pseudos=my_qmc_pps,
jastrows=[('J1', 'bspline', 8, 4.0),
('J2', 'bspline', 8)],
calculations=[
vmc(walkers=1,
warmupsteps=20,
blocks=200,
steps=10,
substeps=2,
timestep=.4)
],
dependencies=(p2q, 'orbitals'))
sims.append(qmc)
# write input files and submit jobs
run_project(sims)
## additional runs for optimization and DMC
##
## to use, comment out "run_project" above and uncomment below
#linopt1 = linear(
# energy = 0.0,
# unreweightedvariance = 1.0,
# reweightedvariance = 0.0,
# timestep = 0.4,
# samples = 5120,
# warmupsteps = 50,
# blocks = 200,
# substeps = 1,
# nonlocalpp = True,
# usebuffer = True,
steps=10,
substeps=2,
timestep=.4)
],
dependencies=(conv, 'orbitals'),
)
qmc_optical = generate_qmcpack(
det_format='old',
identifier='vmc',
path='diamond/vmc_optical',
job=job(cores=16, threads=16, app='qmcpack', hours=1),
input_type='basic',
spin_polarized=True,
system=dia2,
excitation=['up', '0 3 4 4'], #
pseudos=['C.BFD.xml'],
jastrows=[],
calculations=[
vmc(walkers=16,
warmupsteps=20,
blocks=1000,
steps=10,
substeps=2,
timestep=.4)
],
dependencies=(conv, 'orbitals'),
)
run_project()
conv = generate_pw2qmcpack(
identifier = 'conv',
path = 'diamond/scf',
job = Job(cores=1,app='pw2qmcpack.x'),
write_psir = False,
dependencies = (scf,'orbitals')
)
qmc = generate_qmcpack(
identifier = 'vmc',
path = 'diamond/vmc',
job = Job(cores=16,threads=4,app='qmcapp'),
input_type = 'basic',
system = dia16,
pseudos = ['C.BFD.xml'],
jastrows = [],
calculations = [
vmc(
walkers = 1,
warmupsteps = 20,
blocks = 200,
steps = 10,
substeps = 2,
timestep = .4
)
],
dependencies = (conv,'orbitals')
)
run_project(scf,conv,qmc)
[ x/2+d/2 , x/2 , x/2 ]],
net_spin = 0,
tiling = (1,1,1),
kgrid = (1,1,1), # scf kgrid given below to enable symmetries
kshift = (0,0,0),
O = 6,
)
scf = generate_pwscf(
identifier = 'scf',
path = 'scf'+str(ind),
job = jobs['scf'],
input_type = 'generic',
calculation = 'scf',
input_dft = 'lda',
for kgtid in [(1,1,1), (2,2,2), (3,3,3)]:
ecutwfc = 200,
conv_thr = 1e-8,
nosym = True,
wf_collect = True,
system = O2,
# kgrid = (1,1,1),
pseudos = ['O.BFD.upf'],
ind += 1
)
scfs.append(scf)
run_project(scfs)
corrections=[],
jastrows=[],
calculations=[
vmc(
timestep=0.3,
warmupsteps=10,
blocks=80,
steps=5,
substeps=3,
#samplesperthread = 10,
samples=2048,
),
dmc(
timestep=0.01,
warmupsteps=10,
blocks=80,
steps=5,
nonlocalmoves=True,
),
dmc(
timestep=0.005,
warmupsteps=50,
blocks=80,
steps=5,
nonlocalmoves=True,
),
],
dependencies=[(conv, 'orbitals'), (optJ2, 'jastrow')])
run_project(scf, conv, qmc, optJ2, dmc_run)
],
dependencies=(conv, 'orbitals'),
)
qmc_minus.input.simulation.qmcsystem.particlesets.e.groups.u.size += 1
qmc_minus.input.simulation.qmcsystem.wavefunction.determinantset.slaterdeterminant.determinants.updet.size += 1
qmc_plus = generate_qmcpack(
det_format='old',
identifier='vmc',
path='diamond/vmc_+e',
job=job(cores=16, threads=16, app='qmcpack', hours=1),
input_type='basic',
spin_polarized=True,
system=dia2,
pseudos=['C.BFD.xml'],
jastrows=[],
calculations=[
vmc(walkers=16,
warmupsteps=20,
blocks=1000,
steps=10,
substeps=2,
timestep=.4)
],
dependencies=(conv, 'orbitals'),
)
qmc_plus.input.simulation.qmcsystem.particlesets.e.groups.u.size -= 1
qmc_plus.input.simulation.qmcsystem.wavefunction.determinantset.slaterdeterminant.determinants.updet.size -= 1
run_project(scf, nscf, conv, qmc_0, qmc_minus, qmc_plus)
timestep = 0.01, # dmc timestep (1/Ha)
warmupsteps = 50, # No. of MC steps before data is collected
blocks = 400, # No. of data blocks recorded in scalar.dat
steps = 5, # No. of steps per block
nonlocalmoves = True # use Casula's T-moves
), # (retains variational principle for NLPP's)
],
# workflow dependencies
dependencies = [(p2q,'orbitals'),
(opt,'jastrow')]
)
# nexus monitors all runs
run_project(sims)
# print out the total energy
performed_runs = not settings.generate_only and not settings.status_only
if performed_runs:
# get the qmcpack analyzer object
# it contains all of the statistically analyzed data from the run
qa = qmc.load_analyzer_image()
# get the local energy from dmc.dat
le = qa.dmc[1].dmc.LocalEnergy # dmc series 1, dmc.dat, local energy
# print the total energy for the 20 atom system
print 'The DMC ground state energy for C20 is:'
