state,
cand_state]
d = d / self.m_root[:, np.newaxis]
d = d / linalg.norm(d)
velo = self.mol.get_velocities()
in_prd = np.sum(self.m_root[:, np.newaxis] * velo * d)
diff_pot12 = self.pot_multi[self.now_state] - \
self.pot_multi[cand_state]
in_root = in_prd**2 + 2 * diff_pot12
if in_root < 0:
# hopping failer because of the insuffiency of kinetic energy
self.woutp.write_trj_message(
"Hopping Failur [Kinetic Enerty Insuffiency]\n")
return False
else:
self.woutp.write_trj_message("Hopping Success!! State has changed from {0} to {1}\n"\
.format(self.now_state+1,cand_state+1))
self.woutp.write_trj_message("Velocitiies are adjusted\n")
# renewal for energy and force
# time integration restarts at the last configuration
n = sqrt(in_root) - in_prd
self.mol.set_velocities(velo + n * d / self.m_root[:, np.newaxis])
self.now_state = cand_state
self.pot.set_now_state(self.now_state)
self.pot.calc()
return True
def check_ediff(self):
#if np.any(np.diff(self.pot_multi) < self.tsh_ediff_thresh):
# self.dt = self.tsh_ediff_factor * self.dt_bak
#else:
# self.dt = self.dt_bak
if self.now_state < self.nrange - 1 and self.pot_multi[
self.now_state +
1] - self.pot_multi[self.now_state] < self.tsh_ediff_thresh:
self.dt = self.tsh_ediff_factor * self.dt_bak
elif self.now_state > 0 and self.pot_multi[
self.now_state] - self.pot_multi[self.now_state -
1] < self.tsh_ediff_thresh:
self.dt = self.tsh_ediff_factor * self.dt_bak
else:
self.dt = self.dt_bak
self.delta_st = 0.5 * self.dt / self.tsh_times
class TullySurfaceHopping(MolecularDynamics):
"""
Tully Surface Hopping method
is for dealng with non adiabatic transition process during classical MD simulation.
J. C. Tully, J. Chem. Phys. 93, 1061 (1990).
"""
def __init__(self, mol, pot, dt, nstep, tsh_times = 5, restart = False,\
tsh_ediff_thresh=0.1, tsh_ediff_factor=0.25, check_mdstop_dispersion = False,\
limit_dispersion = 10.0, tlim = float('inf')):
MolecularDynamics.__init__(self, mol, pot, dt, nstep, restart,\
check_mdstop_dispersion, limit_dispersion, tlim)
self.now_state = self.pot.get_now_state()
self.nrange = self.pot.get_nrange()
self.m_root = np.sqrt(self.mol.get_masses())
self.tsh_times = tsh_times
self.delta_st = 0.5 * self.dt / self.tsh_times
self.dt_bak = self.dt
self.tsh_ediff_thresh = tsh_ediff_thresh
self.tsh_ediff_factor = tsh_ediff_factor
self.c = np.zeros(self.nrange)
self.c[self.now_state] = 1.0
self.count = 0
self.count_tsh = 0
self.setup_output()
def setup_output(self):
self.woutp = WriteOutputMD_TSH()
if self.restart: self.woutp.restart(self)
else: self.woutp.start(self)
def run(self):
self.prepare()
self.woutp.logging(self)
while self.count < self.nstep:
self.count += 1
self.judge_tsh()
self.step()
self.pre_judge_tsh()
self.check_ediff()
self.judge_tsh()
self.count_tsh = 0
self.woutp.logging(self)
if self.mdstop_time_trans(): break
if self.check_mdstop_dispersion and self.mdstop_atom_dispersion(): break
self.woutp.finalize(self)
def set_coefficients(self, coefficients):
self.c = np.array(coefficients)
def prepare(self):
#self.pot.calc(self.count)
self.pot.calc()
self.pre_judge_tsh()
self.check_ediff()
def step(self):
dt = self.dt
get_accelerations_save = self.mol.get_accelerations()
self.mol.set_positions(self.mol.get_positions() + \
self.mol.get_velocities() * dt + 0.5 * \
get_accelerations_save * dt * dt)
#self.pot.calc(self.count)
self.pot.calc()
self.mol.set_velocities(self.mol.get_velocities() + \
0.5 * (self.mol.get_accelerations() + \
get_accelerations_save) * dt)
self.elaptime += dt
def pre_judge_tsh(self):
self.pot_multi = self.pot.get_potential_energy_multi()
#print self.pot.get_inner_v_d()
#self.nac = np.diag(self.pot_multi) - 1.j*self.vd
self.nac = np.diag(self.pot_multi) - 1.j*self.pot.get_inner_v_d()
self.eig, self.trans = linalg.eigh(self.nac)
self.woutp.write_transition_prob("Time: {}, Count: {}, Current: {}\n".format(self.elaptime * tau2fs, self.count, self.now_state))
def judge_tsh(self):
#print self.c
while self.count_tsh < self.tsh_times:
# solving eq.8 in the reference papaer
# for getting the expansion coordinate
# exponential expansion
c = np.dot(np.conjugate(self.trans).T, self.c)
c = np.dot(np.diag(np.exp(-1j*self.eig*self.delta_st)),c)
self.c = np.dot(self.trans,c)
print self.count_tsh, self.c
#print self.delta_st
# calculation of the swithing probability
# bkl =-2Re(akl*VDkl)
# gkj = deltat*bjk/akk
a = np.outer(self.c,np.conjugate(self.c))
b = -np.real(np.conjugate(a)*self.nac*2.j)
#b = -2.0 * np.real(np.conjugate(a)*self.vd)
#print b
#print b2
# judgement
rand = random()
tot = 0.0
self.woutp.write_transition_prob("step{}: ".format(self.count_tsh))
for i in xrange(self.nrange): self.woutp.write_transition_prob("a{}:{:5.3f} ".format(i,a[i,i].real))
self.woutp.write_transition_prob("| rand:{:8.5f}\n Prob ".format(rand))
for i in xrange(self.nrange):
if i < self.now_state - 1 or i == self.now_state or i > self.now_state + 1: continue
g = self.delta_st*b[i,self.now_state] / \
a[self.now_state,self.now_state].real
# log the hopping probability
self.woutp.write_transition_prob(" {}->{}:{:5.3f}".format(self.now_state,i,g))
if tot < rand < tot + g:
self.woutp.write_transition_prob("\nHopping Starts\n")
self.woutp.write_trj_message("Hopping Starts [Probability Ocuuracne] \n")
if self.velocity_adjustment(i): return
tot += g
self.count_tsh += 1
self.woutp.write_transition_prob("\n")
def velocity_adjustment(self,cand_state):
# unit vector alog the mass-weighted coordinate
d = self.pot.get_velocity_adjustment_vecotr()[self.now_state, cand_state]
d = d / self.m_root[:,np.newaxis]
d = d / linalg.norm(d)
velo = self.mol.get_velocities()
in_prd = np.sum(self.m_root[:,np.newaxis] * velo * d)
diff_pot12 = self.pot_multi[self.now_state] - \
self.pot_multi[cand_state]
in_root = in_prd ** 2 + 2 * diff_pot12
if in_root < 0:
# hopping failer because of the insuffiency of kinetic energy
self.woutp.write_trj_message("Hopping Failur [Kinetic Enerty Insuffiency]\n")
return False
else:
self.woutp.write_trj_message("Hopping Success!! State has changed from {0} to {1}\n"\
.format(self.now_state+1,cand_state+1))
self.woutp.write_trj_message("Velocitiies are adjusted\n")
# renewal for energy and force
# time integration restarts at the last configuration
n = sqrt(in_root) - in_prd
self.mol.set_velocities(velo + n * d / self.m_root[:,np.newaxis])
self.now_state = cand_state
self.pot.set_now_state(self.now_state)
self.pot.calc()
return True
def check_ediff(self):
#if np.any(np.diff(self.pot_multi) < self.tsh_ediff_thresh):
# self.dt = self.tsh_ediff_factor * self.dt_bak
#else:
# self.dt = self.dt_bak
if self.now_state < self.nrange -1 and self.pot_multi[self.now_state+1] - self.pot_multi[self.now_state] < self.tsh_ediff_thresh:
self.dt = self.tsh_ediff_factor * self.dt_bak
elif self.now_state > 0 and self.pot_multi[self.now_state] - self.pot_multi[self.now_state-1] < self.tsh_ediff_thresh:
self.dt = self.tsh_ediff_factor * self.dt_bak
else:
self.dt = self.dt_bak
self.delta_st = 0.5 * self.dt / self.tsh_times