print ' {0} +/- {1} Ha'.format(le.mean,le.error)
#end if
kpoints=dia2_kpath['explicit_kpoints_abs_inv_B'],
C=4,
)
band = generate_pwscf(
identifier='nscf',
path='diamond/band',
job=job(nodes=1, app='pw.x', hours=1),
input_type='generic',
calculation='nscf',
input_dft='lda',
ecutwfc=200,
nspin=2,
conv_thr=1e-8,
nosym=True,
wf_collect=True,
system=dia2_kpts,
nbnd=8, #a sensible nbnd value can be given
verbosity='high', #verbosity must be set to high
pseudos=['C.BFD.upf'],
dependencies=(scf, 'charge_density'),
)
run_project(scf, band)
from pwscf_analyzer import PwscfAnalyzer
p = PwscfAnalyzer(band)
p.analyze()
p.plot_bandstructure()
print "VBM: {0}".format(p.bands.vbm)
print "CBM: {0}".format(p.bands.cbm)
steps=10,
substeps=2,
timestep=.4)
],
dependencies=(conv, 'orbitals'),
)
qmc_optical = generate_qmcpack(
det_format='old',
identifier='vmc',
path='diamond/vmc_optical',
job=job(cores=16, threads=16, app='qmcpack', hours=1),
input_type='basic',
spin_polarized=True,
system=dia2,
excitation=['up', '0 3 4 4'], #
pseudos=['C.BFD.xml'],
jastrows=[],
calculations=[
vmc(walkers=16,
warmupsteps=20,
blocks=1000,
steps=10,
substeps=2,
timestep=.4)
],
dependencies=(conv, 'orbitals'),
)
run_project(scf, nscf, conv, qmc_0, qmc_optical)
kshift = (1,1,1), # grid centered at supercell L point
pseudos = ['Ge.pbe-kjpaw.UPF'], # PBE pseudopotential
system = T_system # the interstitial system
)
# link together the simulation cascade
# current relax gets structure from previous
if len(relaxations)>0: # if it exists
relax.depends(relaxations[-1],'structure')
#end if
relaxations.append(relax) # add relax simulation to the list
#end for
# perform the simulations
run_project(relaxations)
# analyze the results
performed_runs = not settings.generate_only and not settings.status_only
if performed_runs:
print
print 'Relaxation results:'
print '-------------------'
print ' kgrid starting force max force # of cycles'
for ik in range(len(supercell_kgrids)):
kgrid = supercell_kgrids[ik]
relax = relaxations[ik]
pa = relax.load_analyzer_image()
start_force = pa.tot_forces[0]
print b+'net charge:',dia16vac.net_charge
scf = generate_pwscf(
identifier = 'scf',
path = 'diamond/scf',
job = scf_job,
input_type = 'generic',
calculation = 'scf',
input_dft = 'lda',
ecutwfc = 200,
mixing_beta = 0.2,
degauss = 0.01,
conv_thr = 1e-6,
system = dia16vac,
kgrid = (3,3,3),
kshift = (0,0,0),
pseudos = ['C.BFD.upf'],
)
print b+'scf directory:',scf.locdir
si = scf.input
print b+'scf input data\n',si
print b+'scf input file\n',si.write()
pm = run_project()
print b+'status after execute:'
pm.write_simulation_status()
sa = scf.load_analyzer_image()
print b+'DFT Energy:',sa.E
jobs = get_taito_configs()
dia16 = generate_physical_system(units='A',
axes=[[1.785, 1.785, 0.], [0., 1.785, 1.785],
[1.785, 0., 1.785]],
elem=['C', 'C'],
pos=[[0., 0., 0.], [0.8925, 0.8925, 0.8925]],
tiling=(2, 2, 2),
kgrid=(1, 1, 1),
kshift=(0, 0, 0),
C=4)
scf = generate_pwscf(
identifier='scf',
path='scf',
job=jobs['scf'],
input_type='generic',
calculation='scf',
input_dft='lda',
ecutwfc=200,
conv_thr=1e-8,
nosym=True,
wf_collect=True,
system=dia16,
kgrid=(1, 1, 1),
pseudos=['C.BFD.upf'],
)
run_project(scf)
conv_thr=1e-6, # convergence threshold
kgrid=kgrid, # supercell k-point grid
kshift=(1, 1, 1), # grid centered at supercell L point
pseudos=['Ge.pbe-kjpaw.UPF'], # PBE pseudopotential
system=T_system, # the interstitial system
)
# link together the simulation cascade
# current relax gets structure from previous
if len(relaxations) > 0: # if it exists
relax.depends(relaxations[-1], 'structure')
#end if
relaxations.append(relax) # add relax simulation to the list
#end for
# perform the simulations
run_project(relaxations)
# analyze the results
performed_runs = not settings.generate_only and not settings.status_only
if performed_runs:
print
print 'Relaxation results:'
print '-------------------'
print ' kgrid starting force max force # of cycles'
for ik in range(len(supercell_kgrids)):
kgrid = supercell_kgrids[ik]
relax = relaxations[ik]
pa = relax.load_analyzer_image()
start_force = pa.tot_forces[0]
max_force = pa.tot_forces.max()
ncycles = len(pa.tot_forces)